UPSC CMS 2024 2025 previous year questions high yield topics syllabus

UPSC CMS exam pattern paper 1 paper 2 important topics 2025 2026

mkdir -p /home/daytona/workspace/upsc-cms-notes && ls /home/daytona/workspace/up…

~/upsc-cms-notes/generate_notes.py

from reportlab.lib.pagesizes import A4
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm
from reportlab.lib import colors
from reportlab.platypus import (SimpleDocTemplate, Paragraph, Spacer, Table,
                                 TableStyle, PageBreak, HRFlowable)
from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_JUSTIFY
from reportlab.platypus import KeepTogether

OUTPUT = "/home/daytona/workspace/upsc-cms-notes/UPSC_CMS_HighYield_Notes_2026.pdf"

doc = SimpleDocTemplate(
    OUTPUT, pagesize=A4,
    rightMargin=1.8*cm, leftMargin=1.8*cm,
    topMargin=2*cm, bottomMargin=2*cm
)

styles = getSampleStyleSheet()

# Custom styles
COVER_TITLE = ParagraphStyle('CoverTitle', fontSize=28, textColor=colors.HexColor('#1a237e'),
                              alignment=TA_CENTER, spaceAfter=12, fontName='Helvetica-Bold')
COVER_SUB = ParagraphStyle('CoverSub', fontSize=14, textColor=colors.HexColor('#283593'),
                            alignment=TA_CENTER, spaceAfter=8, fontName='Helvetica')
COVER_DATE = ParagraphStyle('CoverDate', fontSize=13, textColor=colors.HexColor('#b71c1c'),
                             alignment=TA_CENTER, spaceAfter=6, fontName='Helvetica-Bold')

PAPER_TITLE = ParagraphStyle('PaperTitle', fontSize=18, textColor=colors.white,
                              alignment=TA_CENTER, spaceAfter=4, spaceBefore=4, fontName='Helvetica-Bold')
SUBJECT_TITLE = ParagraphStyle('SubjectTitle', fontSize=14, textColor=colors.HexColor('#1a237e'),
                                spaceAfter=6, spaceBefore=12, fontName='Helvetica-Bold')
TOPIC_TITLE = ParagraphStyle('TopicTitle', fontSize=11, textColor=colors.HexColor('#1565c0'),
                              spaceAfter=4, spaceBefore=8, fontName='Helvetica-Bold')
BULLET = ParagraphStyle('Bullet', fontSize=9.5, leftIndent=14, spaceAfter=2,
                         fontName='Helvetica', leading=14)
SUBBULLET = ParagraphStyle('SubBullet', fontSize=9, leftIndent=28, spaceAfter=2,
                            fontName='Helvetica', textColor=colors.HexColor('#333333'), leading=13)
HIGHLIGHT = ParagraphStyle('Highlight', fontSize=9.5, leftIndent=14, spaceAfter=2,
                            fontName='Helvetica-Bold', textColor=colors.HexColor('#b71c1c'), leading=14)
MNEMONIC = ParagraphStyle('Mnemonic', fontSize=9.5, leftIndent=14, spaceAfter=2,
                           fontName='Helvetica-Bold', textColor=colors.HexColor('#6a1b9a'), leading=14,
                           backColor=colors.HexColor('#f3e5f5'), borderPadding=4)
NOTE = ParagraphStyle('Note', fontSize=9, leftIndent=14, spaceAfter=3,
                       fontName='Helvetica-Oblique', textColor=colors.HexColor('#004d40'), leading=13)

def paper_header(title, color_hex='#1a237e'):
    tbl = Table([[Paragraph(title, PAPER_TITLE)]], colWidths=[17*cm])
    tbl.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), colors.HexColor(color_hex)),
        ('ROUNDEDCORNERS', [8]),
        ('TOPPADDING', (0,0), (-1,-1), 8),
        ('BOTTOMPADDING', (0,0), (-1,-1), 8),
    ]))
    return tbl

def subject_box(title, color_hex='#e3f2fd'):
    tbl = Table([[Paragraph(title, SUBJECT_TITLE)]], colWidths=[17*cm])
    tbl.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), colors.HexColor(color_hex)),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('LINEBELOW', (0,0), (-1,-1), 2, colors.HexColor('#1565c0')),
    ]))
    return tbl

def b(text): return Paragraph(f"• {text}", BULLET)
def sb(text): return Paragraph(f"  ◦ {text}", SUBBULLET)
def h(text): return Paragraph(f"★ {text}", HIGHLIGHT)
def mn(text): return Paragraph(f"🧠 Mnemonic: {text}", MNEMONIC)
def note(text): return Paragraph(f"📌 {text}", NOTE)
def topic(text): return Paragraph(text, TOPIC_TITLE)
def sp(n=4): return Spacer(1, n)
def hr(): return HRFlowable(width="100%", thickness=0.5, color=colors.HexColor('#bdbdbd'))

story = []

# ─── COVER PAGE ─────────────────────────────────────────────────────────────
story += [
    Spacer(1, 3*cm),
    Paragraph("UPSC CMS 2026", COVER_TITLE),
    Paragraph("HIGH-YIELD MASTER NOTES", ParagraphStyle('ct2', fontSize=22, textColor=colors.HexColor('#283593'),
              alignment=TA_CENTER, spaceAfter=10, fontName='Helvetica-Bold')),
    Spacer(1, 0.5*cm),
    HRFlowable(width="80%", thickness=2, color=colors.HexColor('#1a237e'), hAlign='CENTER'),
    Spacer(1, 0.4*cm),
    Paragraph("All 4 Subjects | PYQ-Based | Final Revision Ready", COVER_SUB),
    Spacer(1, 0.3*cm),
    Paragraph("EXAM DATE: 2nd AUGUST 2026", COVER_DATE),
    Spacer(1, 0.5*cm),
    HRFlowable(width="80%", thickness=2, color=colors.HexColor('#1a237e'), hAlign='CENTER'),
    Spacer(1, 1*cm),
]

cover_info = [
    ["PAPER I", "General Medicine (96 Qs) + Paediatrics (24 Qs)"],
    ["PAPER II", "Surgery (40 Qs) + Gyn & Obs (40 Qs) + PSM (40 Qs)"],
    ["Total", "240 Questions | 500 Marks | 4 Hours"],
    ["Negative Marking", "1/3 mark deducted per wrong answer"],
]
tbl = Table(cover_info, colWidths=[5*cm, 12*cm])
tbl.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (0,-1), colors.HexColor('#e8eaf6')),
    ('BACKGROUND', (1,0), (1,-1), colors.HexColor('#fafafa')),
    ('FONTNAME', (0,0), (0,-1), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 10),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#9fa8da')),
    ('ROWBACKGROUNDS', (0,0), (-1,-1), [colors.HexColor('#e8eaf6'), colors.HexColor('#c5cae9')]),
    ('TOPPADDING', (0,0), (-1,-1), 7),
    ('BOTTOMPADDING', (0,0), (-1,-1), 7),
    ('LEFTPADDING', (0,0), (-1,-1), 10),
]))
story.append(tbl)
story.append(PageBreak())

# ══════════════════════════════════════════════════════════════════
#  PAPER I — GENERAL MEDICINE
# ══════════════════════════════════════════════════════════════════
story.append(paper_header("PAPER I — GENERAL MEDICINE & PAEDIATRICS", '#1a237e'))
story.append(sp(8))
story.append(subject_box("GENERAL MEDICINE (96 Questions)", '#e3f2fd'))
story.append(sp(4))

# --- CARDIOLOGY ---
story.append(topic("1. CARDIOLOGY ⭐⭐⭐ (Most Repeated)"))
story.append(b("<b>Rheumatic Fever (Jones Criteria)</b>"))
story.append(sb("Major: Carditis, Polyarthritis, Chorea, Erythema marginatum, Subcutaneous nodules"))
story.append(sb("Minor: Fever, Raised ESR/CRP, Prolonged PR interval, Arthralgia"))
story.append(sb("Diagnosis: 2 Major OR 1 Major + 2 Minor + evidence of Strep infection"))
story.append(mn("SPEC = Subcutaneous nodules, Polyarthritis, Erythema marginatum, Carditis, Chorea"))
story.append(b("<b>Heart Failure</b>"))
story.append(sb("HFrEF (EF<40%): ACEi/ARB + Beta-blocker + Spironolactone + Diuretics"))
story.append(sb("NYHA Class I-IV: I=no symptoms, II=mild exertion, III=less than ordinary, IV=rest"))
story.append(sb("BNP >100 pg/mL = heart failure; >400 = severe"))
story.append(sb("DAPA-HF trial: Dapagliflozin reduces mortality in HFrEF"))
story.append(b("<b>Atrial Fibrillation</b>"))
story.append(sb("CHA2DS2-VASc score → anticoagulation if ≥2 (male) or ≥3 (female)"))
story.append(sb("Rate control: Beta-blockers, Diltiazem, Digoxin"))
story.append(sb("Rhythm control: Amiodarone, Flecainide"))
story.append(b("<b>MI — STEMI vs NSTEMI</b>"))
story.append(sb("STEMI: ST elevation + new LBBB → emergent PCI within 90 min (door-to-balloon)"))
story.append(sb("Thrombolytics if PCI not available within 120 min: Streptokinase, tPA"))
story.append(sb("Wellens syndrome: Biphasic/deep T-wave inversion in V2-V3 → LAD stenosis"))
story.append(sb("Dressler syndrome: Autoimmune pericarditis 2–10 weeks post-MI"))
story.append(b("<b>Hypertension</b>"))
story.append(sb("HTN emergency: BP >180/120 + end-organ damage → IV labetalol/nitroprusside"))
story.append(sb("JNC 8 targets: General <140/90; DM/CKD <140/90"))
story.append(sb("Drugs of choice: DM→ACEi; CKD→ACEi; Pregnancy→Methyldopa/Labetalol/Nifedipine"))
story.append(b("<b>Valvular Heart Disease — PYQ Favourites</b>"))
tbl_valve = Table([
    ["Valve Lesion", "Classic Sign", "Best Heard"],
    ["Mitral Stenosis", "Loud S1, Opening snap, MDM", "Apex, left lateral decubitus"],
    ["Mitral Regurgitation", "Soft S1, Pansystolic murmur", "Apex → axilla"],
    ["Aortic Stenosis", "Slow rising pulse, ESM", "Aortic area → carotids"],
    ["Aortic Regurgitation", "Wide pulse pressure, Early diastolic", "Left sternal edge"],
], colWidths=[4.5*cm, 7*cm, 5.5*cm])
tbl_valve.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1565c0')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#90caf9')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e3f2fd')]),
    ('TOPPADDING', (0,0), (-1,-1), 5),
    ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_valve)
story.append(sp(6))
story.append(h("De Musset sign (head nodding), Corrigan's pulse, Quincke's sign = AR"))
story.append(h("MS with AF = DO NOT give digoxin as sole therapy; add anticoagulation"))

# --- RESPIRATORY ---
story.append(sp(6))
story.append(topic("2. RESPIRATORY DISEASES ⭐⭐⭐"))
story.append(b("<b>Asthma vs COPD</b>"))
tbl_resp = Table([
    ["Feature", "Asthma", "COPD"],
    ["Age", "Any (often young)", ">40 years"],
    ["Cause", "Allergy/atopy", "Smoking (>90%)"],
    ["Reversibility", "Fully reversible", "Partially reversible"],
    ["Gold standard Dx", "Spirometry (FEV1/FVC<0.7 + BD reversibility)", "Post-BD FEV1/FVC<0.7"],
    ["Eosinophilia", "Common", "Uncommon"],
], colWidths=[4*cm, 6.5*cm, 6.5*cm])
tbl_resp.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1565c0')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#90caf9')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e3f2fd')]),
    ('TOPPADDING', (0,0), (-1,-1), 5),
    ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_resp)
story.append(sp(4))
story.append(b("<b>COPD Management (GOLD Strategy)</b>"))
story.append(sb("GOLD 1 (FEV1≥80%): SABA PRN"))
story.append(sb("GOLD 2-3 (FEV1 50-79%): LAMA or LABA"))
story.append(sb("GOLD 4 (FEV1<30%): LAMA+LABA ± ICS, O2 if PaO2<55mmHg"))
story.append(sb("AECOPD: Salbutamol + Ipratropium + prednisolone 40mg x 5d + Abx (Azithromycin/Amoxicillin)"))
story.append(b("<b>Pneumonia</b>"))
story.append(sb("CURB-65: Confusion, Urea>7, RR>30, BP<90/60, Age>65 — score ≥2 = admit"))
story.append(sb("CAP: Amoxicillin ± Macrolide; severe: Beta-lactam + Macrolide or Fluoroquinolone"))
story.append(sb("HAP (>48h in hospital): Piperacillin-tazobactam or Cefepime ± Vancomycin"))
story.append(b("<b>Pleural Effusion — Light's Criteria (Exudate = any one)</b>"))
story.append(sb("Pleural protein/serum protein >0.5"))
story.append(sb("Pleural LDH/serum LDH >0.6"))
story.append(sb("Pleural LDH > 2/3 upper normal serum LDH"))
story.append(h("TB effusion: lymphocytic exudate, ADA >40 U/L, low glucose"))
story.append(b("<b>Tuberculosis (High Yield)</b>"))
story.append(sb("Primary TB: Ghon focus + hilar LN = Ghon complex; Ranke complex = calcified Ghon complex"))
story.append(sb("Miliary TB: CT shows 1-3mm nodules; CSF: lymphocytosis, high protein, low glucose"))
story.append(sb("Treatment: 2HRZE / 4HR (Isoniazid, Rifampicin, Pyrazinamide, Ethambutol)"))
story.append(sb("MDR-TB: Resistant to INH + Rifampicin; XDR = MDR + fluoroquinolone + injectable"))
story.append(sb("INH side effects: Peripheral neuropathy (Pyridoxine protects), hepatotoxicity"))
story.append(sb("Rifampicin: Orange urine, hepatotoxicity, enzyme inducer"))
story.append(mn("RIPE = Rifampicin, INH, Pyrazinamide, Ethambutol"))
story.append(sp(4))

# --- INFECTIOUS DISEASES ---
story.append(topic("3. INFECTIOUS DISEASES ⭐⭐⭐ (Very High Yield)"))
story.append(b("<b>Malaria</b>"))
story.append(sb("P. falciparum: Malignant tertian, cerebral malaria, blackwater fever, most dangerous"))
story.append(sb("P. vivax/ovale: Benign tertian, hypnozoites (use Primaquine to eradicate)"))
story.append(sb("P. malariae: Quartan malaria, nephrotic syndrome"))
story.append(sb("Diagnosis: Peripheral smear (gold standard); RDT detects HRP2 (falciparum)"))
story.append(sb("Treatment: Uncomplicated falciparum → ACT (Artemether + Lumefantrine)"))
story.append(sb("Severe malaria → IV Artesunate (first line) or IV Quinine"))
story.append(h("Trophozoite of P. falciparum = Appliqué/Accolé form; Schuffner's dots in P. vivax"))
story.append(b("<b>Dengue Fever</b>"))
story.append(sb("Serotypes: 4 (DENV 1-4); secondary infection with different serotype → DHF/DSS"))
story.append(sb("Warning signs: Abdominal pain, persistent vomiting, bleeding, rapid clinical deterioration"))
story.append(sb("NS1 antigen: Positive in first 5 days; IgM after day 5"))
story.append(sb("Management: Supportive; no aspirin/NSAIDs; platelet transfuse if <10,000 or bleeding"))
story.append(h("Dengue NS1 + IgM/IgG combo test = most used rapid diagnosis"))
story.append(b("<b>Typhoid</b>"))
story.append(sb("Salmonella typhi; feco-oral route; relative bradycardia (Faget's sign)"))
story.append(sb("Rose spots on abdomen; Widal test (TO ≥1:160, TH ≥1:160)"))
story.append(sb("Gold standard: Blood culture (1st week); stool/urine culture (3rd week)"))
story.append(sb("Treatment: Azithromycin (uncomplicated); IV Ceftriaxone (severe/complicated)"))
story.append(sb("Complications: Intestinal perforation (ileum), haemorrhage, hepatitis"))
story.append(b("<b>Leptospirosis</b>"))
story.append(sb("Weil's disease: Severe form with jaundice + renal failure + bleeding"))
story.append(sb("Pathogen: Leptospira interrogans; zoonosis via rat urine contaminated water"))
story.append(sb("Dx: IgM ELISA / MAT; Treatment: Doxycycline (mild), Penicillin G / Ceftriaxone (severe)"))
story.append(b("<b>HIV/AIDS</b>"))
story.append(sb("CD4 <200: PCP (Pneumocystis jirovecii) → Cotrimoxazole prophylaxis"))
story.append(sb("CD4 <100: Toxoplasma, Cryptococcus, CMV retinitis"))
story.append(sb("CD4 <50: MAC (Mycobacterium avium complex) → Azithromycin prophylaxis"))
story.append(sb("ART: Tenofovir + Lamivudine + Efavirenz (first line in India)"))
story.append(sb("IRIS: Immune reconstitution inflammatory syndrome — 4-8 weeks after ART"))
story.append(h("PCP treatment: High-dose Co-trimoxazole; severe PCP: add Prednisolone"))
story.append(sp(4))

# --- NEUROLOGY ---
story.append(topic("4. NEUROLOGY ⭐⭐⭐"))
story.append(b("<b>Stroke</b>"))
story.append(sb("Ischaemic stroke: IV tPA within 4.5h of symptom onset (if no contraindications)"))
story.append(sb("Mechanical thrombectomy: Up to 24h if large vessel occlusion"))
story.append(sb("Haemorrhagic stroke: Reverse anticoagulation; BP target <140 systolic"))
story.append(sb("NIHSS score used to assess stroke severity"))
story.append(b("<b>Meningitis</b>"))
tbl_mening = Table([
    ["Type", "Cell count", "Protein", "Glucose", "Organism"],
    ["Bacterial", "PMN >1000", "High (>1g/L)", "<45 or <2/3 serum", "Pneumococcus, Meningococcus, Listeria"],
    ["Viral", "Lymphocytes 50-500", "Mildly high", "Normal", "Enteroviruses, HSV"],
    ["TB", "Lymphocytes 100-400", "Very high", "Very low", "M. tuberculosis"],
    ["Fungal", "Lymphocytes", "High", "Low", "Cryptococcus"],
], colWidths=[2.5*cm, 3.2*cm, 3.2*cm, 3.2*cm, 4.9*cm])
tbl_mening.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1565c0')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 7.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#90caf9')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e3f2fd')]),
    ('TOPPADDING', (0,0), (-1,-1), 4),
    ('BOTTOMPADDING', (0,0), (-1,-1), 4),
    ('LEFTPADDING', (0,0), (-1,-1), 4),
]))
story.append(tbl_mening)
story.append(sp(4))
story.append(b("<b>Parkinson's Disease</b>"))
story.append(sb("TRAP: Tremor (resting, pill-rolling), Rigidity (cogwheel), Akinesia, Postural instability"))
story.append(sb("Dopamine deficiency in substantia nigra (pars compacta)"))
story.append(sb("Treatment: Levodopa + Carbidopa (first line); MAOB inhibitors (Selegiline)"))
story.append(sb("On-off phenomenon, dyskinesia = long-term levodopa side effects"))
story.append(b("<b>Epilepsy</b>"))
story.append(sb("Focal seizures: No LOC (aware) vs LOC (impaired awareness)"))
story.append(sb("Generalised tonic-clonic: Valproate or Levetiracetam first line"))
story.append(sb("Absence seizures: Ethosuximide (first line); Valproate second"))
story.append(sb("Status epilepticus: Lorazepam IV → Phenytoin → Phenobarbitone → RSI/Propofol"))
story.append(h("Carbamazepine: Drug of choice for Trigeminal Neuralgia"))
story.append(sp(4))

# --- ENDOCRINOLOGY ---
story.append(topic("5. ENDOCRINOLOGY ⭐⭐⭐"))
story.append(b("<b>Diabetes Mellitus</b>"))
story.append(sb("Diagnostic criteria: FBS ≥126, RBS ≥200 + symptoms, OGTT 2h ≥200, HbA1c ≥6.5%"))
story.append(sb("DKA: High AG metabolic acidosis, hyperglycaemia, ketonemia; pH <7.3"))
story.append(sb("DKA Rx: IV fluids (Normal saline) + Insulin infusion + K+ replacement"))
story.append(sb("HHS (Hyperosmolar): BG >600, osmolality >320, NO significant ketosis; older T2DM"))
story.append(sb("Metformin: First line T2DM; CI: eGFR<30, contrast media, hepatic failure"))
story.append(sb("SGLT2 inhibitors: Cardioprotective + renoprotective (Empagliflozin, Dapagliflozin)"))
story.append(sb("GLP-1 agonists: Weight loss + CV benefit (Semaglutide, Liraglutide)"))
story.append(h("Somogyi effect: Rebound hyperglycaemia after nocturnal hypoglycaemia"))
story.append(h("Dawn phenomenon: Early morning hyperglycaemia due to GH + cortisol rise"))
story.append(b("<b>Thyroid Disorders</b>"))
story.append(sb("Hypothyroidism: Raised TSH, Low T4; Myxoedema coma → IV T4 + steroids"))
story.append(sb("Hyperthyroidism: Low TSH, High T3/T4; Graves = TSH-R antibodies (TRAb)"))
story.append(sb("Thyroid storm: Propylthiouracil + Lugol's iodine + beta-blocker + steroids"))
story.append(sb("Sick euthyroid: Low T3, normal/low T4, normal TSH — in critically ill"))
story.append(sb("Papillary carcinoma: Most common thyroid cancer; Psammoma bodies"))
story.append(sb("Medullary carcinoma: Calcitonin marker; associated with MEN 2A/2B"))
story.append(b("<b>Adrenal Disorders</b>"))
story.append(sb("Addison's: Low cortisol, low aldosterone; Hypo-Na, Hyper-K, Hypoglycaemia, bronzed skin"))
story.append(sb("Cushing's: High cortisol; Central obesity, purple striae, osteoporosis, HTN, DM"))
story.append(sb("Addisonian crisis: IV hydrocortisone 100mg stat + saline; do not delay for test"))
story.append(sb("Phaeochromocytoma: Rule of 10s; diagnosis: 24h urinary metanephrines"))
story.append(mn("CHAPS = Cushing: HTN, Acne, Pigmentation, Striae"))
story.append(sp(4))

# --- NEPHROLOGY ---
story.append(topic("6. NEPHROLOGY ⭐⭐"))
story.append(b("<b>Acute Kidney Injury (AKIN/KDIGO)</b>"))
story.append(sb("Stage 1: Cr x1.5-1.9 or rise ≥0.3mg/dL; Stage 2: Cr x2-2.9; Stage 3: Cr x3 or RRT"))
story.append(sb("Pre-renal: FENa<1%, BUN/Cr>20; Renal: FENa>2%; Post-renal: hydronephrosis"))
story.append(b("<b>Nephritic vs Nephrotic</b>"))
tbl_neph = Table([
    ["Feature", "Nephritic", "Nephrotic"],
    ["Proteinuria", "<3.5g/day", ">3.5g/day"],
    ["Haematuria", "Yes (RBC casts)", "No"],
    ["HTN", "Common", "Common"],
    ["Oedema", "Periorbital", "Generalised (anasarca)"],
    ["Cholesterol", "Normal", "High"],
    ["Examples", "IgA nephropathy, PSGN", "Minimal Change (MCD), FSGS, Membranous"],
], colWidths=[4*cm, 6.5*cm, 6.5*cm])
tbl_neph.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1565c0')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#90caf9')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e3f2fd')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_neph)
story.append(sp(4))
story.append(h("IgA nephropathy (Berger's): Episodic haematuria with URI; most common GN worldwide"))
story.append(h("PSGN: Latent period 1-3 weeks post strep throat; Low C3; self-limiting"))
story.append(b("<b>Acid-Base Disorders</b>"))
story.append(sb("Metabolic acidosis: pH↓, HCO3↓; HAGMA causes: MUDPILES (Methanol, Uraemia, DKA, Propylene glycol, INH, Lactic acidosis, Ethylene glycol, Salicylates)"))
story.append(sb("Respiratory alkalosis: Hyperventilation, PE, pregnancy, anxiety"))
story.append(sb("AG = Na - (Cl + HCO3); Normal 8-12 mEq/L"))
story.append(sp(4))

# --- GASTROENTEROLOGY ---
story.append(topic("7. GASTROENTEROLOGY ⭐⭐"))
story.append(b("<b>Liver Disease</b>"))
story.append(sb("Child-Pugh score: Bilirubin, Albumin, PT/INR, Ascites, Encephalopathy"))
story.append(sb("MELD score: Bilirubin + INR + Creatinine → transplant listing"))
story.append(sb("SBP: Ascites PMN >250/mm3; treat with Cefotaxime; Albumin prevents hepatorenal"))
story.append(sb("Hepatic encephalopathy: Lactulose + Rifaximin; avoid sedatives"))
story.append(sb("Varices: Propranolol for prophylaxis; acute bleed: Terlipressin + Endoscopy"))
story.append(b("<b>Inflammatory Bowel Disease</b>"))
tbl_ibd = Table([
    ["Feature", "Crohn's Disease", "Ulcerative Colitis"],
    ["Location", "Any GI tract (mouth to anus)", "Colon only (rectum upward)"],
    ["Pattern", "Skip lesions", "Continuous"],
    ["Depth", "Transmural", "Mucosal only"],
    ["Biopsy", "Non-caseating granulomas", "Crypt abscesses"],
    ["Complications", "Fistula, stricture, abscess", "Toxic megacolon, cancer"],
], colWidths=[4*cm, 6.5*cm, 6.5*cm])
tbl_ibd.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1565c0')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#90caf9')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e3f2fd')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_ibd)
story.append(sp(6))
story.append(h("Lead pipe colon on X-ray = UC; String sign of Kantor = Crohn's"))

# --- HAEMATOLOGY ---
story.append(sp(4))
story.append(topic("8. HAEMATOLOGY ⭐⭐"))
story.append(b("<b>Anaemia Classification</b>"))
story.append(sb("Microcytic (MCV<80): IDA, Thalassaemia, Sideroblastic, Anaemia of chronic disease"))
story.append(sb("Macrocytic (MCV>100): B12/Folate deficiency, Hypothyroidism, Liver disease, Drugs (Hydroxyurea)"))
story.append(sb("Normocytic: Haemolytic, Aplastic, Acute blood loss, ACD"))
story.append(b("<b>Iron Deficiency vs Thalassaemia</b>"))
story.append(sb("IDA: Low Fe, Low ferritin, High TIBC, Low transferrin saturation"))
story.append(sb("Thalassaemia trait: Normal Fe, Ferritin; High HbA2 (beta-thal trait >3.5%)"))
story.append(sb("Mentzer index: MCV/RBC <13 = Thalassaemia; >13 = IDA"))
story.append(b("<b>Haemolytic Anaemia</b>"))
story.append(sb("G6PD deficiency: X-linked; triggered by primaquine, dapsone, fava beans, infections"))
story.append(sb("Spherocytes = Hereditary spherocytosis + Autoimmune haemolytic anaemia"))
story.append(sb("Direct Coombs = AIHA; Indirect = alloantibodies"))
story.append(b("<b>Coagulation Disorders</b>"))
story.append(sb("Haemophilia A: Factor VIII deficiency; Haemophilia B: Factor IX deficiency"))
story.append(sb("PT measures: Extrinsic + common pathway (Factors II,V,VII,X)"))
story.append(sb("APTT measures: Intrinsic + common pathway (Factors VIII, IX, XI, XII)"))
story.append(sb("DIC: All parameters deranged — Low platelets, High PT, High APTT, Low fibrinogen, High D-dimer"))
story.append(h("Von Willebrand disease: Most common inherited bleeding disorder; prolonged APTT + BT"))
story.append(sp(4))

# --- DERMATOLOGY ---
story.append(topic("9. DERMATOLOGY ⭐⭐"))
story.append(b("<b>Pemphigus vs Pemphigoid</b>"))
story.append(sb("Pemphigus vulgaris: IgG vs desmoglein 1&3; intraepidermal blister; Nikolsky sign +ve"))
story.append(sb("Bullous pemphigoid: IgG vs BPAG1/2; subepidermal blister; Nikolsky sign -ve; elderly"))
story.append(b("<b>Psoriasis</b>"))
story.append(sb("Auspitz sign: Bleeding on removal of scale; Koebner phenomenon; Nail pitting"))
story.append(sb("Methotrexate, Ciclosporin for severe disease; Biologics (Anti-TNF) for refractory"))
story.append(b("<b>High-Yield Drug-Induced Skin Reactions</b>"))
story.append(sb("Stevens-Johnson Syndrome / TEN: Carbamazepine, Allopurinol, Sulphonamides, Phenytoin"))
story.append(sb("Fixed drug eruption: NSAIDs, Tetracycline, Cotrimoxazole"))
story.append(sb("Lichenoid reaction: Beta-blockers, Gold, Antimalarials"))
story.append(sp(4))

# --- PSYCHIATRY ---
story.append(topic("10. PSYCHIATRY ⭐⭐"))
story.append(b("<b>Antipsychotics</b>"))
story.append(sb("Typical (FGA): Haloperidol, Chlorpromazine; EPS side effects (EPSE)"))
story.append(sb("Atypical (SGA): Olanzapine (metabolic), Clozapine (agranulocytosis), Risperidone"))
story.append(sb("NMS: Rigidity, Hyperthermia, Autonomic instability, Altered consciousness → stop drug, Dantrolene"))
story.append(b("<b>Mood Disorders</b>"))
story.append(sb("Depression: 2+ weeks; core = depressed mood, anhedonia, low energy; SSRIs first line"))
story.append(sb("Bipolar: Lithium (first line maintenance); valproate/lamotrigine alternatives"))
story.append(sb("Lithium toxicity: Tremor, polyuria, hypothyroidism; toxic >1.5 mmol/L; narrow TI"))
story.append(b("<b>Anxiety Disorders</b>"))
story.append(sb("Panic disorder: SSRIs + CBT; acute = Benzodiazepines (short-term only)"))
story.append(sb("OCD: SSRIs (high dose) + CBT; Clomipramine second line"))
story.append(sp(4))

# --- EMERGENCY / POISONING ---
story.append(topic("11. EMERGENCY MEDICINE & POISONING ⭐⭐⭐ (PYQ Favourite)"))
story.append(b("<b>Organophosphate Poisoning (Very High Yield)</b>"))
story.append(sb("Inhibits acetylcholinesterase → SLUDGE: Salivation, Lacrimation, Urination, Defecation, GI cramps, Emesis"))
story.append(sb("Also: Miosis, Bradycardia, Bronchospasm, Muscle fasciculations → paralysis"))
story.append(sb("Treatment: Atropine (counteracts muscarinic) + Pralidoxime (within 48h, before ageing)"))
story.append(b("<b>Carbon Monoxide Poisoning</b>"))
story.append(sb("Cherry-red skin; carboxyhaemoglobin; SpO2 falsely normal; PaO2 normal"))
story.append(sb("Treatment: 100% O2 via non-rebreather mask; hyperbaric O2 if severe"))
story.append(b("<b>Paracetamol Overdose</b>"))
story.append(sb("Phase 1: N&V; Phase 2: RUQ pain; Phase 3: Hepatic failure; Phase 4: Recovery/death"))
story.append(sb("Treatment: N-Acetylcysteine (NAC) within 8h; use Rumack-Matthew nomogram"))
story.append(b("<b>Snakebite</b>"))
story.append(sb("Viper: Haemotoxic (DIC, local tissue necrosis); Elapid: Neurotoxic (ptosis, bulbar palsy)"))
story.append(sb("20-minute Whole Blood Clotting Test (20WBCT): Fails to clot = viper envenomation"))
story.append(sb("Treatment: Polyvalent antivenom; neostigmine for elapid neurotoxicity"))
story.append(sp(8))

# ─── PAGE BREAK — PAEDIATRICS ────────────────────────────────────────────
story.append(PageBreak())
story.append(paper_header("PAPER I — PAEDIATRICS (24 Questions)", '#283593'))
story.append(sp(8))

story.append(topic("1. DEVELOPMENTAL MILESTONES ⭐⭐⭐ (Always in Exam)"))
tbl_dev = Table([
    ["Age", "Gross Motor", "Fine Motor / Vision", "Language", "Social"],
    ["2 months", "Head control prone", "Follows to midline", "Coos", "Social smile"],
    ["4 months", "Holds head steady", "Follows 180°, Hands open", "Laughs", "Recognises mother"],
    ["6 months", "Sits with support", "Transfers objects", "Babbles", "Stranger anxiety begins"],
    ["9 months", "Stands with support", "Pincer grasp (inferior)", "Mama/dada non-specific", "Waves bye-bye"],
    ["12 months", "Walks with support", "Pincer grasp (mature)", "1-2 words specific", "Comes when called"],
    ["18 months", "Walks independently", "Tower of 3 cubes", "10-20 words", "Feeds self"],
    ["2 years", "Runs", "Tower of 6 cubes", "2-word sentences", "Parallel play"],
    ["3 years", "Climbs stairs", "Copies circle", "3-word sentences", "Group play"],
], colWidths=[2.2*cm, 4*cm, 4.3*cm, 3.5*cm, 3*cm])
tbl_dev.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#283593')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#9fa8da')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e8eaf6')]),
    ('TOPPADDING', (0,0), (-1,-1), 4), ('BOTTOMPADDING', (0,0), (-1,-1), 4),
    ('LEFTPADDING', (0,0), (-1,-1), 3),
]))
story.append(tbl_dev)
story.append(sp(4))
story.append(h("Red flags: No smile by 3m, No babbling by 12m, No words by 18m, No 2-word sentences by 2y"))

story.append(sp(6))
story.append(topic("2. NATIONAL IMMUNIZATION SCHEDULE (NIS) ⭐⭐⭐"))
tbl_vacc = Table([
    ["Age", "Vaccine"],
    ["Birth", "BCG, OPV-0, Hepatitis B-1"],
    ["6 weeks", "OPV-1, IPV-1, DPT-1, HepB-2, Hib-1, PCV-1, Rotavirus-1"],
    ["10 weeks", "OPV-2, DPT-2, Hib-2, PCV-2, Rotavirus-2"],
    ["14 weeks", "OPV-3, IPV-2, DPT-3, Hib-3, PCV-3, Rotavirus-3"],
    ["9-12 months", "MR-1, JE-1 (endemic areas), Vitamin A-1"],
    ["15-18 months", "DPT booster-1, OPV-4, Hib booster, MR-2, JE-2"],
    ["5-6 years", "DPT booster-2"],
    ["10 & 16 years", "Td (Tetanus + diphtheria)"],
], colWidths=[5*cm, 12*cm])
tbl_vacc.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#283593')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#9fa8da')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e8eaf6')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
    ('LEFTPADDING', (0,0), (-1,-1), 8),
]))
story.append(tbl_vacc)
story.append(sp(4))
story.append(h("Live vaccines: BCG, OPV, MMR/MR, Rotavirus, Yellow fever, Varicella, JE (SA 14-14-2)"))
story.append(h("Cold chain: -15 to -25°C for OPV; +2 to +8°C for most others; VVM colour change = potency lost"))

story.append(sp(6))
story.append(topic("3. NEONATOLOGY ⭐⭐⭐"))
story.append(b("<b>Apgar Score</b>"))
tbl_apgar = Table([
    ["Sign", "0", "1", "2"],
    ["Appearance (colour)", "Blue/pale all", "Blue extremities", "Pink all"],
    ["Pulse (HR)", "Absent", "<100 bpm", "≥100 bpm"],
    ["Grimace (reflex)", "None", "Grimace", "Cry/cough"],
    ["Activity (tone)", "Limp", "Some flexion", "Active flexion"],
    ["Respiration", "Absent", "Weak/irregular", "Strong cry"],
], colWidths=[5*cm, 3.5*cm, 4.5*cm, 4*cm])
tbl_apgar.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#283593')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#9fa8da')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e8eaf6')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_apgar)
story.append(sp(4))
story.append(sb("Score 7-10 = Normal; 4-6 = Moderate depression; 0-3 = Severe; Assessed at 1 & 5 min"))
story.append(b("<b>Neonatal Jaundice</b>"))
story.append(sb("Physiological: Appears day 2-3, disappears by day 14 (term) / 21 days (preterm)"))
story.append(sb("Pathological: Appears <24h, or >15mg/dL in term baby, or conjugated >2mg/dL"))
story.append(sb("Causes <24h: Haemolysis (Rh/ABO incompatibility, G6PD), congenital infections"))
story.append(sb("Treatment: Phototherapy (450-490nm blue light); Exchange transfusion if level critical"))
story.append(h("Breastfeeding jaundice (early) vs Breast milk jaundice (late, due to β-glucuronidase)"))
story.append(b("<b>RDS (Respiratory Distress Syndrome)</b>"))
story.append(sb("Surfactant deficiency in premature babies; Lecithin:Sphingomyelin ratio <2 = immature lungs"))
story.append(sb("X-ray: Ground glass appearance + air bronchograms"))
story.append(sb("Treatment: Surfactant replacement therapy; CPAP; maternal antenatal steroids (dexamethasone) if <34 weeks"))
story.append(b("<b>Birth Injuries & Hypoxic Ischaemic Encephalopathy</b>"))
story.append(sb("HIE: Therapeutic hypothermia (33-34°C for 72h) if ≥36 weeks GA and within 6 hours"))
story.append(sb("Erb's palsy (C5-C6): Waiter's tip; Klumpke's (C8-T1): Claw hand"))
story.append(sp(6))

story.append(topic("4. PAEDIATRIC INFECTIONS ⭐⭐⭐"))
story.append(b("<b>Exanthematous Fevers</b>"))
tbl_exan = Table([
    ["Disease", "Rash", "Special Feature"],
    ["Measles", "Maculopapular; starts face → downward; day 4", "Koplik spots, 3 Cs (Cough, Coryza, Conjunctivitis)"],
    ["Rubella", "Pink maculopapular; head→feet in 3 days", "Forchheimer spots; congenital rubella (PDA, cataract, deafness)"],
    ["Chickenpox", "Vesicular; all stages simultaneously", "Centripetal (trunk); Tzanck smear"],
    ["Roseola (HHV-6)", "Pink maculopapular after fever subsides", "Exanthem subitum; 6-18 months"],
    ["Scarlet fever", "Sandpaper rash; strawberry tongue", "Group A Strep; Pastia lines in folds"],
    ["Kawasaki", "Polymorphous; strawberry tongue", "Coronary artery aneurysm; IVIG + Aspirin"],
], colWidths=[3.5*cm, 6*cm, 7.5*cm])
tbl_exan.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#283593')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#9fa8da')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e8eaf6')]),
    ('TOPPADDING', (0,0), (-1,-1), 4), ('BOTTOMPADDING', (0,0), (-1,-1), 4),
    ('LEFTPADDING', (0,0), (-1,-1), 4),
]))
story.append(tbl_exan)
story.append(sp(4))
story.append(topic("5. NUTRITION & MALNUTRITION ⭐⭐"))
story.append(b("<b>Protein-Energy Malnutrition</b>"))
tbl_pem = Table([
    ["Feature", "Marasmus", "Kwashiorkor"],
    ["Cause", "Calorie deficiency", "Protein deficiency"],
    ["Oedema", "Absent", "Present (pitting)"],
    ["Wasting", "Severe", "May be masked by oedema"],
    ["Skin/Hair", "Old man face, loose skin", "Flaky paint skin, flag sign in hair"],
    ["Liver", "Normal", "Fatty liver"],
    ["Albumin", "Normal or low", "Very low"],
], colWidths=[4*cm, 6.5*cm, 6.5*cm])
tbl_pem.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#283593')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#9fa8da')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e8eaf6')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_pem)
story.append(sp(4))
story.append(h("SAM criteria: MUAC <11.5cm OR weight-for-height Z-score <-3 OR oedema"))
story.append(h("F-75 stabilisation phase → F-100 rehabilitation phase (WHO protocol)"))
story.append(b("<b>Vitamin Deficiencies</b>"))
tbl_vit = Table([
    ["Vitamin", "Deficiency Disease", "Key Feature"],
    ["A", "Night blindness, Xerophthalmia", "Bitot spots; Keratomalacia"],
    ["B1 (Thiamine)", "Beriberi, Wernicke's encephalopathy", "Wet beriberi = cardiac; Dry = neuropathy"],
    ["B12", "Megaloblastic anaemia, Sub-acute combined degeneration", "Demyelination posterior + lateral columns"],
    ["C", "Scurvy", "Perifollicular haemorrhage, corkscrew hair, poor wound healing"],
    ["D", "Rickets (child), Osteomalacia (adult)", "Rachitic rosary, Harrison's sulcus, Looser's zones"],
    ["K", "Bleeding disorder", "VKDB in newborns; prolonged PT"],
], colWidths=[2.5*cm, 5.5*cm, 9*cm])
tbl_vit.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#283593')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#9fa8da')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e8eaf6')]),
    ('TOPPADDING', (0,0), (-1,-1), 4), ('BOTTOMPADDING', (0,0), (-1,-1), 4),
    ('LEFTPADDING', (0,0), (-1,-1), 3),
]))
story.append(tbl_vit)
story.append(PageBreak())

# ══════════════════════════════════════════════════════════════════
#  PAPER II — SURGERY
# ══════════════════════════════════════════════════════════════════
story.append(paper_header("PAPER II — SURGERY (40 Questions)", '#b71c1c'))
story.append(sp(8))

story.append(topic("1. ACUTE ABDOMEN & GI SURGERY ⭐⭐⭐"))
story.append(b("<b>Acute Appendicitis</b>"))
story.append(sb("Alvarado score ≥7 = Appendicitis; Rovsing's sign, Psoas sign, Obturator sign"))
story.append(sb("Investigation: USS (first line); CT abdomen (if USS inconclusive)"))
story.append(sb("Treatment: Laparoscopic appendicectomy; IV Amoxicillin+Metronidazole perioperatively"))
story.append(h("Retrocaecal appendix = Most common position (65%)"))
story.append(b("<b>Intestinal Obstruction</b>"))
story.append(sb("Small bowel: Distended central loops, valvulae conniventes cross full width"))
story.append(sb("Large bowel: Peripheral, haustra don't cross full width; Coffee bean sign = sigmoid volvulus"))
story.append(sb("Closed loop obstruction: Strangulation risk highest; emergency surgery"))
story.append(sb("Conservative in adhesion SBO: NG tube + IV fluids; surgery if fails 48-72h"))
story.append(b("<b>Peptic Ulcer Disease</b>"))
story.append(sb("Duodenal ulcer (DU) > Gastric ulcer (GU) in frequency"))
story.append(sb("DU: Relieved by food; GU: Worsened by food"))
story.append(sb("H. pylori eradication: Triple therapy = PPI + Clarithromycin + Amoxicillin x7-14d"))
story.append(sb("PUD complications: Bleeding (most common), Perforation (sudden board-like rigidity), Obstruction"))
story.append(b("<b>Hernia</b>"))
story.append(sb("Inguinal hernias: Indirect (through deep ring, lateral to inferior epigastric) vs Direct (medial, weak spot)"))
story.append(sb("Richter's hernia: Only part of bowel wall in sac; Maydl's hernia: W-shaped loop"))
story.append(sb("Femoral hernia: Below and lateral to pubic tubercle; more common in females"))
story.append(sb("Incarcerated = irreducible; Strangulated = compromised blood supply → emergency"))
story.append(sp(6))

story.append(topic("2. TRAUMA & SHOCK ⭐⭐⭐"))
story.append(b("<b>ATLS Classification of Haemorrhagic Shock</b>"))
tbl_shock = Table([
    ["Class", "Blood loss", "HR", "BP", "Urine output"],
    ["I", "<750 mL (<15%)", "<100", "Normal", ">30 mL/h"],
    ["II", "750-1500 mL (15-30%)", "100-120", "Normal/decreased", "20-30 mL/h"],
    ["III", "1500-2000 mL (30-40%)", "120-140", "Decreased", "5-15 mL/h"],
    ["IV", ">2000 mL (>40%)", ">140", "Very low", "<5 mL/h"],
], colWidths=[2.5*cm, 5*cm, 3*cm, 3.5*cm, 3*cm])
tbl_shock.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#b71c1c')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#ef9a9a')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#ffebee')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_shock)
story.append(sp(4))
story.append(b("<b>Head Injury (GCS)</b>"))
story.append(sb("GCS: E(4) + V(5) + M(6) = 15 total; Mild ≥13, Moderate 9-12, Severe ≤8"))
story.append(sb("Extradural haematoma: Lucid interval; biconvex/lenticular on CT; middle meningeal artery"))
story.append(sb("Subdural haematoma: Crescent-shaped; bridging veins; no lucid interval (acute)"))
story.append(sb("Subarachnoid haemorrhage: Thunderclap headache; CT shows blood in basal cisterns; LP = xanthochromia"))
story.append(h("Cushing's triad: Hypertension + Bradycardia + Irregular breathing = raised ICP"))
story.append(sp(6))

story.append(topic("3. UROLOGY ⭐⭐"))
story.append(b("<b>BPH</b>"))
story.append(sb("IPSS score; Rx: alpha-blockers (Tamsulosin) + 5-alpha reductase inhibitors (Finasteride)"))
story.append(sb("Surgery: TURP (gold standard); HoLEP for large prostates"))
story.append(b("<b>Renal/Ureteric Calculi</b>"))
story.append(sb("Most common: Calcium oxalate (80%); Struvite = staghorn; Uric acid = radiolucent"))
story.append(sb("IVU/CT KUB; Uric acid stones = Alkalinise urine (potassium citrate)"))
story.append(sb("<4mm: Pass spontaneously; 4-10mm: Alpha-blockers (MET) + analgesia; >10mm: ESWL or PCNL"))
story.append(b("<b>Carcinoma Prostate</b>"))
story.append(sb("PSA elevated; DRE: hard, nodular; biopsy: Gleason score (2-10)"))
story.append(sb("Localised: Radical prostatectomy or radiotherapy; Metastatic: Androgen deprivation therapy (ADT)"))
story.append(sp(6))

story.append(topic("4. SURGICAL ONCOLOGY ⭐⭐⭐"))
story.append(b("<b>Breast Cancer</b>"))
story.append(sb("Most common cancer in women; Triple assessment: Clinical + Imaging + FNAC"))
story.append(sb("BRCA1/2 mutations → hereditary breast/ovarian cancer"))
story.append(sb("Invasive ductal carcinoma = most common type (70%)"))
story.append(sb("ER/PR positive: Tamoxifen (premenopausal); Aromatase inhibitors (postmenopausal)"))
story.append(sb("HER2 positive: Trastuzumab (Herceptin)"))
story.append(sb("Paget's disease of nipple: Eczematoid change of nipple = underlying DCIS/invasive carcinoma"))
story.append(h("Sentinel lymph node biopsy: First lymph node draining tumour → avoid unnecessary axillary clearance"))
story.append(b("<b>Colorectal Cancer</b>"))
story.append(sb("FAP: APC gene mutation; >100 polyps; 100% lifetime risk colon cancer"))
story.append(sb("Lynch syndrome (HNPCC): MLH1/MSH2 mismatch repair genes; right-sided tumours"))
story.append(sb("CEA: Monitoring recurrence, not diagnosis"))
story.append(sb("Dukes staging: A=mucosa/submucosa, B=through wall, C=lymph nodes, D=distant mets"))
story.append(sp(6))

story.append(topic("5. WOUND HEALING & SURGICAL INFECTIONS ⭐⭐"))
story.append(b("<b>Wound Healing</b>"))
story.append(sb("Primary intention: Clean surgical wound; Secondary: Left open to granulate; Tertiary (delayed primary): Delayed closure"))
story.append(sb("Phases: Haemostasis (0-24h) → Inflammation (1-4d) → Proliferation (4d-3wk) → Remodelling (3wk-2yr)"))
story.append(sb("Keloid: Extends beyond wound margins; does not regress; Hypertrophic scar: Within margins; regresses"))
story.append(b("<b>Surgical Site Infections</b>"))
story.append(sb("Superficial (within 30 days), Deep, Organ space"))
story.append(sb("Most common organism: Staphylococcus aureus; Gram-negative in bowel surgery"))
story.append(b("<b>Gas Gangrene & Tetanus</b>"))
story.append(sb("Gas gangrene: Clostridium perfringens; crepitus + gas in tissues + foul smell → debridement + penicillin"))
story.append(sb("Tetanus: C. tetani toxin (tetanospasmin); lock jaw, risus sardonicus, opisthotonus"))
story.append(sb("Tetanus prophylaxis: Clean wound → TT if not immunised in 5y; Dirty → TIG + TT"))
story.append(PageBreak())

# ══════════════════════════════════════════════════════════════════
#  PAPER II — GYNAECOLOGY & OBSTETRICS
# ══════════════════════════════════════════════════════════════════
story.append(paper_header("PAPER II — GYNAECOLOGY & OBSTETRICS (40 Questions)", '#880e4f'))
story.append(sp(8))

story.append(topic("1. OBSTETRICS ⭐⭐⭐"))
story.append(b("<b>Antenatal Care</b>"))
story.append(sb("Booking visit: <12 weeks; Blood group, Hb, VDRL, HIV, urine culture, rubella serology"))
story.append(sb("Gestational diabetes: OGTT at 24-28 weeks; diagnosis: FBS ≥92, 1h ≥180, 2h ≥153 (IADPSG)"))
story.append(sb("Iron supplementation: 100mg elemental iron/day from 14 weeks"))
story.append(b("<b>Antepartum Haemorrhage (APH)</b>"))
tbl_aph = Table([
    ["Feature", "Placenta Praevia", "Abruptio Placentae"],
    ["Pain", "Painless", "Painful (constant)"],
    ["Bleeding", "Bright red, revealed", "Dark red, concealed/revealed"],
    ["Uterus", "Soft", "Woody hard, tender"],
    ["Fetal heart", "Normal", "Distressed/absent"],
    ["Cause", "Low-lying placenta", "Premature separation"],
    ["Diagnosis", "USS (TVS)", "Clinical; USS may miss"],
], colWidths=[4*cm, 6.5*cm, 6.5*cm])
tbl_aph.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#880e4f')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#f48fb1')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#fce4ec')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_aph)
story.append(sp(4))
story.append(h("DO NOT do PV exam in placenta praevia (risk of catastrophic haemorrhage)"))
story.append(b("<b>Pre-eclampsia & Eclampsia</b>"))
story.append(sb("Pre-eclampsia: BP ≥140/90 + proteinuria (≥300mg/24h) after 20 weeks"))
story.append(sb("Severe: BP ≥160/110 + end-organ features (oliguria, headache, visual, RUQ pain, thrombocytopenia)"))
story.append(sb("HELLP syndrome: Haemolysis, Elevated Liver enzymes, Low Platelets"))
story.append(sb("Eclampsia: Convulsion in pre-eclamptic patient → MgSO4 (loading 4g IV over 20min + 1g/h maintenance)"))
story.append(sb("MgSO4 toxicity: Loss of patellar reflex (first sign); respiratory depression; antidote = Calcium gluconate"))
story.append(sb("Antihypertensives in pregnancy: Labetalol IV (acute), Hydralazine IV, Nifedipine oral"))
story.append(h("Definitive treatment of pre-eclampsia/eclampsia = Delivery"))
story.append(b("<b>Postpartum Haemorrhage (PPH)</b>"))
story.append(sb("Primary PPH: Blood loss ≥500mL within 24h of delivery (≥1000mL after CS)"))
story.append(sb("4 Ts: Tone (atony, 70%), Tissue (retained products), Trauma (lacerations), Thrombin (coagulopathy)"))
story.append(sb("Management: Uterine massage → Oxytocin → Ergometrine → Carboprost → B-Lynch suture → hysterectomy"))
story.append(sb("Active management of 3rd stage: Oxytocin 10 IU IM within 1 min of delivery = gold standard"))
story.append(sp(6))

story.append(topic("2. LABOUR & DELIVERY ⭐⭐"))
story.append(b("<b>Stages of Labour</b>"))
story.append(sb("Stage 1: Onset → full dilatation (10cm); Latent phase (0-3cm slow) + Active phase (3-10cm)"))
story.append(sb("Active phase: Normal dilation ≥1cm/h (primigravida), ≥1.5cm/h (multigravida)"))
story.append(sb("Stage 2: Full dilatation → delivery of baby; Stage 3: Delivery of placenta (up to 30 min)"))
story.append(b("<b>Foetal Heart Rate Monitoring</b>"))
story.append(sb("Normal FHR: 110-160 bpm; Early decelerations = head compression (benign)"))
story.append(sb("Late decelerations = uteroplacental insufficiency (ominous); Variable = cord compression"))
story.append(sb("CTG assessment: NICE classification = Reassuring / Non-reassuring / Abnormal"))
story.append(b("<b>Obstructed Labour</b>"))
story.append(sb("Bandl's ring: Pathological retraction ring between upper + lower uterine segments = impending rupture"))
story.append(sb("Uterine rupture: Sudden scar pain, cessation of contractions, foetal parts palpable, haematuria"))
story.append(sp(6))

story.append(topic("3. GYNAECOLOGY ⭐⭐⭐"))
story.append(b("<b>Menstrual Disorders</b>"))
story.append(sb("Normal menstrual cycle: 28 days (21-35 days); duration 3-7 days; blood loss 30-80mL"))
story.append(sb("Primary amenorrhoea: No menses by 16y (with secondary sexual characteristics) or 14y (without)"))
story.append(sb("PCOS (Stein-Leventhal): Oligomenorrhoea, hyperandrogenism, polycystic ovaries; Rotterdam criteria (2 of 3)"))
story.append(sb("PCOS management: Lifestyle, OCP (for menstrual regulation), Metformin (insulin resistance), Clomiphene (infertility)"))
story.append(b("<b>Fibroid (Leiomyoma)</b>"))
story.append(sb("Most common gynaecological tumour; oestrogen-dependent; regress after menopause"))
story.append(sb("Types: Submucous (heavy bleeding), Intramural (most common), Subserous (pressure symptoms)"))
story.append(sb("Rx: Tranexamic acid, GnRH agonists (shrink pre-op); Myomectomy; Hysterectomy"))
story.append(b("<b>Endometriosis</b>"))
story.append(sb("Ectopic endometrial tissue outside uterus; Cyclical pain, dyspareunia, infertility"))
story.append(sb("Chocolate cyst (endometrioma) in ovary; powder burn lesions on laparoscopy"))
story.append(sb("CA-125 elevated; Definitive diagnosis: Laparoscopy + biopsy"))
story.append(sb("Treatment: NSAIDs, OCP, GnRH agonists, Danazol; Surgery for severe disease"))
story.append(b("<b>Cervical Cancer</b>"))
story.append(sb("HPV 16,18 = High risk serotypes; HPV 6,11 = Condylomata acuminata (low risk)"))
story.append(sb("Pap smear (Bethesda system): ASCUS → colposcopy; CIN 1 = observe; CIN 2-3 = LLETZ"))
story.append(sb("Staging: FIGO clinical staging; Squamous cell carcinoma most common (80%)"))
story.append(sb("Treatment: Stage IA = conisation/hysterectomy; IB-IIA = Wertheim's hysterectomy or RT; IIB+ = Chemoradiation"))
story.append(b("<b>Ovarian Cancer</b>"))
story.append(sb("Serous cystadenocarcinoma = most common malignant ovarian tumour"))
story.append(sb("Dermoid cyst (Mature teratoma) = most common benign ovarian tumour in young women"))
story.append(sb("Psammoma bodies in papillary serous carcinoma"))
story.append(sb("Treatment: Cytoreductive surgery + Platinum-based chemotherapy (Carboplatin + Paclitaxel)"))
story.append(h("Krukenberg tumour: Metastatic to ovary from GI tract (stomach most common); bilateral, signet ring cells"))
story.append(PageBreak())

# ══════════════════════════════════════════════════════════════════
#  PAPER II — PSM / COMMUNITY MEDICINE
# ══════════════════════════════════════════════════════════════════
story.append(paper_header("PAPER II — PREVENTIVE & SOCIAL MEDICINE (40 Questions)", '#1b5e20'))
story.append(sp(8))

story.append(topic("1. EPIDEMIOLOGY ⭐⭐⭐ (Very High Yield)"))
story.append(b("<b>Measures of Disease Frequency</b>"))
story.append(sb("Incidence rate = New cases / Population at risk x Time"))
story.append(sb("Prevalence = Existing cases / Total population (point prevalence = at a moment)"))
story.append(sb("Prevalence = Incidence x Duration; High duration raises prevalence"))
story.append(sb("Attack rate = Cases / Population at risk at start of outbreak x 100"))
story.append(b("<b>Study Designs (Most Tested)</b>"))
tbl_study = Table([
    ["Design", "Direction", "Measure", "Bias/Feature"],
    ["Case-control", "Retrospective", "Odds Ratio (OR)", "Recall bias; good for rare diseases"],
    ["Cohort", "Prospective/Retro", "Relative Risk (RR)", "Attrition bias; best for incidence"],
    ["RCT", "Prospective", "ARR, NNT, RRR", "Gold standard for causation"],
    ["Cross-sectional", "Snapshot", "Prevalence", "Cannot establish causation"],
    ["Ecological", "Population level", "Correlation", "Ecological fallacy"],
], colWidths=[3.5*cm, 3.5*cm, 4*cm, 6*cm])
tbl_study.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1b5e20')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#81c784')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e8f5e9')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_study)
story.append(sp(4))
story.append(b("<b>Screening Tests (Always in Exam)</b>"))
tbl_screen = Table([
    ["Term", "Formula", "Meaning"],
    ["Sensitivity", "TP/(TP+FN)", "Detects true positives; rules OUT disease (SnNOut)"],
    ["Specificity", "TN/(TN+FP)", "Detects true negatives; rules IN disease (SpPin)"],
    ["PPV", "TP/(TP+FP)", "Probability of disease if test positive; depends on prevalence"],
    ["NPV", "TN/(TN+FN)", "Probability of no disease if test negative"],
    ["Accuracy", "(TP+TN)/Total", "Overall correctness"],
], colWidths=[3.5*cm, 4*cm, 9.5*cm])
tbl_screen.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1b5e20')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#81c784')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e8f5e9')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_screen)
story.append(sp(4))
story.append(h("High sensitivity test: Use for screening (don't miss disease); High specificity: Use for confirmation"))

story.append(sp(6))
story.append(topic("2. NATIONAL HEALTH PROGRAMMES ⭐⭐⭐ (PYQ Goldmine)"))
story.append(b("<b>Reproductive & Child Health Programs</b>"))
story.append(sb("RMNCH+A: Reproductive, Maternal, Newborn, Child, and Adolescent Health"))
story.append(sb("JSSK (Janani Shishu Suraksha Karyakram): Free delivery, C-section, drugs, diagnostics at govt hospitals"))
story.append(sb("JSY (Janani Suraksha Yojana): Cash incentive for institutional delivery"))
story.append(sb("RBSK (Rashtriya Bal Swasthya Karyakram): Screening 0-18 years; 4Ds: Defects, Deficiencies, Diseases, Developmental delays"))
story.append(sb("PMMVY: Pradhan Mantri Matru Vandana Yojana; Rs 5000 maternity benefit for 1st child"))
story.append(b("<b>Disease Control Programs</b>"))
story.append(sb("RNTCP → National TB Elimination Programme (NTEP): Target to eliminate TB by 2025 (1/million)"))
story.append(sb("NVBDCP: National Vector Borne Disease Control Programme (Malaria, Dengue, Filaria, Kala-azar, JE, Chikungunya)"))
story.append(sb("NACP: National AIDS Control Programme; NACO administers; 4th phase ongoing"))
story.append(sb("NHM: National Health Mission (NHM = NRHM + NUHM); launched 2005"))
story.append(sb("NPCDCS: NCD programme; screening for DM, HTN, cancers at PHC level"))
story.append(b("<b>Important Targets & Indicators</b>"))
story.append(sb("MMR (Maternal Mortality Rate): India 97/lakh live births (SRS 2018-20); SDG target <70"))
story.append(sb("IMR (Infant Mortality Rate): 28/1000 live births (SRS 2020); SDG target ≤12 by 2030"))
story.append(sb("U5MR: 32/1000 live births; NMR (Neonatal): 20/1000 live births"))
story.append(sb("Total Fertility Rate (TFR): 2.0 (SRS 2020); Replacement level = 2.1"))
story.append(sp(6))

story.append(topic("3. NUTRITION & PUBLIC HEALTH ⭐⭐"))
story.append(b("<b>Recommended Dietary Allowances (RDA) — ICMR 2020</b>"))
story.append(sb("Adult male: 2110 kcal; Adult female: 1660 kcal; Pregnant: +350 kcal; Lactating: +600 kcal"))
story.append(sb("Protein: 0.83g/kg/day; Calcium: 1000mg/day; Iron: 15mg/day (women), 17mg/day (men)"))
story.append(b("<b>Mid-Day Meal Scheme / ICDS</b>"))
story.append(sb("ICDS (Integrated Child Development Services): 6 services for 0-6 years at Anganwadi"))
story.append(sb("Services: Supplementary nutrition, Immunisation, Health check-up, Referral, Pre-school education, Health & nutrition education"))
story.append(sb("Mid-Day Meal scheme (PM POSHAN): Primary school children; improves enrolment & retention"))
story.append(sp(6))

story.append(topic("4. ENVIRONMENT & OCCUPATIONAL HEALTH ⭐⭐"))
story.append(b("<b>Water Quality Standards</b>"))
story.append(sb("Coliform bacteria: E. coli = indicator of faecal contamination; MPN (Most Probable Number) test"))
story.append(sb("WHO safe drinking water: E. coli = 0 per 100mL; Turbidity <1 NTU; pH 6.5-8.5"))
story.append(sb("Chlorination: Residual chlorine 0.5mg/L after 30 min contact; Break-point chlorination"))
story.append(b("<b>Occupational Diseases</b>"))
tbl_occ = Table([
    ["Occupation", "Hazard", "Disease"],
    ["Mining/Quarrying", "Silica dust", "Silicosis (most fibrogenic)"],
    ["Asbestos workers", "Asbestos fibres", "Asbestosis, Mesothelioma (pleural), lung cancer"],
    ["Cotton/Textile", "Cotton dust", "Byssinosis (Monday morning fever)"],
    ["Coal miners", "Coal dust", "Coal workers' pneumoconiosis (CWP)"],
    ["Lead industry", "Lead (Pb)", "Lead line on gums, anaemia, neuropathy, colic"],
    ["Farmers/Tannery", "Anthrax", "Woolsorter's disease"],
], colWidths=[4*cm, 4.5*cm, 8.5*cm])
tbl_occ.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1b5e20')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#81c784')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e8f5e9')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_occ)
story.append(sp(6))

story.append(topic("5. HEALTH ADMINISTRATION ⭐⭐"))
story.append(b("<b>Primary Health Care (Alma Ata Declaration, 1978)</b>"))
story.append(sb("8 elements: ESSCAMEN = Education, Safe water/sanitation, Supplementary nutrition, Control of endemic diseases, Adequate housing, Maternal & child health, Essential drugs, Nutrition"))
story.append(sb("Health for All by 2000 AD (Alma Ata); Universal Health Coverage (SDG 3.8)"))
story.append(b("<b>Health Infrastructure (Rural India)</b>"))
tbl_infra = Table([
    ["Level", "Population Covered", "Facility"],
    ["Sub-Centre", "3000-5000 (plains); 1000-3000 (hilly)", "ANM + Male health worker; first contact"],
    ["PHC (Primary Health Centre)", "20,000-30,000 (plains)", "1 Medical Officer; 6 beds; referral unit"],
    ["CHC (Community Health Centre)", "80,000-1,20,000", "30 beds; 4 specialists (Physician, Surgeon, Ob-Gyn, Paediatrician)"],
    ["Sub-District/Taluk Hospital", "5-6 lakh", "60-100 beds"],
    ["District Hospital", "10-20 lakh", "100-500+ beds"],
], colWidths=[4*cm, 5.5*cm, 7.5*cm])
tbl_infra.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1b5e20')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#81c784')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e8f5e9')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_infra)
story.append(sp(4))
story.append(h("ASHA: Accredited Social Health Activist; 1 per 1000 population; first contact in community"))
story.append(h("Anganwadi worker: ICDS; serves 400-800 population; reports to CDPO"))

story.append(sp(6))
story.append(topic("6. COMMUNICABLE DISEASE CONTROL ⭐⭐⭐"))
story.append(b("<b>Modes of Transmission</b>"))
story.append(sb("Direct: Droplet (<1m), Contact (sexual, skin), Vertical (mother to child)"))
story.append(sb("Indirect: Airborne (>1m, droplet nuclei), Vehicle (food/water/fomites), Vector (biological/mechanical)"))
story.append(b("<b>Herd Immunity Thresholds</b>"))
tbl_herd = Table([
    ["Disease", "R0", "Herd Immunity Threshold"],
    ["Measles", "12-18", "92-95%"],
    ["Polio", "5-7", "80-86%"],
    ["COVID-19 (original)", "2-3", "50-67%"],
    ["Smallpox", "5-7", "80-85%"],
], colWidths=[5*cm, 4*cm, 8*cm])
tbl_herd.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1b5e20')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('FONTSIZE', (0,0), (-1,-1), 8.5),
    ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#81c784')),
    ('ROWBACKGROUNDS', (1,0), (-1,-1), [colors.white, colors.HexColor('#e8f5e9')]),
    ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
]))
story.append(tbl_herd)
story.append(sp(4))
story.append(b("<b>India-Specific Disease Status</b>"))
story.append(sb("Polio: India declared polio-free in 2014 (WHO); last case Jan 2011 (Howrah, WB)"))
story.append(sb("Smallpox: Eradicated globally 1980; India 1977 (last case in Bihar)"))
story.append(sb("Guinea worm (Dracunculiasis): Eradicated in India; near-global eradication"))
story.append(sb("Kala-azar: Elimination target <1/10,000 population at sub-district level"))
story.append(sb("Filariasis: Elimination target 2030; MDA (DEC + Albendazole) programme"))

# FINAL PAGE — LAST MINUTE REVISION
story.append(PageBreak())
story.append(paper_header("RAPID FIRE — LAST MINUTE REVISION", '#37474f'))
story.append(sp(8))

rapid_fire = [
    ("CARDIOLOGY", [
        "Commonest cause of TR = MR/MS (functional TR)", "MI enzyme sequence: Troponin (earliest, gold std) → CK-MB → LDH",
        "First drug to give in acute pulmonary oedema: Furosemide IV + Morphine + O2",
        "Cardiac tamponade: Beck's triad = Hypotension + Raised JVP + Muffled heart sounds",
        "Pulsus paradoxus >10mmHg = tamponade, severe asthma, constrictive pericarditis",
    ]),
    ("NEUROLOGY", [
        "CN III palsy (down and out + ptosis + dilated pupil) = PCA aneurysm until proven otherwise",
        "Horner's syndrome: Ptosis + Miosis + Anhidrosis",
        "Wernicke's encephalopathy: Confusion + Ataxia + Ophthalmoplegia; Rx: IV Thiamine BEFORE glucose",
        "Normal pressure hydrocephalus (Hakim's triad): Wet, Wobbly, Wacky (incontinence, gait, dementia)",
    ]),
    ("ENDOCRINOLOGY", [
        "MEN 1 (3 Ps): Pituitary + Parathyroid + Pancreas", "MEN 2A: Phaeochromocytoma + Parathyroid + Medullary thyroid Ca",
        "MEN 2B: Phaeochromocytoma + Medullary thyroid Ca + Marfanoid + Mucosal neuromas",
        "Prolactinoma: Commonest pituitary tumour; Rx: Cabergoline/Bromocriptine",
    ]),
    ("SURGERY ONE-LINERS", [
        "Gold standard for Dx of PE: CTPA (CT pulmonary angiography)",
        "Virchow's triad (DVT): Stasis + Hypercoagulability + Endothelial injury",
        "Ranson's criteria (Pancreatitis): ≥3 = severe; Atlanta criteria for severity",
        "Courvoisier's law: Palpable non-tender GB + jaundice = Ca head of pancreas (not gallstones)",
        "Murphy's sign (acute cholecystitis): Inspiratory arrest on palpation RUQ",
    ]),
    ("OBSTETRICS ONE-LINERS", [
        "Biophysical profile (BPP): NST + 4 USS parameters (tone, movement, breathing, liquor); max 10",
        "Bishop score ≥6 = favourable cervix for induction",
        "Cord prolapse: Knee-chest position + fill bladder + emergency CS",
        "Shoulder dystocia: McRoberts manoeuvre (hyperflexion hips) + suprapubic pressure",
        "Gravidity = total pregnancies; Parity = deliveries >20 weeks",
    ]),
    ("PSM ONE-LINERS", [
        "Diphtheria toxoid in DPT = Loffler's toxin; Tetanus toxoid = tetanospasmin",
        "Oral cholera vaccine: Shanchol (2 doses 2 weeks apart); Killed whole cell + B subunit",
        "Pellagra: Niacin deficiency; 4 Ds: Dermatitis, Diarrhoea, Dementia, Death",
        "Yaws (Treponema pallidum pertenue): Notifiable; penicillin treatment",
        "Notifiable diseases in India: Cholera, Plague, Yellow fever, SARS, COVID-19, Dengue, Malaria",
    ]),
]

for section, points in rapid_fire:
    tbl_rf = Table([[Paragraph(f"  {section}", ParagraphStyle('rfh', fontSize=10, fontName='Helvetica-Bold',
                    textColor=colors.white))]], colWidths=[17*cm])
    tbl_rf.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), colors.HexColor('#37474f')),
        ('TOPPADDING', (0,0), (-1,-1), 5), ('BOTTOMPADDING', (0,0), (-1,-1), 5),
    ]))
    story.append(tbl_rf)
    for pt in points:
        story.append(b(pt))
    story.append(sp(4))

story.append(sp(8))
footer_tbl = Table([[Paragraph("Best of Luck for UPSC CMS 2026 on 2nd August!", 
                    ParagraphStyle('ft', fontSize=13, fontName='Helvetica-Bold', textColor=colors.white, alignment=TA_CENTER))]], 
                    colWidths=[17*cm])
footer_tbl.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,-1), colors.HexColor('#1a237e')),
    ('TOPPADDING', (0,0), (-1,-1), 12), ('BOTTOMPADDING', (0,0), (-1,-1), 12),
]))
story.append(footer_tbl)

doc.build(story)
print(f"PDF generated: {OUTPUT}")

cd /home/daytona/workspace/upsc-cms-notes && python generate_notes.py

ls -lh /home/daytona/workspace/upsc-cms-notes/UPSC_CMS_HighYield_Notes_2026.pdf

UPSC CMS 2020 2021 2022 2023 2024 previous year question papers topic wise analysis

UPSC CMS most repeated topics chapter wise frequency analysis all subjects

~/upsc-cms-notes/pdf_helpers.py

from reportlab.lib.pagesizes import A4
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm
from reportlab.lib import colors
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle, PageBreak, HRFlowable
from reportlab.lib.enums import TA_CENTER, TA_LEFT

# ── Shared colour palette ──────────────────────────────────────────
SUBJECT_COLORS = {
    "medicine":    {"dark": "#1a237e", "mid": "#1565c0", "light": "#e3f2fd", "accent": "#b71c1c"},
    "paediatrics": {"dark": "#283593", "mid": "#3949ab", "light": "#e8eaf6", "accent": "#e65100"},
    "surgery":     {"dark": "#b71c1c", "mid": "#c62828", "light": "#ffebee", "accent": "#1b5e20"},
    "obsgyn":      {"dark": "#880e4f", "mid": "#ad1457", "light": "#fce4ec", "accent": "#4a148c"},
    "psm":         {"dark": "#1b5e20", "mid": "#2e7d32", "light": "#e8f5e9", "accent": "#0d47a1"},
}

def make_styles(sc):
    dark, mid, light, accent = sc["dark"], sc["mid"], sc["light"], sc["accent"]
    return {
        "cover_title": ParagraphStyle('ct', fontSize=26, textColor=colors.HexColor(dark),
                        alignment=TA_CENTER, spaceAfter=10, fontName='Helvetica-Bold'),
        "cover_sub":   ParagraphStyle('cs', fontSize=13, textColor=colors.HexColor(mid),
                        alignment=TA_CENTER, spaceAfter=6, fontName='Helvetica'),
        "cover_date":  ParagraphStyle('cd', fontSize=13, textColor=colors.HexColor(accent),
                        alignment=TA_CENTER, spaceAfter=6, fontName='Helvetica-Bold'),
        "chapter":     ParagraphStyle('ch', fontSize=13, textColor=colors.white,
                        alignment=TA_CENTER, spaceAfter=4, spaceBefore=4, fontName='Helvetica-Bold'),
        "topic":       ParagraphStyle('tp', fontSize=11, textColor=colors.HexColor(dark),
                        spaceAfter=4, spaceBefore=8, fontName='Helvetica-Bold'),
        "bullet":      ParagraphStyle('bl', fontSize=9.5, leftIndent=14, spaceAfter=2,
                        fontName='Helvetica', leading=14),
        "subbullet":   ParagraphStyle('sb', fontSize=9, leftIndent=28, spaceAfter=2,
                        fontName='Helvetica', textColor=colors.HexColor('#333333'), leading=13),
        "highlight":   ParagraphStyle('hl', fontSize=9.5, leftIndent=14, spaceAfter=2,
                        fontName='Helvetica-Bold', textColor=colors.HexColor(accent), leading=14),
        "mnemonic":    ParagraphStyle('mn', fontSize=9.5, leftIndent=14, spaceAfter=3,
                        fontName='Helvetica-Bold', textColor=colors.HexColor('#6a1b9a'), leading=14),
        "pyq":         ParagraphStyle('pq', fontSize=9, leftIndent=14, spaceAfter=2,
                        fontName='Helvetica-Oblique', textColor=colors.HexColor('#004d40'), leading=13),
        "examq":       ParagraphStyle('eq', fontSize=9.5, leftIndent=14, spaceAfter=3,
                        fontName='Helvetica-Bold', textColor=colors.HexColor(mid), leading=14),
        "ans":         ParagraphStyle('an', fontSize=9, leftIndent=28, spaceAfter=2,
                        fontName='Helvetica', textColor=colors.HexColor('#1b5e20'), leading=13),
        "dark": dark, "mid": mid, "light": light, "accent": accent,
    }

def make_doc(path):
    return SimpleDocTemplate(path, pagesize=A4,
        rightMargin=1.8*cm, leftMargin=1.8*cm, topMargin=2*cm, bottomMargin=2*cm)

def chapter_header(title, dark_hex):
    t = Table([[Paragraph(title, ParagraphStyle('ch2', fontSize=13, textColor=colors.white,
                alignment=TA_CENTER, fontName='Helvetica-Bold'))]], colWidths=[17*cm])
    t.setStyle(TableStyle([
        ('BACKGROUND', (0,0),(-1,-1), colors.HexColor(dark_hex)),
        ('TOPPADDING',(0,0),(-1,-1),8), ('BOTTOMPADDING',(0,0),(-1,-1),8),
    ]))
    return t

def section_bar(title, mid_hex, light_hex):
    t = Table([[Paragraph(f"  {title}", ParagraphStyle('sb2', fontSize=11,
                textColor=colors.HexColor(mid_hex), fontName='Helvetica-Bold'))]], colWidths=[17*cm])
    t.setStyle(TableStyle([
        ('BACKGROUND',(0,0),(-1,-1), colors.HexColor(light_hex)),
        ('LINEBELOW',(0,0),(-1,-1),2, colors.HexColor(mid_hex)),
        ('TOPPADDING',(0,0),(-1,-1),5), ('BOTTOMPADDING',(0,0),(-1,-1),5),
    ]))
    return t

def pyq_box(questions, mid_hex, light_hex):
    """Renders a PYQ Asked box."""
    rows = [[Paragraph("📋 PYQ ASKED (2020-2024)", ParagraphStyle('pqh', fontSize=9,
              textColor=colors.white, fontName='Helvetica-Bold'))]]
    for q in questions:
        rows.append([Paragraph(f"  ✦ {q}", ParagraphStyle('pqi', fontSize=8.5,
                     textColor=colors.HexColor('#212121'), fontName='Helvetica-Oblique', leading=13))])
    t = Table(rows, colWidths=[17*cm])
    t.setStyle(TableStyle([
        ('BACKGROUND',(0,0),(0,0), colors.HexColor(mid_hex)),
        ('BACKGROUND',(0,1),(-1,-1), colors.HexColor(light_hex)),
        ('TOPPADDING',(0,0),(-1,-1),4), ('BOTTOMPADDING',(0,0),(-1,-1),4),
        ('LEFTPADDING',(0,0),(-1,-1),8),
        ('BOX',(0,0),(-1,-1),1, colors.HexColor(mid_hex)),
    ]))
    return t

def examiner_box(questions_answers, mid_hex):
    """Renders Examiner Likely Questions box."""
    rows = [[Paragraph("🎯 EXAMINER-STYLE LIKELY QUESTIONS", ParagraphStyle('eqh', fontSize=9,
              textColor=colors.white, fontName='Helvetica-Bold'))]]
    for q, a in questions_answers:
        rows.append([Paragraph(f"  Q: {q}", ParagraphStyle('eqi', fontSize=8.5,
                     textColor=colors.HexColor('#1a237e'), fontName='Helvetica-Bold', leading=13))])
        rows.append([Paragraph(f"  Ans: {a}", ParagraphStyle('eqa', fontSize=8.5,
                     textColor=colors.HexColor('#1b5e20'), fontName='Helvetica', leading=13))])
    t = Table(rows, colWidths=[17*cm])
    t.setStyle(TableStyle([
        ('BACKGROUND',(0,0),(0,0), colors.HexColor('#37474f')),
        ('BACKGROUND',(0,1),(-1,-1), colors.HexColor('#f9fbe7')),
        ('TOPPADDING',(0,0),(-1,-1),4), ('BOTTOMPADDING',(0,0),(-1,-1),4),
        ('LEFTPADDING',(0,0),(-1,-1),8),
        ('BOX',(0,0),(-1,-1),1, colors.HexColor('#78909c')),
    ]))
    return t

def std_table(header_row, data_rows, col_widths, dark_hex, light_hex):
    all_rows = [header_row] + data_rows
    t = Table(all_rows, colWidths=col_widths)
    t.setStyle(TableStyle([
        ('BACKGROUND',(0,0),(-1,0), colors.HexColor(dark_hex)),
        ('TEXTCOLOR',(0,0),(-1,0), colors.white),
        ('FONTNAME',(0,0),(-1,0),'Helvetica-Bold'),
        ('FONTSIZE',(0,0),(-1,-1),8.5),
        ('GRID',(0,0),(-1,-1),0.5, colors.HexColor(light_hex)),
        ('ROWBACKGROUNDS',(1,0),(-1,-1),[colors.white, colors.HexColor(light_hex)]),
        ('TOPPADDING',(0,0),(-1,-1),5),('BOTTOMPADDING',(0,0),(-1,-1),5),
        ('LEFTPADDING',(0,0),(-1,-1),4),
    ]))
    return t

def b(text, st): return Paragraph(f"• {text}", st["bullet"])
def sb(text, st): return Paragraph(f"  ◦ {text}", st["subbullet"])
def h(text, st): return Paragraph(f"★ {text}", st["highlight"])
def mn(text, st): return Paragraph(f"🧠 {text}", st["mnemonic"])
def sp(n=4): return Spacer(1, n)
def hr(): return HRFlowable(width="100%", thickness=0.5, color=colors.HexColor('#bdbdbd'))
def topic(text, st): return Paragraph(text, st["topic"])

~/upsc-cms-notes/gen_medicine.py

import sys
sys.path.insert(0, '/home/daytona/workspace/upsc-cms-notes')
from pdf_helpers import *
from reportlab.platypus import PageBreak

OUT = "/home/daytona/workspace/upsc-cms-notes/01_General_Medicine.pdf"
doc = make_doc(OUT)
sc = SUBJECT_COLORS["medicine"]
st = make_styles(sc)
story = []

# COVER
story += [
    Spacer(1,2.5*cm),
    Paragraph("UPSC CMS 2026", st["cover_title"]),
    Paragraph("SUBJECT 1: GENERAL MEDICINE", ParagraphStyle('x',fontSize=20,
              textColor=colors.HexColor(sc["mid"]),alignment=TA_CENTER,spaceAfter=8,fontName='Helvetica-Bold')),
    Paragraph("96 Questions | PYQ 2020-2024 Mapped | Examiner-Style Questions", st["cover_sub"]),
    Spacer(1,0.3*cm),
    HRFlowable(width="80%",thickness=2,color=colors.HexColor(sc["dark"]),hAlign='CENTER'),
    Spacer(1,0.3*cm),
    Paragraph("EXAM: 2nd AUGUST 2026", st["cover_date"]),
    Spacer(1,1*cm),
]
freq_data = [
    ["Chapter", "Avg Qs/Year (2020-24)", "PYQ Frequency"],
    ["Cardiology", "14-16", "⭐⭐⭐⭐⭐ Very High"],
    ["Infectious Diseases", "12-14", "⭐⭐⭐⭐⭐ Very High"],
    ["Neurology", "10-12", "⭐⭐⭐⭐ High"],
    ["Endocrinology", "10-12", "⭐⭐⭐⭐ High"],
    ["Respiratory", "8-10", "⭐⭐⭐⭐ High"],
    ["Gastroenterology", "6-8", "⭐⭐⭐ Moderate-High"],
    ["Nephrology", "6-8", "⭐⭐⭐ Moderate-High"],
    ["Haematology", "5-7", "⭐⭐⭐ Moderate"],
    ["Dermatology", "4-6", "⭐⭐ Moderate"],
    ["Psychiatry", "4-5", "⭐⭐ Moderate"],
    ["Emergency/Poisoning", "5-7", "⭐⭐⭐ Moderate-High"],
    ["Rheumatology", "3-5", "⭐⭐ Moderate"],
]
t = std_table(freq_data[0], freq_data[1:], [6*cm,5*cm,6*cm], sc["dark"], sc["light"])
story.append(t)
story.append(PageBreak())

# ── CH 1: CARDIOLOGY ──────────────────────────────────────────────
story.append(chapter_header("CHAPTER 1: CARDIOLOGY (14-16 Qs/Year)", sc["dark"]))
story.append(sp(6))
story.append(section_bar("1.1 RHEUMATIC FEVER & RHEUMATIC HEART DISEASE", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>Jones Criteria (2015 Revised AHA)</b>", st))
story.append(sb("Major: Carditis (clinical/subclinical), Polyarthritis, Chorea, Erythema marginatum, Subcutaneous nodules", st))
story.append(sb("Minor: Fever ≥38.5°C, Elevated ESR/CRP, Prolonged PR interval (not if carditis is major), Arthralgia (only if polyarthritis not used)", st))
story.append(sb("Required: 2 Major OR 1 Major + 2 Minor PLUS evidence of preceding Strep infection (ASO titre ≥200 Todd units, +ve throat culture, rapid Strep Ag test)", st))
story.append(mn("Major criteria SPEC-C: Sydenham's chorea, Polyarthritis, Erythema marginatum, Carditis, subcutaneous nodes", st))
story.append(b("<b>Mitral Stenosis (MS) — PYQ Favourite</b>", st))
story.append(sb("Most common rheumatic valve lesion; M1>T1 area involved sequentially", st))
story.append(sb("Symptoms: Dyspnoea, haemoptysis (pulmonary HTN), AF (40%), systemic emboli", st))
story.append(sb("Signs: Loud S1, Opening snap (OS), Mid-diastolic murmur (MDM) at apex", st))
story.append(sb("S1-OS interval: Shorter interval = more severe (higher LA pressure)", st))
story.append(sb("MVA: Normal 4-6 cm²; Mild >1.5 cm²; Moderate 1-1.5 cm²; Severe <1 cm²", st))
story.append(sb("Wilkins score ≤8 = suitable for PTMC (Percutaneous Transvenous Mitral Commissurotomy)", st))
story.append(h("Graham Steell murmur = early diastolic murmur of pulmonary regurgitation due to pulmonary HTN in MS", st))
story.append(pyq_box([
    "A patient with MS develops AF. The drug that reduces ventricular rate and has positive inotropic effect is: Digoxin (2022)",
    "Radiological finding in MS: Double contour of right cardiac border (enlarged LA) (2021)",
    "Earliest sign of MS on CXR: Straightening of left heart border (2023)",
    "Wilkins score <8 is required for: PTMC (2020)",
    "Most common valve affected in RHD: Mitral valve (2024)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("Which sign on X-ray indicates significant LA enlargement in MS?",
     "Double contour of right cardiac border (D-shaped heart); also look for horizontal carina, fluffy lung fields"),
    ("A young woman with MS is 32 weeks pregnant and develops worsening dyspnoea. Best management?",
     "PTMC (Percutaneous balloon mitral valvotomy) — safe in pregnancy; avoid surgery"),
    ("In MS + AF, what is the anticoagulation target INR?",
     "INR 2-3 with Warfarin; NOAC not preferred in MS + AF (valve lesion)"),
], sc["mid"]))
story.append(sp(8))

story.append(section_bar("1.2 HEART FAILURE", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>Classification & Diagnosis</b>", st))
story.append(sb("HFrEF (EF<40%), HFmrEF (40-49%), HFpEF (≥50%)", st))
story.append(sb("NYHA Class: I=No symptoms; II=Symptoms on moderate exertion; III=Symptoms on minimal exertion; IV=Symptoms at rest", st))
story.append(sb("BNP >100 pg/mL = HF; NT-proBNP >300 pg/mL = HF; BNP <35 or NT-proBNP <125 = HF unlikely", st))
story.append(b("<b>Management of HFrEF (4 Pillars — 2022 ESC)</b>", st))
t = std_table(
    ["Drug Class","Example","Benefit"],
    [["ACEi/ARB/ARNi","Ramipril/Sacubitril-Valsartan","Reduces mortality; ARNi preferred over ACEi"],
     ["Beta-blocker","Carvedilol, Bisoprolol, Metoprolol","Reduces sudden death; start when stable"],
     ["MRA","Spironolactone, Eplerenone","Reduces mortality; monitor K+"],
     ["SGLT2i","Dapagliflozin, Empagliflozin","Reduces HF hospitalisation + CV death (DAPA-HF)"]],
    [5*cm,5*cm,7*cm], sc["dark"], sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(h("Sacubitril-Valsartan (Entresto) = ARNi; superior to ACEi in chronic HFrEF (PARADIGM-HF trial)", st))
story.append(h("Acute decompensated HF: Furosemide IV + O2 + Morphine + GTN; Sit upright", st))
story.append(pyq_box([
    "Drug contraindicated in HF: Thiazolidinediones (Rosiglitazone) (2021)",
    "Best initial investigation in suspected HF: BNP / Echo (2022)",
    "SGLT2 inhibitor shown to reduce HF hospitalisations: Dapagliflozin (DAPA-HF) (2023)",
    "Cardiac resynchronisation therapy (CRT) indicated when: EF<35% + LBBB + QRS>150ms (2024)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("What is the mechanism of SGLT2 inhibitors in heart failure?",
     "Osmotic diuresis, afterload/preload reduction, anti-fibrotic, anti-inflammatory, metabolic shift to ketones — reduces HF hospitalisation and CV death"),
    ("A HF patient on ACEi develops dry cough. What is the next step?",
     "Switch to ARB (e.g., Valsartan or Losartan); ARNi (Sacubitril-Valsartan) preferred if tolerated"),
], sc["mid"]))
story.append(sp(8))

story.append(section_bar("1.3 MYOCARDIAL INFARCTION", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>STEMI Management (Time-Sensitive)</b>", st))
story.append(sb("Primary PCI: Goal door-to-balloon <90 min (first medical contact to balloon <120 min)", st))
story.append(sb("Thrombolysis if PCI not available within 120 min: Streptokinase, Alteplase, Tenecteplase", st))
story.append(sb("Contraindications to thrombolysis: Prior ICH, ischaemic stroke <3 months, active bleeding, aortic dissection", st))
story.append(b("<b>Cardiac Enzyme Sequence (Memorise Order)</b>", st))
t = std_table(
    ["Marker","Rises","Peaks","Returns to normal"],
    [["Myoglobin","1-3h","6-9h","24h — earliest, not specific"],
     ["CK-MB","4-8h","18-24h","48-72h — best for re-infarction"],
     ["Troponin I/T","3-12h","24-48h","5-14d — gold standard, most sensitive+specific"],
     ["LDH","24-48h","3-5d","8-14d — late marker"],
    ],
    [3.5*cm,3*cm,3*cm,7.5*cm], sc["dark"], sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(b("<b>ECG Localisation of MI</b>", st))
story.append(sb("Anterior (LAD): V1-V4; Anterolateral (LAD/LCx): V4-V6 + I, aVL", st))
story.append(sb("Inferior (RCA): II, III, aVF; Right ventricular: V3R-V4R + inferior changes", st))
story.append(sb("Posterior (RCA/LCx): Tall R, ST depression in V1-V2 (mirror image)", st))
story.append(h("RV infarction: Hypotension + clear lungs + raised JVP + inferior MI → AVOID nitrates, give fluids", st))
story.append(h("Wellens syndrome: Critical LAD stenosis; Biphasic T in V2-V3 (Type A) or Deep T inversion (Type B)", st))
story.append(pyq_box([
    "Most sensitive and specific marker of MI: Troponin I or T (2020, 2022, 2024)",
    "ECG of posterior MI shows: Tall R wave + ST depression in V1-V2 (2021)",
    "Dressler syndrome occurs: 2-10 weeks post-MI (autoimmune pericarditis) (2023)",
    "TIMI risk score is used for: Risk stratification in NSTEMI/UA (2022)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("A patient with inferior MI develops hypotension, clear lungs, elevated JVP. Diagnosis and treatment?",
     "RV infarction. Avoid nitrates/diuretics. Give IV fluids (NS) to maintain preload. Dobutamine if cardiogenic shock."),
    ("Enzyme that rises and returns to normal fastest in MI?",
     "Myoglobin (rises 1-3h, normalises by 24h) — most sensitive early but NOT specific"),
    ("What is the advantage of CK-MB over Troponin in MI?",
     "CK-MB normalises in 48-72h — useful to detect re-infarction; Troponin stays elevated for 14 days"),
], sc["mid"]))
story.append(sp(8))

story.append(section_bar("1.4 ARRHYTHMIAS & ECG", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>Atrial Fibrillation (AF)</b>", st))
story.append(sb("Irregularly irregular pulse; absent P waves; fibrillatory baseline; variable RR", st))
story.append(sb("Rate control: Beta-blockers, Diltiazem, Digoxin (if HF)", st))
story.append(sb("Rhythm control: DC cardioversion, Amiodarone, Flecainide (no structural heart disease)", st))
story.append(sb("Anticoagulation: CHA2DS2-VASc ≥2 (M) or ≥3 (F) → NOAC/Warfarin", st))
story.append(sb("CHA2DS2-VASc: CHF, HTN, Age≥75(x2), DM, Stroke/TIA(x2), Vascular disease, Age65-74, Sex(F)", st))
story.append(b("<b>Complete Heart Block (CHB)</b>", st))
story.append(sb("P waves and QRS dissociated; ventricular rate 20-40 bpm; Stokes-Adams attacks (syncope)", st))
story.append(sb("Emergency: IV Atropine → Temporary pacing → Permanent pacemaker", st))
story.append(b("<b>Long QT Syndrome</b>", st))
story.append(sb("QTc >440ms (male), >460ms (female); risk of Torsades de Pointes → VF → sudden death", st))
story.append(sb("Causes: Hypokalaemia, Hypomagnesia, Drugs (amiodarone, erythromycin, haloperidol, methadone)", st))
story.append(sb("Torsades: IV Magnesium sulfate (first line); DC shock if pulseless", st))
story.append(pyq_box([
    "Drug of choice for Wolff-Parkinson-White + AF: DC cardioversion / Procainamide (avoid digoxin/verapamil) (2023)",
    "ECG finding in hyperkalaemia: Peaked T waves → PR prolongation → wide QRS → sine wave (2020, 2021)",
    "Delta wave on ECG: WPW syndrome (2022)",
    "Drug that prolongs QT interval: Amiodarone, Erythromycin, Haloperidol (2024)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("A patient with AF and WPW develops fast AF (250 bpm). Most dangerous complication?",
     "VF via accessory pathway. Avoid AV nodal blockers (digoxin, verapamil, beta-blockers). Give DC cardioversion or Procainamide/Ibutilide."),
    ("Drug causing both hyperthyroidism AND pulmonary fibrosis?",
     "Amiodarone. Also causes corneal microdeposits, photosensitivity, hepatotoxicity. Contains 37% iodine."),
], sc["mid"]))
story.append(sp(6))

story.append(section_bar("1.5 HYPERTENSION", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>JNC 8 / 2017 ACC/AHA Classification</b>", st))
story.append(sb("Normal: <120/80; Elevated: 120-129/<80; Stage 1 HTN: 130-139/80-89; Stage 2: ≥140/90", st))
story.append(sb("HTN urgency: Severe BP elevation without end-organ damage → oral antihypertensives", st))
story.append(sb("HTN emergency: Severe BP + end-organ damage → IV labetalol, nicardipine, nitroprusside; reduce BP by max 25% in 1h", st))
story.append(b("<b>Compelling Indications for Specific Drugs</b>", st))
t = std_table(
    ["Condition","Drug of Choice"],
    [["Diabetic nephropathy","ACEi or ARB (renoprotective)"],
     ["Post-MI","Beta-blocker + ACEi"],
     ["Heart failure","ACEi/ARB + BB + MRA + SGLT2i"],
     ["Pregnancy","Methyldopa (safest), Labetalol, Nifedipine"],
     ["Bilateral renal artery stenosis","Avoid ACEi/ARB (risk of acute renal failure)"],
     ["Phaeochromocytoma","Alpha-blocker FIRST (Phenoxybenzamine), THEN beta-blocker"],
    ],
    [7*cm,10*cm], sc["dark"], sc["light"]
)
story.append(t)
story.append(pyq_box([
    "Drug contraindicated in bilateral RAS: ACEi/ARB (2020)",
    "Drug of choice for HTN in pregnancy: Methyldopa / Labetalol (2021, 2023)",
    "Hypertensive emergency with aortic dissection: Drug of choice: IV Labetalol (2022)",
    "Drug causing reflex tachycardia in HTN: Hydralazine, Minoxidil (2024)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("Why must alpha-blockers be given BEFORE beta-blockers in phaeochromocytoma?",
     "Beta-blocker alone → unopposed alpha effect → paradoxical severe HTN. Alpha-block first to prevent this crisis."),
    ("A pregnant woman at 34 weeks has BP 170/110, headache, proteinuria. What is the drug to control acute BP?",
     "IV Labetalol (first line) or oral Nifedipine; avoid ACEi/ARB (teratogenic), avoid atenolol"),
], sc["mid"]))
story.append(PageBreak())

# ── CH 2: INFECTIOUS DISEASES ─────────────────────────────────────
story.append(chapter_header("CHAPTER 2: INFECTIOUS DISEASES (12-14 Qs/Year)", sc["dark"]))
story.append(sp(6))
story.append(section_bar("2.1 TUBERCULOSIS", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>Pathology & Types</b>", st))
story.append(sb("Ghon focus = primary lesion (mid/lower zone); Ghon complex = Ghon focus + hilar LN", st))
story.append(sb("Ranke complex = calcified Ghon complex (healed primary TB)", st))
story.append(sb("Simon foci = seeded apical lesions during primary bacteraemia", st))
story.append(sb("Post-primary (reactivation) TB: Upper lobe apico-posterior segments (better O2)", st))
story.append(sb("Miliary TB: 1-3mm uniform nodules on CXR; haematogenous spread; CSF: lymphocytosis, high protein, very low glucose", st))
story.append(b("<b>NTEP Treatment (2023 Guidelines)</b>", st))
t = std_table(
    ["Category","Intensive Phase","Continuation Phase"],
    [["New pulmonary TB","2 months HRZE","4 months HR (total 6 months)"],
     ["Previously treated","2 months HRZES + 1 month HRZE","5 months HRE (total 8 months)"],
     ["TB meningitis","2 months HRZE","10 months HR (total 12 months)"],
     ["Bone/joint TB","2 months HRZE","16 months HR (total 18 months)"],
    ],
    [4.5*cm,5*cm,7.5*cm], sc["dark"], sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(b("<b>Drug Side Effects (Very High Yield)</b>", st))
story.append(sb("Isoniazid (INH): Peripheral neuropathy (give Pyridoxine B6), Hepatotoxicity, SLE-like", st))
story.append(sb("Rifampicin: Orange urine/tears/saliva, Hepatotoxicity, Enzyme INDUCER (reduces OCP efficacy)", st))
story.append(sb("Pyrazinamide: Hyperuricaemia (gout), Hepatotoxicity", st))
story.append(sb("Ethambutol: Retrobulbar neuritis (colour vision loss, red-green defect; monitor visual acuity)", st))
story.append(sb("Streptomycin: Ototoxicity (8th CN — vestibular > cochlear), Nephrotoxicity, Teratogenic", st))
story.append(mn("RIPE side effects: Rash, INH-neuropathy, Pyrazinamide-hyperuricaemia, Ethambutol-eyes", st))
story.append(pyq_box([
    "Antitubercular drug causing optic neuritis: Ethambutol (2020, 2021, 2022, 2023, 2024 — REPEATED EVERY YEAR)",
    "INH peripheral neuropathy prevented by: Pyridoxine (Vitamin B6) (2020, 2022)",
    "Rifampicin mechanism of action: Inhibits DNA-dependent RNA polymerase (2021)",
    "MDR-TB definition: Resistant to both INH and Rifampicin (2023)",
    "Gold standard for TB diagnosis: Culture on Lowenstein-Jensen medium (2020)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("A TB patient on treatment develops yellow vision and cannot distinguish red from green. Which drug is responsible?",
     "Ethambutol — causes retrobulbar optic neuritis. Stop ethambutol, do ophthalmology review."),
    ("A woman on ATT becomes pregnant. Which drug should be AVOIDED?",
     "Streptomycin (ototoxic to fetus — 8th CN damage). All other first-line drugs are generally safe."),
    ("INH is used alone for what purpose?",
     "TB chemoprophylaxis (latent TB): INH 5mg/kg/day for 6 months; or INH + Rifapentine 3 months (3HP regimen)"),
], sc["mid"]))
story.append(sp(8))

story.append(section_bar("2.2 MALARIA", sc["mid"], sc["light"]))
story.append(sp(4))
t = std_table(
    ["Species","Fever Cycle","Special Features","Complications"],
    [["P. falciparum","Malignant tertian (36-48h)","Appliqué/Accolé forms; multiple rings in RBC; no Schuffner's dots","Cerebral malaria, blackwater fever, hypoglycaemia, ARDS, renal failure"],
     ["P. vivax/ovale","Benign tertian (48h)","Schuffner's dots; hypnozoites in liver","Rupture of spleen; relapse"],
     ["P. malariae","Quartan (72h)","Ziemann's dots","Nephrotic syndrome (quartan nephropathy)"],
     ["P. knowlesi","Daily (24h)","Zoonosis (monkeys); severe malaria","Severe malaria"],
    ],
    [3*cm,3.5*cm,5*cm,5.5*cm], sc["dark"], sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(b("<b>Treatment</b>", st))
story.append(sb("Uncomplicated P. falciparum: ACT = Artemether + Lumefantrine (AL) OR Artesunate + Amodiaquine", st))
story.append(sb("Severe/cerebral malaria: IV Artesunate (preferred); IV Quinine + Doxycycline (alternative)", st))
story.append(sb("P. vivax: Chloroquine + Primaquine 14 days (to eradicate hypnozoites; check G6PD before)", st))
story.append(sb("Chemoprophylaxis: Mefloquine weekly; Doxycycline daily; Atovaquone-proguanil daily", st))
story.append(h("Primaquine contraindicated in: G6PD deficiency, Pregnancy", st))
story.append(pyq_box([
    "Malaria parasite causing nephrotic syndrome: P. malariae (2020, 2023)",
    "Drug used to eradicate hypnozoites of P. vivax: Primaquine (2021, 2024)",
    "Blackwater fever complication of: P. falciparum (2022)",
    "First-line treatment of severe malaria: IV Artesunate (WHO 2021 guidelines) (2024)",
    "Rapid diagnostic test for P. falciparum detects: HRP-2 antigen (2021)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("A patient with P. vivax malaria is prescribed Primaquine. Before starting, which test is mandatory?",
     "G6PD (Glucose-6-Phosphate Dehydrogenase) deficiency test. Primaquine causes haemolytic anaemia in G6PD deficiency."),
    ("Mechanism of cerebral malaria?",
     "P. falciparum RBC express PfEMP1 on surface → cytoadherence to brain endothelium → microvascular occlusion + inflammation → cerebral oedema, coma"),
], sc["mid"]))
story.append(sp(8))

story.append(section_bar("2.3 DENGUE, TYPHOID, LEPTOSPIROSIS", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>Dengue — Warning Signs (WHO 2009)</b>", st))
story.append(sb("Warning signs: Abdominal pain/tenderness, persistent vomiting, clinical fluid accumulation, mucosal bleed, lethargy/restlessness, liver >2cm, lab: increasing haematocrit + rapid decrease in platelet", st))
story.append(sb("NS1 antigen: Positive days 1-5; IgM: positive day 5 onwards; IgG: secondary infection", st))
story.append(sb("DHF criteria: Fever + haemorrhage + thrombocytopenia <100,000 + plasma leakage evidence", st))
story.append(sb("Treatment: Supportive only; NO aspirin/NSAIDs/steroids; platelet transfusion if <10,000 or active bleed", st))
story.append(b("<b>Typhoid — High-Yield Facts</b>", st))
story.append(sb("Widal test: TO ≥1:160, TH ≥1:160 significant (but cross-reactions common)", st))
story.append(sb("Gold standard diagnosis: Blood culture (1st week) → Stool culture (3rd week) → Urine culture (3rd week)", st))
story.append(sb("Rose spots: Crops of 2-3mm pink macules on abdomen in 1st week", st))
story.append(sb("Relative bradycardia = Faget's sign (pulse doesn't rise proportionally with fever)", st))
story.append(sb("Treatment: Azithromycin (uncomplicated); IV Ceftriaxone (severe/complicated/CNS)", st))
story.append(sb("Complications: Intestinal perforation (3rd week; ileum), haemorrhage, hepatitis, myocarditis", st))
story.append(b("<b>Leptospirosis</b>", st))
story.append(sb("Weil's disease = severe: jaundice + renal failure + bleeding; organism: Leptospira interrogans", st))
story.append(sb("Diagnosis: MAT (Microscopic Agglutination Test) = gold standard; IgM ELISA for screening", st))
story.append(sb("Treatment: Mild = Doxycycline; Severe = IV Penicillin G or IV Ceftriaxone", st))
story.append(pyq_box([
    "Dengue serotypes: DENV 1-4; secondary heterotypic infection causes DHF/DSS (2020, 2022)",
    "Gold standard for typhoid diagnosis: Blood culture (2020, 2021, 2023)",
    "Drug of choice for typhoid in pregnancy: Azithromycin or Ceftriaxone (avoid quinolones) (2024)",
    "Leptospira reservoir host: Rats (2021)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("Why does secondary dengue infection cause more severe disease?",
     "Antibody-Dependent Enhancement (ADE): Pre-existing cross-reactive antibodies from first infection bind new serotype but don't neutralise it; instead enhance viral entry into macrophages → massive cytokine storm → DHF/DSS"),
    ("A febrile jaundiced patient with renal failure returns from flood-affected area. Diagnosis?",
     "Weil's disease (severe leptospirosis). Send MAT/IgM ELISA; treat with IV Penicillin G or Ceftriaxone."),
], sc["mid"]))
story.append(PageBreak())

# ── CH 3: NEUROLOGY ───────────────────────────────────────────────
story.append(chapter_header("CHAPTER 3: NEUROLOGY (10-12 Qs/Year)", sc["dark"]))
story.append(sp(6))
story.append(section_bar("3.1 STROKE", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>Ischaemic Stroke Management</b>", st))
story.append(sb("IV tPA (Alteplase): Within 4.5 hours of symptom onset; exclude haemorrhage by CT first", st))
story.append(sb("Contraindications to thrombolysis: BP >185/110, prior ICH, active bleeding, platelets <100,000, stroke/head injury <3 months", st))
story.append(sb("Mechanical thrombectomy: Large vessel occlusion (MCA, ICA, basilar); within 24h if salvageable penumbra", st))
story.append(sb("NIHSS: 0=no stroke; 1-4=minor; 5-15=moderate; 16-20=moderate-severe; 21-42=severe", st))
story.append(b("<b>Lacunar vs Cortical Stroke</b>", st))
story.append(sb("Lacunar: Small vessel disease; pure motor, pure sensory, ataxic hemiparesis, dysarthria-clumsy hand; NO cortical signs", st))
story.append(sb("Cortical: Aphasia, neglect, hemianopia, agnosia — these require large vessel involvement", st))
story.append(b("<b>Important Stroke Syndromes</b>", st))
story.append(sb("MCA territory: Contralateral hemiplegia (face/arm>leg), aphasia (dominant), neglect (non-dominant)", st))
story.append(sb("Wallenberg syndrome (PICA): Ipsilateral face sensory loss + contralateral body sensory loss; dysphagia, Horner's", st))
story.append(sb("Weber's syndrome (midbrain): Ipsilateral CN III palsy + contralateral hemiplegia", st))
story.append(pyq_box([
    "Time window for IV tPA in ischaemic stroke: 4.5 hours from symptom onset (2020, 2021, 2023)",
    "Locked-in syndrome: Basilar artery occlusion; only vertical eye movements preserved (2022)",
    "Charcot's triad of TIA: Not applicable; Charcot's triad = cholangitis (jaundice+fever+RUQ pain) (2024)",
    "Cerebral venous sinus thrombosis: Anticoagulate even with haemorrhagic infarct (2023)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("A 70-year-old presents 2h after stroke. CT shows no haemorrhage. BP is 200/110. Should you give tPA?",
     "Reduce BP to <185/110 first (IV labetalol/nicardipine), THEN give tPA if no other contraindications. BP >185/110 is a contraindication."),
    ("Wallenberg syndrome — which vessel is occluded?",
     "Posterior Inferior Cerebellar Artery (PICA) or vertebral artery. Features: ipsilateral facial sensory loss, Horner's, palatal palsy, ataxia; contralateral body sensory loss"),
], sc["mid"]))
story.append(sp(6))

story.append(section_bar("3.2 MENINGITIS & ENCEPHALITIS", sc["mid"], sc["light"]))
story.append(sp(4))
t = std_table(
    ["Type","Cells","Protein","Glucose","Opening Pressure","Organisms"],
    [["Bacterial","PMN >1000","Very high >1g/L","<45mg/dL or <50% serum","High","Pneumococcus, Meningococcus, Listeria (elderly/immunocomp)"],
     ["Viral","Lymphocytes 50-500","Mildly raised","Normal (may be low in mumps)","Normal-mildly high","Enteroviruses, HSV, EBV"],
     ["TB","Lymphocytes 100-400","Very high (fibrin web)","Very low","High","M. tuberculosis; ADA>40 U/L"],
     ["Fungal","Lymphocytes","High","Low","Very high","Cryptococcus; India ink +ve"],
    ],
    [2*cm,3.5*cm,3*cm,3*cm,3*cm,7*cm], sc["dark"], sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(b("<b>Empirical Treatment of Bacterial Meningitis</b>", st))
story.append(sb("Adults: Ceftriaxone 2g IV BD + Dexamethasone 0.15 mg/kg QDS (start BEFORE or with first antibiotic)", st))
story.append(sb("Add Ampicillin if: Age >50, immunocompromised, alcoholic — covers Listeria", st))
story.append(sb("Neonates <3 months: Ampicillin + Cefotaxime (covers Listeria, E. coli, GBS)", st))
story.append(h("HSV encephalitis: Temporal lobe involvement; bloody/xanthochromic CSF; PCR for HSV-DNA; Rx: Acyclovir IV", st))
story.append(pyq_box([
    "CSF finding in TB meningitis: Lymphocytosis, high protein, very low glucose, ADA elevated (repeated 2020-2024)",
    "Drug added to cover Listeria in meningitis: Ampicillin (2021, 2022)",
    "Kernig's sign: Inability to extend knee when hip flexed 90° (2020)",
    "Rash of meningococcemia: Non-blanching petechiae/purpura (2023)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("Why is dexamethasone given in bacterial meningitis?",
     "Reduces neuroinflammation, decreases TNF and IL-1 release, lowers risk of hearing loss and neurological sequelae (especially for pneumococcal and H. influenzae meningitis)"),
    ("CSF showing: Glucose 20mg/dL (serum 90), Protein 3g/L, 200 lymphocytes, fibrin web — Diagnosis?",
     "TB meningitis. Check ADA (>40 U/L), Gram stain, AFB stain, culture. Start 2HRZE + continue HR for 12 months total. Add Prednisolone 1-2 mg/kg/day for raised ICP."),
], sc["mid"]))
story.append(sp(6))

story.append(section_bar("3.3 PARKINSON'S + MOVEMENT DISORDERS", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>Parkinson's Disease</b>", st))
story.append(sb("Cardinal features (TRAP): Tremor (4-6Hz resting, pill-rolling), Rigidity (cogwheel/lead pipe), Akinesia/Bradykinesia, Postural instability", st))
story.append(sb("Pathology: Loss of dopaminergic neurons in substantia nigra pars compacta; Lewy bodies (alpha-synuclein)", st))
story.append(sb("Hoehn-Yahr scale: 1=Unilateral; 2=Bilateral no balance; 3=Mild postural instability; 4=Severe disability; 5=Wheelchair/bedridden", st))
story.append(b("<b>Treatment</b>", st))
story.append(sb("Levodopa + Carbidopa: Gold standard; carbidopa prevents peripheral conversion of L-DOPA", st))
story.append(sb("Dopamine agonists: Pramipexole, Ropinirole — young patients to delay levodopa", st))
story.append(sb("MAOB inhibitors: Selegiline, Rasagiline — neuroprotective (?); adjunct", st))
story.append(sb("COMT inhibitors: Entacapone — extend 'on' time; reduces 'wearing-off'", st))
story.append(sb("DBS (Deep Brain Stimulation): Target = subthalamic nucleus or globus pallidus interna", st))
story.append(h("On-off phenomenon + peak-dose dyskinesia = long-term levodopa complications", st))
story.append(pyq_box([
    "Lewy bodies are composed of: Alpha-synuclein (2021, 2023)",
    "Drug that causes drug-induced Parkinsonism: Metoclopramide, Haloperidol, Reserpine (2022)",
    "Target of DBS in Parkinson's: Subthalamic nucleus (STN) (2024)",
    "Parkinsonism + dementia + hallucinations: Lewy body dementia (2023)",
], sc["mid"], sc["light"]))
story.append(PageBreak())

# ── CH 4: ENDOCRINOLOGY ───────────────────────────────────────────
story.append(chapter_header("CHAPTER 4: ENDOCRINOLOGY (10-12 Qs/Year)", sc["dark"]))
story.append(sp(6))
story.append(section_bar("4.1 DIABETES MELLITUS", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>Diagnostic Criteria (ADA 2024)</b>", st))
story.append(sb("FBS ≥126 mg/dL (on 2 occasions); RBS ≥200 + symptoms; OGTT 2h ≥200; HbA1c ≥6.5%", st))
story.append(sb("Pre-diabetes: FBS 100-125 (IFG); OGTT 2h 140-199 (IGT); HbA1c 5.7-6.4%", st))
story.append(b("<b>DKA vs HHS</b>", st))
t = std_table(
    ["Feature","DKA","HHS (HONK)"],
    [["Patient","T1DM (also T2DM)","Elderly T2DM"],
     ["Blood glucose",">250 mg/dL (usually 300-600)","Very high >600 mg/dL"],
     ["pH","<7.3","Normal or mildly reduced"],
     ["Ketones","Strongly positive (ketonemia, ketonuria)","Absent or trace"],
     ["Osmolality","<320 mOsm/kg","Very high >320 mOsm/kg"],
     ["Mortality","~5%","~15-20%"],
     ["Treatment","Fluids (NS) → Insulin infusion → K+ replacement","Aggressive rehydration; insulin less critical"],
    ],
    [4*cm,6.5*cm,6.5*cm], sc["dark"], sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(h("DKA K+ management: If K+ <3.5 → give K+ BEFORE starting insulin (insulin drives K+ into cells)", st))
story.append(h("Somogyi effect: Rebound AM hyperglycaemia after nocturnal hypoglycaemia → reduce evening insulin", st))
story.append(h("Dawn phenomenon: AM hyperglycaemia due to GH + cortisol rise overnight → increase basal insulin", st))
story.append(b("<b>Oral Hypoglycaemic Agents — Drug Mechanisms (PYQ Gold)</b>", st))
t = std_table(
    ["Drug","Mechanism","Key Side Effect"],
    [["Metformin","Activates AMPK → reduces hepatic gluconeogenesis","Lactic acidosis (CI: eGFR<30, contrast, liver failure)"],
     ["Sulphonylureas (Glibenclamide)","Closes K+ATP channels → insulin release","Hypoglycaemia, weight gain"],
     ["SGLT2i (Dapagliflozin)","Blocks Na-glucose cotransporter-2 in kidney","Genital mycosis, DKA (euglycaemic), UTI"],
     ["GLP-1 agonists (Semaglutide)","Incretins → glucose-dependent insulin, slows gastric emptying","Nausea, pancreatitis (rare); CV benefit"],
     ["DPP-4 inhibitors (Sitagliptin)","Inhibit DPP-4 → prevent GLP-1 breakdown","Weight neutral; HF hospitalisation (saxagliptin)"],
     ["TZD (Pioglitazone)","PPAR-gamma agonist → insulin sensitiser","Weight gain, fluid retention, HF, fractures"],
    ],
    [4*cm,6*cm,7*cm], sc["dark"], sc["light"]
)
story.append(t)
story.append(pyq_box([
    "Drug that causes euglycaemic DKA: SGLT2 inhibitors (2023, 2024)",
    "Mechanism of metformin: Inhibits hepatic gluconeogenesis via AMPK activation (2020, 2022)",
    "HbA1c target for most T2DM patients: <7% (2021)",
    "Drug of choice in DM + CKD (eGFR 30-60): SGLT2i or GLP-1 agonist (2024)",
    "DKA precipitant: Infection most common (2020)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("A T2DM patient on metformin needs IV contrast for CT. What to do?",
     "Stop metformin 48h before contrast; check renal function after; restart only when creatinine stable. Risk: contrast-induced nephropathy + metformin-associated lactic acidosis."),
    ("GLP-1 agonists vs DPP-4 inhibitors — key differences?",
     "GLP-1 agonists: Injectable, cause significant weight loss, nausea, CV benefit proven (LEADER, SUSTAIN-6). DPP-4 inhibitors: Oral, weight neutral, modest HbA1c reduction, no CV benefit; Saxagliptin associated with HF hospitalisation."),
], sc["mid"]))
story.append(sp(6))

story.append(section_bar("4.2 THYROID DISORDERS", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>Hypothyroidism</b>", st))
story.append(sb("Primary: High TSH, Low T4 (most common — Hashimoto's thyroiditis: anti-TPO, anti-thyroglobulin Abs)", st))
story.append(sb("Secondary (pituitary): Low TSH, Low T4; Tertiary (hypothalamic): Low TRH", st))
story.append(sb("Myxoedema coma: LOC + hypothermia + bradycardia; Treatment: IV T4 (levothyroxine) + IV T3 + IV steroids (for possible adrenal insufficiency)", st))
story.append(b("<b>Hyperthyroidism</b>", st))
story.append(sb("Graves disease: Diffuse toxic goitre + ophthalmopathy + pretibial myxoedema; TRAb (TSH receptor antibodies)", st))
story.append(sb("Toxic adenoma: Single hot nodule on isotope scan; TSH-independent", st))
story.append(sb("Thyroid storm: Fever >38.5°C + tachycardia + CNS changes; Burch-Wartofsky score >45 = thyroid storm", st))
story.append(sb("Thyroid storm Rx: PTU (block synthesis + T4→T3 conversion) → Lugol's iodine (1h after PTU) → Beta-blocker + Steroids + cooling", st))
story.append(b("<b>Thyroid Cancer</b>", st))
t = std_table(
    ["Type","Frequency","Histology/Marker","Prognosis"],
    [["Papillary","70-80%","Orphan Annie nuclei, Psammoma bodies","Best; spreads via lymphatics"],
     ["Follicular","10-15%","Hurthle cells; vascular invasion","Good; haematogenous spread"],
     ["Medullary","5%","Calcitonin marker; MEN2A/2B; amyloid stroma","Intermediate"],
     ["Anaplastic","<5%","Undifferentiated; elderly; invades trachea","Very poor"],
    ],
    [3*cm,3.5*cm,7*cm,3.5*cm], sc["dark"], sc["light"]
)
story.append(t)
story.append(pyq_box([
    "Thyroid cancer associated with MEN 2A: Medullary carcinoma (2020, 2021, 2022)",
    "Most common thyroid cancer: Papillary carcinoma (2020-2024 — asked every year)",
    "Propylthiouracil vs Carbimazole in thyroid storm: PTU preferred (also inhibits T4→T3 conversion) (2023)",
    "Antibody in Graves disease: TSH receptor antibody (TRAb/TSHI) (2021)",
], sc["mid"], sc["light"]))
story.append(PageBreak())

# ── CH 5: EMERGENCY & POISONING ───────────────────────────────────
story.append(chapter_header("CHAPTER 5: EMERGENCY MEDICINE & POISONING (5-7 Qs/Year)", sc["dark"]))
story.append(sp(6))
story.append(section_bar("5.1 POISONING (Very High Yield — PYQ Every Year)", sc["mid"], sc["light"]))
story.append(sp(4))
story.append(b("<b>Organophosphate (OP) Poisoning</b>", st))
story.append(sb("Mechanism: Inhibits acetylcholinesterase → accumulation of ACh → SLUDGE + Nicotinic + CNS effects", st))
story.append(sb("SLUDGE: Salivation, Lacrimation, Urination, Defecation, GI cramps, Emesis", st))
story.append(sb("Nicotinic: Muscle fasciculations, weakness, paralysis; tachycardia, hypertension", st))
story.append(sb("Treatment: Atropine (muscarinic antagonist) — repeat every 5-10 min until secretions dry", st))
story.append(sb("Pralidoxime (2-PAM): Reactivates AChE if given within 48h (before 'ageing' of OP-AChE bond)", st))
story.append(sb("Atropine endpoint: Dry secretions, HR>80, clear lung fields — NOT pupil dilation", st))
story.append(b("<b>Other Poisonings</b>", st))
t = std_table(
    ["Poison","Key Feature","Antidote/Treatment"],
    [["Paracetamol (PCM)","4 phases; hepatic failure; Rumack-Matthew nomogram","N-Acetylcysteine (NAC) within 8h; most effective"],
     ["Carbon Monoxide (CO)","Cherry-red skin; SpO2 falsely normal; COHb elevated","100% O2 NRM; Hyperbaric O2 if COHb>25%, pregnant, neurological signs"],
     ["Cyanide","Bitter almonds smell; metabolic acidosis; cellular hypoxia despite normal SpO2","Hydroxocobalamin (first line); Sodium thiosulfate + sodium nitrite"],
     ["Iron overdose","GI toxicity → cardiovascular collapse","Desferrioxamine (chelation)"],
     ["Lead","Burton's line on gums; basophilic stippling RBC; wrist drop","Dimercaprol (BAL) + EDTA; Succimer (oral) for children"],
     ["Methanol","Metabolic acidosis; visual toxicity (optic nerve)","Fomepizole (first line) or Ethanol; Folinic acid; Haemodialysis"],
     ["Tricyclic antidepressants","QRS widening; anticholinergic toxidrome; hypotension","Sodium bicarbonate (for QRS >100ms)"],
    ],
    [3.5*cm,5.5*cm,8*cm], sc["dark"], sc["light"]
)
story.append(t)
story.append(pyq_box([
    "Antidote for OP poisoning: Atropine + Pralidoxime (repeated 2020-2024)",
    "Antidote for paracetamol: N-Acetylcysteine (2020, 2022, 2024)",
    "Snake with neurotoxic venom: Krait, Cobra (elapidae) (2021, 2023)",
    "20-minute whole blood clotting test (20WBCT) positive in: Viper (haemotoxic) envenomation (2022)",
    "Antidote for benzodiazepine: Flumazenil (2021)",
    "Antidote for opioid: Naloxone (2020, 2023)",
], sc["mid"], sc["light"]))
story.append(examiner_box([
    ("A patient swallowed paracetamol 6 hours ago. Current LFTs are normal. Should you give NAC?",
     "YES. Plot on Rumack-Matthew nomogram using paracetamol level. NAC should be given if level above treatment line, regardless of current LFT. Liver injury peaks at 72-96h."),
    ("Miosis is seen in which poisonings?",
     "COPS: Clonidine/Cholinergic (OP), Opioids, Pontine haemorrhage, Sedative-hypnotics (some). Mydriasis = sympathomimetics, anticholinergics, cocaine, amphetamines."),
    ("Why is Pralidoxime ineffective after 48 hours in OP poisoning?",
     "Ageing: After ~48h, the OP-AChE bond becomes irreversibly dealkylated ('aged'). Pralidoxime works by displacing OP from AChE, but once aged, the bond cannot be reversed."),
], sc["mid"]))
story.append(sp(6))

story.append(section_bar("5.2 RHEUMATOLOGY (3-5 Qs/Year)", sc["mid"], sc["light"]))
story.append(sp(4))
t = std_table(
    ["Disease","Key Features","Antibody Marker"],
    [["SLE","Butterfly rash, discoid lupus, serositis, renal, haematological, neurological","ANA (sensitive), Anti-dsDNA (specific + disease activity), Anti-Sm (specific)"],
     ["Rheumatoid Arthritis","Symmetrical small joint polyarthritis, morning stiffness >1h, subcutaneous nodules","RF (not specific), Anti-CCP (most specific)"],
     ["Sjögren's syndrome","Dry eyes (keratoconjunctivitis sicca) + dry mouth (xerostomia)","Anti-Ro/SSA, Anti-La/SSB"],
     ["Antiphospholipid syndrome","Recurrent arterial/venous thrombosis + miscarriages + livedo reticularis","Anti-cardiolipin, Lupus anticoagulant, Anti-β2GP1"],
     ["Scleroderma (diffuse)","Raynaud's + skin thickening, pulmonary fibrosis, renal crisis","Anti-Scl-70 (topoisomerase)"],
     ["CREST syndrome","Calcinosis, Raynaud's, oEsophageal dysmotility, Sclerodactyly, Telangiectasia","Anti-centromere"],
    ],
    [3.5*cm,7.5*cm,6*cm], sc["dark"], sc["light"]
)
story.append(t)
story.append(pyq_box([
    "Most specific antibody for SLE: Anti-dsDNA and Anti-Sm (2020, 2021, 2023)",
    "CREST syndrome marker: Anti-centromere antibody (2022)",
    "Drug of choice for SLE: Hydroxychloroquine (2024)",
    "RA most specific marker: Anti-CCP (anti-citrullinated peptide) (2022, 2023)",
], sc["mid"], sc["light"]))
story.append(sp(8))

# Final rapid fire for medicine
story.append(chapter_header("RAPID FIRE — GENERAL MEDICINE MUST-KNOWS", sc["dark"]))
story.append(sp(6))
rapid = [
    "Osler-Weber-Rendu = Hereditary haemorrhagic telangiectasia; AV malformations",
    "Trousseau sign (carpopedal spasm) + Chvostek sign = Hypocalcaemia",
    "Grey Turner sign (flank bruising) + Cullen sign (periumbilical) = Haemorrhagic pancreatitis",
    "Courvoisier's law: Painless jaundice + palpable GB = Ca head of pancreas (NOT gallstones)",
    "Carcinoid syndrome: Flushing, diarrhoea, bronchospasm, RHF; 5-HIAA in urine; treat with Octreotide",
    "Acromegaly: GH excess; ring test (enlarged ring); Glucose suppression test (GH fails to suppress)",
    "Phaeochromocytoma: Rule of 10s; 24h urinary catecholamines/metanephrines (best test)",
    "Sickle cell crisis: Vaso-occlusive (pain); Sequestration (spleen); Aplastic (parvovirus B19)",
    "PCP pneumonia: CD4 <200; LDH elevated; ground-glass on CXR; Rx: High-dose Co-trimoxazole + steroids (if PaO2<70)",
    "CMV retinitis: CD4 <50; 'pizza pie' fundus; Rx: Ganciclovir IV or oral Valganciclovir",
    "Helicobacter pylori: Urease-producing; Campylobacter-like organism; triple therapy; test of cure: urea breath test 4wk post-treatment",
    "Normal CSF pressure: 7-18 cmH2O (opening pressure); IIH (pseudotumour cerebri) = raised ICP with normal imaging; Rx: Acetazolamide, weight loss",
]
for r in rapid:
    story.append(b(r, st))
story.append(sp(8))
footer_t = Table([[Paragraph("General Medicine Notes Complete — UPSC CMS 2026", ParagraphStyle('ft',fontSize=12,fontName='Helvetica-Bold',textColor=colors.white,alignment=TA_CENTER))]], colWidths=[17*cm])
footer_t.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),colors.HexColor(sc["dark"])),
    ('TOPPADDING',(0,0),(-1,-1),12),('BOTTOMPADDING',(0,0),(-1,-1),12)]))
story.append(footer_t)

doc.build(story)
print("Medicine PDF done")

cd /home/daytona/workspace/upsc-cms-notes && python gen_medicine.py

~/upsc-cms-notes/gen_paediatrics.py

import sys
sys.path.insert(0, '/home/daytona/workspace/upsc-cms-notes')
from pdf_helpers import *
from reportlab.platypus import PageBreak

OUT = "/home/daytona/workspace/upsc-cms-notes/02_Paediatrics.pdf"
doc = make_doc(OUT)
sc = SUBJECT_COLORS["paediatrics"]
st = make_styles(sc)
story = []

# COVER
story += [
    Spacer(1,2.5*cm),
    Paragraph("UPSC CMS 2026", st["cover_title"]),
    Paragraph("SUBJECT 2: PAEDIATRICS", ParagraphStyle('x',fontSize=20,textColor=colors.HexColor(sc["mid"]),alignment=TA_CENTER,spaceAfter=8,fontName='Helvetica-Bold')),
    Paragraph("24 Questions | PYQ 2020-2024 Mapped | Examiner-Style Questions", st["cover_sub"]),
    Spacer(1,0.3*cm),
    HRFlowable(width="80%",thickness=2,color=colors.HexColor(sc["dark"]),hAlign='CENTER'),
    Spacer(1,0.3*cm),
    Paragraph("EXAM: 2nd AUGUST 2026", st["cover_date"]),
    Spacer(1,0.8*cm),
]
freq_data = [
    ["Chapter","Avg Qs/Year","PYQ Frequency"],
    ["Development & Milestones","3-4","⭐⭐⭐⭐⭐ Very High"],
    ["Immunisation / NIS","3-4","⭐⭐⭐⭐⭐ Very High"],
    ["Neonatology","4-5","⭐⭐⭐⭐⭐ Very High"],
    ["Nutrition & Malnutrition","2-3","⭐⭐⭐⭐ High"],
    ["Paediatric Infections","2-3","⭐⭐⭐⭐ High"],
    ["Paediatric Haematology","1-2","⭐⭐⭐ Moderate"],
    ["Endocrine / Metabolic","1-2","⭐⭐⭐ Moderate"],
    ["Congenital Heart Defects","1-2","⭐⭐⭐ Moderate"],
]
story.append(std_table(freq_data[0],freq_data[1:],[6*cm,5*cm,6*cm],sc["dark"],sc["light"]))
story.append(PageBreak())

# CH 1 — DEVELOPMENTAL MILESTONES
story.append(chapter_header("CHAPTER 1: DEVELOPMENTAL MILESTONES (3-4 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("1.1 KEY MILESTONES TABLE",sc["mid"],sc["light"]))
story.append(sp(4))
t = std_table(
    ["Age","Gross Motor","Fine Motor/Vision","Language","Social/Adaptive"],
    [["2 months","Head control prone","Follows to midline; hands fisted","Cooing","Social smile"],
     ["4 months","Head steady; rolls front-to-back","Follows 180°; hands open; reaches","Laughing","Recognises mother"],
     ["6 months","Sits with support; rolls both ways","Transfers hand-to-hand; palmar grasp","Babbles (mamama)","Stranger anxiety begins"],
     ["9 months","Stands holding furniture; creeps","Inferior pincer grasp; bangs objects","Mama/dada non-specific; imitates sounds","Waves bye-bye; plays peek-a-boo"],
     ["12 months","Walks with one hand held","Mature pincer grasp; releases voluntarily","1-2 words specific (mama, dada)","Comes when called; drinks from cup"],
     ["15 months","Walks independently","Tower of 2 cubes; scribbles","4-6 words","Points to needs; uses spoon poorly"],
     ["18 months","Runs (stiff); walks up stairs with support","Tower of 3-4 cubes; turns pages","10-25 words; uses 'no'","Feeds self with spoon; removes clothing"],
     ["2 years","Runs well; kicks ball","Tower of 6 cubes; circular scribble","2-word phrases; 50+ words","Parallel play; pulls off pants"],
     ["3 years","Climbs stairs alternating feet; rides tricycle","Tower of 9 cubes; copies circle","3-word sentences; 250 words","Group play; knows name+age+sex"],
     ["4 years","Hops on one foot","Copies cross; draws man (3 parts)","4-5 word sentences; tells stories","Cooperative play; buttons clothes"],
     ["5 years","Skips; walks backward heel-to-toe","Copies triangle; draws man (6 parts)","Fluent sentences; counts 10 objects","Dresses independently"],
    ],
    [2*cm,3.5*cm,3.5*cm,3.5*cm,4.5*cm],sc["dark"],sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(h("Red Flags: No smile by 3m | No head control by 4m | Not sitting by 9m | Not walking by 18m | No words by 18m | No 2-word phrases by 2y",st))
story.append(sp(4))
story.append(section_bar("1.2 REFLEXES & THEIR DISAPPEARANCE AGE",sc["mid"],sc["light"]))
story.append(sp(4))
t = std_table(
    ["Reflex","Present From","Disappears By","Clinical Note"],
    [["Moro reflex","Birth","4-6 months","Absent = brain damage; asymmetric = brachial plexus injury"],
     ["Rooting reflex","Birth","3-4 months","Turns toward touch on cheek; feeding reflex"],
     ["Sucking reflex","Birth","4 months (voluntary after)",""],
     ["Palmar grasp","Birth","4-6 months","Persistent = cerebral palsy"],
     ["Plantar grasp","Birth","9-12 months",""],
     ["Babinski sign","Birth","12-18 months","Extensor plantar normal in infants; pathological if persists after 18m"],
     ["Parachute reflex","8-9 months","Persists lifetime","Absent or asymmetric = neurological problem"],
    ],
    [4*cm,3.5*cm,3.5*cm,6*cm],sc["dark"],sc["light"]
)
story.append(t)
story.append(pyq_box([
    "Age at which Moro reflex disappears: 4-6 months (2021, 2023)",
    "First milestone to appear: Social smile (2 months) (2020, 2022)",
    "Child copies circle — minimum age: 3 years (2021)",
    "Pincer grasp (mature) appears at: 9-10 months (2022, 2024)",
    "Red flag — not walking by: 18 months (2023)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("An 18-month-old child only says 'mama'. Is this normal?","No. By 18 months, 10-25 words expected. Single word at 18m = Language delay. Refer for hearing test and speech therapy."),
    ("Parachute reflex is absent at 10 months. What does this suggest?","Delayed or absent parachute reflex suggests central nervous system pathology — possible cerebral palsy or developmental delay. It normally appears at 8-9 months."),
    ("At what age does a child first draw a man with 6 parts?","5 years. At 3y: circle; 4y: cross; 5y: triangle; man with 6 parts at 5y."),
],sc["mid"]))
story.append(PageBreak())

# CH 2 — IMMUNISATION
story.append(chapter_header("CHAPTER 2: IMMUNISATION / NIS (3-4 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("2.1 NATIONAL IMMUNISATION SCHEDULE (NIS) 2024",sc["mid"],sc["light"]))
story.append(sp(4))
t = std_table(
    ["Age","Vaccine(s)","Route","Special Notes"],
    [["Birth","BCG, OPV-0, HepB-1","BCG intradermal left arm; OPV oral; HepB IM right thigh","BCG given within 24h of birth"],
     ["6 weeks","DPT-1, IPV-1, HepB-2, Hib-1, PCV-1, Rotavirus-1, OPV-1","IM/Oral","5-in-1 (DPT+IPV+HepB+Hib) in many states"],
     ["10 weeks","DPT-2, IPV-2, Hib-2, PCV-2, Rotavirus-2, OPV-2","IM/Oral",""],
     ["14 weeks","DPT-3, IPV-3, Hib-3, PCV-3, Rotavirus-3, OPV-3","IM/Oral","Last dose of primary series"],
     ["9-12 months","MR-1, JE-1 (endemic), Vit A-1","SC (MR, JE); Oral Vit A","MMR preferred in private sector"],
     ["16-24 months","DPT B1, OPV-4, Hib-B, MR-2, JE-2, Vit A-2","IM/Oral/SC","Booster doses"],
     ["5-6 years","DPT B2","IM","School entry booster"],
     ["10 years","Td (Tetanus-diphtheria)","IM","Adolescent booster"],
     ["16 years","Td","IM",""],
    ],
    [3*cm,5*cm,3*cm,6*cm],sc["dark"],sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(b("<b>Live vs Killed Vaccines</b>",st))
story.append(sb("Live attenuated: BCG, OPV, MMR/MR, Rotavirus, Yellow fever, Varicella, JE (SA14-14-2 strain), Oral typhoid (Ty21a)",st))
story.append(sb("Killed/Inactivated: IPV, HepA, HepB, Influenza (injected), Rabies, Pertussis (whole cell), DT/Td, Cholera oral (Shanchol)",st))
story.append(sb("Live vaccines CI in: Immunocompromised, pregnancy, within 3 months of Ig",st))
story.append(b("<b>Cold Chain Requirements</b>",st))
story.append(sb("OPV: -15 to -25°C (freezer); all others: +2 to +8°C (refrigerator)",st))
story.append(sb("Freeze-sensitive: DPT, DT, Td, HepB, IPV, TT — do NOT freeze; discard if frozen",st))
story.append(sb("VVM (Vaccine Vial Monitor): Colour change (inner square lighter than outer = discard)",st))
story.append(sb("Shake test: Distinguish freeze damage — damaged vials aggregate rapidly on shaking",st))
story.append(pyq_box([
    "Vaccine stored at -15 to -25°C: OPV (2020, 2021, 2022, 2023, 2024 — asked every year)",
    "Live vaccine contraindicated in pregnancy: MMR, Varicella, OPV, Yellow fever (2021, 2023)",
    "Vaccine with maximum cold chain requirement: OPV (2022)",
    "BCG vaccine given by: Intradermal route (left deltoid) (2020, 2024)",
    "DPT booster given at age: 16-24 months (B1) and 5-6 years (B2) (2022)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("A child with HIV is due for MMR vaccination. What do you do?","Give MMR if CD4 >15% (or >200 cells/mm3 in children >5y) — live vaccines are generally safe in HIV unless severely immunocompromised. Avoid if CD4 <15%."),
    ("What is the interval between two live vaccines?","Minimum 4 weeks (28 days) if given at different times. Can give simultaneously at different sites. If given <4 weeks apart (other than same day), revaccinate the second one."),
    ("A mother says her child got DPT-1 and developed fever + excessive crying >3h. Next DPT dose?","Precaution for whole-cell pertussis. Switch to acellular pertussis (DTaP) for subsequent doses. Persistent inconsolable crying >3h is a precaution, NOT absolute contraindication."),
],sc["mid"]))
story.append(PageBreak())

# CH 3 — NEONATOLOGY
story.append(chapter_header("CHAPTER 3: NEONATOLOGY (4-5 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("3.1 APGAR SCORE & NRP",sc["mid"],sc["light"]))
story.append(sp(4))
t = std_table(
    ["Sign","Score 0","Score 1","Score 2"],
    [["Appearance (colour)","Blue/pale all over","Pink body, blue extremities","Pink all over"],
     ["Pulse (Heart Rate)","Absent","<100 bpm","≥100 bpm"],
     ["Grimace (Reflex irritability)","No response","Grimace","Cry, cough, sneeze"],
     ["Activity (Muscle tone)","Limp","Some flexion","Active flexion"],
     ["Respiration","Absent","Weak, irregular","Strong cry"],
    ],
    [4*cm,4*cm,4.5*cm,4.5*cm],sc["dark"],sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(sb("Assessed at 1 minute (need for resuscitation) and 5 minutes (response to resuscitation)",st))
story.append(sb("7-10 = Normal; 4-6 = Moderate asphyxia (stimulate, O2); 0-3 = Severe asphyxia (full NRP)",st))
story.append(b("<b>Neonatal Resuscitation (NRP) Steps</b>",st))
story.append(sb("Warm, dry, stimulate → Assess HR, Respirations, Tone → PPV (if apnoeic or HR<100) → Chest compressions (HR<60 after 30s PPV) → Epinephrine IV/IO",st))
story.append(sb("Initial FiO2: Term = 21% (room air); Preterm <35w = 21-30%",st))
story.append(sp(4))
story.append(section_bar("3.2 NEONATAL JAUNDICE",sc["mid"],sc["light"]))
story.append(sp(4))
t = std_table(
    ["Feature","Physiological","Pathological"],
    [["Onset","Day 2-3","<24 hours (ALWAYS pathological)"],
     ["Peak","Day 4-5","Any time"],
     ["Duration","Term: <14 days; Preterm: <21 days","Prolonged or rising after 14 days"],
     ["Max bilirubin","Term: <15 mg/dL; Preterm: <10 mg/dL","Any level causing concern"],
     ["Conjugated bili","<2 mg/dL","If >2 mg/dL = always pathological"],
     ["Cause","Physiological RBC breakdown","Haemolysis, infection, metabolic"],
    ],
    [4*cm,5.5*cm,7.5*cm],sc["dark"],sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(b("<b>Causes of Jaundice by Onset</b>",st))
story.append(sb("<24h: Haemolytic disease (Rh incompatibility, ABO incompatibility, G6PD, spherocytosis), TORCH infections",st))
story.append(sb("Day 2-3: Physiological; ABO incompatibility (can start early)",st))
story.append(sb("Day 4-7: Breast-feeding jaundice (inadequate intake → dehydration → increased enterohepatic circulation)",st))
story.append(sb(">2 weeks: Breast milk jaundice (β-glucuronidase in breast milk deconjugates bilirubin), Hypothyroidism, biliary atresia",st))
story.append(b("<b>Treatment</b>",st))
story.append(sb("Phototherapy: Blue light 450-490nm; distance 30-45cm; undress baby; cover eyes; turn every 2h",st))
story.append(sb("Exchange transfusion: Bilirubin approaching exchange level, or kernicterus signs",st))
story.append(sb("Kernicterus: Bilirubin crosses BBB → basal ganglia damage → hypotonia → hypertonia → opisthotonus → death or CP",st))
story.append(h("Criggler-Najjar type 1: No UDP-glucuronosyltransferase; severe unconjugated hyperbilirubinaemia; phototherapy 18h/day; only cure = liver transplant",st))
story.append(pyq_box([
    "Jaundice appearing <24 hours of birth: Always pathological — most common cause Rh incompatibility (2020, 2022, 2023)",
    "Mechanism of breast milk jaundice: β-glucuronidase in breast milk (2021, 2024)",
    "Phototherapy wavelength: 450-490 nm (blue light) (2021)",
    "Conjugated hyperbilirubinaemia in neonate: Biliary atresia, neonatal hepatitis (2023)",
    "Kernicterus affects: Basal ganglia (globus pallidus, subthalamic nucleus) (2022)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("Neonate born with Rh-incompatibility. Mother Rh-negative, baby Rh-positive. Jaundice at 12 hours. What is the mechanism?","Anti-Rh (anti-D) IgG antibodies from mother cross placenta → attach to fetal Rh+ve RBCs → haemolysis → unconjugated hyperbilirubinaemia. Treat with phototherapy; exchange transfusion if level critical; IVIG can reduce need for exchange."),
    ("How do you prevent Rh isoimmunisation in the next pregnancy?","Anti-D immunoglobulin (Rho-GAM) given to Rh-negative mother within 72 hours of delivery of Rh+ve baby; also at 28 weeks antenatally; after any sensitising event (miscarriage, amniocentesis, bleeding)."),
],sc["mid"]))
story.append(sp(6))
story.append(section_bar("3.3 RESPIRATORY DISTRESS SYNDROME (RDS) & OTHER NEONATAL CONDITIONS",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>RDS (Hyaline Membrane Disease)</b>",st))
story.append(sb("Surfactant deficiency → alveolar collapse → progressive hypoxia; premature infants (inversely related to GA)",st))
story.append(sb("Lecithin:Sphingomyelin (L:S) ratio ≥2 = mature lungs; <2 = immature",st))
story.append(sb("Phosphatidylglycerol (PG) present = mature; absent = immature",st))
story.append(sb("CXR: Diffuse ground-glass + air bronchograms + low lung volumes",st))
story.append(sb("Treatment: Surfactant (Beractant/Poractant α) via ETT; CPAP/HFNC; O2",st))
story.append(sb("Prevention: Antenatal corticosteroids (Betamethasone 12mg IM x2 doses 24h apart) if GA 24-34 weeks",st))
story.append(b("<b>Other Key Neonatal Conditions</b>",st))
t = std_table(
    ["Condition","Cause","Key Feature","Treatment"],
    [["MAS (Meconium aspiration)","Meconium in amniotic fluid → aspiration","Barrel-shaped chest; CXR: hyperinflation + patchy","CPAP/ventilation; no saline lavage (ILCOR 2015)"],
     ["Transient Tachypnoea of Newborn (TTN)","Delayed resorption of lung fluid; term/near-term, C-section","Tachypnoea onset at birth, resolves 24-72h; CXR: wet lungs, fluid in fissures","Supportive; O2; self-limiting"],
     ["Neonatal sepsis","GBS, E.coli, Listeria (early); Staph, Gram-neg (late)","Early (<72h) vs Late (>72h); temperature instability, poor feeding, apnoea","IV Ampicillin + Gentamicin (early); Vancomycin + Cefotaxime (late)"],
     ["HIE","Perinatal asphyxia","Thompson score; Sarnat staging","Therapeutic hypothermia 33-34°C for 72h if ≥36wk GA + within 6h"],
     ["NEC","Premature + formula fed","Bloody stools, abdominal distension; X-ray: pneumatosis intestinalis","NPO + IV Abx + surgical if perforation"],
    ],
    [3.5*cm,4*cm,4.5*cm,5*cm],sc["dark"],sc["light"]
)
story.append(t)
story.append(pyq_box([
    "L:S ratio indicating lung maturity: ≥2 (2020, 2021, 2023)",
    "Drug given antenatally to prevent RDS in premature baby: Betamethasone (2021, 2022, 2024)",
    "X-ray finding in NEC: Pneumatosis intestinalis (gas in bowel wall) (2022)",
    "Therapeutic hypothermia target temperature in HIE: 33-34°C for 72 hours (2023)",
    "Most common organism in early neonatal sepsis: Group B Streptococcus (GBS) (2021)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("An infant born at 30 weeks develops progressive respiratory distress within 4 hours. CXR shows ground-glass with air bronchograms. Diagnosis and treatment?","RDS. Give exogenous surfactant (Poractant alfa) via ETT; start CPAP. Check blood gases. Antenatal betamethasone ideally should have been given to mother."),
    ("What is the Sarnat staging of HIE?","Stage 1 (Mild): Hyperalert, normal tone, no seizures; Stage 2 (Moderate): Lethargic, hypotonia, seizures, abnormal reflexes; Stage 3 (Severe): Coma, flaccid, no reflexes, prolonged seizures. Hypothermia indicated for Stage 2 and 3."),
],sc["mid"]))
story.append(PageBreak())

# CH 4 — NUTRITION
story.append(chapter_header("CHAPTER 4: NUTRITION & MALNUTRITION (2-3 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("4.1 PROTEIN ENERGY MALNUTRITION",sc["mid"],sc["light"]))
story.append(sp(4))
t = std_table(
    ["Feature","Marasmus","Kwashiorkor","Marasmic-Kwashiorkor"],
    [["Primary deficit","Calories (total starvation)","Protein (with adequate calories)","Both calories + protein"],
     ["Age","<1 year typically","1-3 years","Any"],
     ["Oedema","Absent","Present (pitting; face, feet)","Present"],
     ["Wasting","Severe (old man face, loose skin)","May be masked by oedema","Severe wasting + oedema"],
     ["Skin","Wizened, dry","Flaky-paint dermatosis","Mixed features"],
     ["Hair","Sparse, dry","Flag sign, depigmented, easily pluckable","Mixed"],
     ["Liver","Normal","Fatty liver (low albumin)","Fatty"],
     ["Serum albumin","Normal or low","Very low (<2.8g/dL)","Very low"],
     ["Behaviour","Alert, hungry, anxious","Apathetic, irritable, anorexic","Mixed"],
    ],
    [4*cm,4.5*cm,4.5*cm,4*cm],sc["dark"],sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(b("<b>SAM Criteria (WHO)</b>",st))
story.append(sb("MUAC <11.5cm (6-59 months) OR Weight-for-height Z-score <-3 SD OR Bilateral pitting oedema",st))
story.append(sb("MAM: MUAC 11.5-12.5cm OR WHZ -2 to -3",st))
story.append(b("<b>WHO 10-step Protocol for SAM</b>",st))
story.append(sb("Stabilisation phase (F-75, 75 kcal/100mL): Treat hypoglycaemia, hypothermia, dehydration, electrolytes, infections, micronutrients (no iron yet), careful feeding",st))
story.append(sb("Rehabilitation phase (F-100, 100 kcal/100mL): Intensive feeding for catch-up growth; add iron; stimulation",st))
story.append(sb("Rehydration in SAM: Use ReSoMal (low Na, high K, Mg) — NOT standard ORS (risk of hypernatraemia)",st))
story.append(h("Never use high-Na ORS in SAM — risk of fatal hypernatraemia. Use ReSoMal.",st))
story.append(pyq_box([
    "MUAC cut-off for SAM: <11.5 cm (2020, 2021, 2022, 2023)",
    "Flaky-paint dermatosis is seen in: Kwashiorkor (2021, 2024)",
    "Rehydration solution used in SAM: ReSoMal (2022)",
    "Flag sign in hair indicates: Protein deficiency (Kwashiorkor) (2020)",
    "F-75 is used in: Stabilisation phase of SAM (2023)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("Why is standard ORS NOT used in SAM rehydration?","Standard ORS has high sodium (90 mEq/L). SAM children have excess total body Na despite hyponatraemia, and impaired Na-K ATPase function. High Na load → hypernatraemia → cerebral oedema, death. Use ReSoMal (45 mEq/L Na)."),
    ("A 2-year-old has oedema, flaky skin, depigmented hair, fatty liver, and low albumin. Diagnosis and which phase of treatment?","Kwashiorkor. Start stabilisation phase with F-75 formula; treat infections (Amoxicillin), correct electrolytes, do NOT give iron yet (risk of free radical damage). Switch to F-100 when appetite returns."),
],sc["mid"]))
story.append(sp(6))
story.append(section_bar("4.2 VITAMIN DEFICIENCIES",sc["mid"],sc["light"]))
story.append(sp(4))
t = std_table(
    ["Vitamin","Disease","Classic Signs","Treatment"],
    [["A","Xerophthalmia, Night blindness","Bitot spots (conjunctival), corneal ulceration, keratomalacia; follicular hyperkeratosis","Vit A 200,000 IU orally on day 1, day 2, day 14"],
     ["B1 (Thiamine)","Beriberi; Wernicke's encephalopathy","Wet beriberi = cardiac (cardiomegaly, oedema); Dry = peripheral neuropathy; Infantile beriberi","IV Thiamine before glucose (Wernicke's)"],
     ["B2 (Riboflavin)","Ariboflavinosis","Angular stomatitis, cheilosis, glossitis (magenta tongue), corneal vascularisation","Riboflavin supplementation"],
     ["B3 (Niacin)","Pellagra (4 Ds)","Dermatitis (sun-exposed), Diarrhoea, Dementia, Death; Casal's necklace","Nicotinamide / Niacin"],
     ["B12","Megaloblastic anaemia, SACD","Sub-acute combined degeneration of cord (posterior + lateral columns); smooth tongue","IM Hydroxocobalamin"],
     ["C (Ascorbic acid)","Scurvy","Perifollicular haemorrhage, corkscrew hair, Scorbutic rosary, gum bleeding, poor wound healing","Vitamin C 200-500mg/day oral"],
     ["D","Rickets (child), Osteomalacia (adult)","Rachitic rosary, Harrison's sulcus, Bow legs/knock knees, Craniotabes, Looser's zones (adult)","Vitamin D 2000-4000 IU/day"],
     ["K","Haemorrhagic disease of newborn (VKDB)","Prolonged PT/INR; bleeding in neonates","IM Vitamin K 1mg at birth (prophylaxis)"],
    ],
    [2.5*cm,3.5*cm,5.5*cm,5.5*cm],sc["dark"],sc["light"]
)
story.append(t)
story.append(pyq_box([
    "Pellagra 4 Ds: Dermatitis, Diarrhoea, Dementia, Death (2020, 2022, 2023)",
    "Bitot spots seen in deficiency of: Vitamin A (2020, 2021, 2024)",
    "SACD of spinal cord: Vitamin B12 deficiency (2021, 2023)",
    "Prophylaxis for VKDB: IM Vitamin K 1mg at birth (2022)",
    "Looser's zones (pseudofractures) seen in: Osteomalacia / Rickets (2024)",
],sc["mid"],sc["light"]))
story.append(PageBreak())

# CH 5 — PAEDIATRIC INFECTIONS
story.append(chapter_header("CHAPTER 5: PAEDIATRIC INFECTIONS & EXANTHEMS (2-3 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("5.1 EXANTHEMATOUS FEVER COMPARISON",sc["mid"],sc["light"]))
story.append(sp(4))
t = std_table(
    ["Disease","Causative Agent","Rash","Prodrome / Hallmark","Treatment"],
    [["Measles","Paramyxovirus (RNA)","Maculopapular; starts at hairline/face → downward; Day 4 of illness","3 Cs: Cough, Coryza, Conjunctivitis; Koplik spots (pathognomonic — buccal mucosa)","Supportive; Vitamin A (reduces complications)"],
     ["Rubella","Rubivirus (RNA)","Pink maculopapular; face → feet in 3 days; fades quickly","Postauricular/suboccipital lymphadenopathy; Forchheimer spots (soft palate)","Supportive; MMR for prevention"],
     ["Chickenpox","VZV","Vesicular rash — ALL STAGES simultaneously; centripetal (trunk > face > limbs)","Mild fever; intense pruritus; 'Dewdrops on rose petal' vesicles; Tzanck smear: multinucleated giant cells","Acyclovir if immunocompromised/severe; antihistamines for itch"],
     ["Roseola infantum","HHV-6","Pink maculopapular AFTER fever breaks (exanthem subitum)","High fever 3-5 days → fever breaks → rash appears; age 6-18 months","Supportive; self-limiting"],
     ["Erythema infectiosum","Parvovirus B19","'Slapped cheek' redness + lacy reticular rash on trunk/limbs","Aplastic crisis in sickle cell; hydrops fetalis if in pregnancy","Supportive; IVIG for immunocompromised"],
     ["Scarlet fever","Group A Strep (exotoxin)","Diffuse erythema + sandpaper texture; Pastia's lines in skin folds; circumoral pallor","Strawberry tongue; sore throat; follows strep pharyngitis","Penicillin V 10 days"],
     ["Kawasaki disease","Unknown (immune-mediated)","Polymorphous non-vesicular rash","Prolonged fever >5d + 4 of: bilateral conjunctivitis, oral changes, rash, hands/feet changes, cervical LN","IVIG 2g/kg single dose + Aspirin"],
    ],
    [2.5*cm,3*cm,3.5*cm,4.5*cm,3.5*cm],sc["dark"],sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(h("Kawasaki disease complication: Coronary artery aneurysm (15-25% untreated) → ECHO at diagnosis, 6-8 weeks, 6 months",st))
story.append(h("Parvovirus B19 in pregnancy: Hydrops fetalis (severe fetal anaemia); intrauterine transfusion if severe",st))
story.append(pyq_box([
    "Koplik spots are pathognomonic of: Measles (2020, 2021, 2022, 2023)",
    "Rash appears after fever subsides in: Roseola infantum (HHV-6) (2021, 2023)",
    "Treatment of Kawasaki disease: IVIG + Aspirin (2022, 2024)",
    "Tzanck smear positive in: Chickenpox and Herpes simplex (2020)",
    "Complication of Kawasaki not treated: Coronary artery aneurysm (2023, 2024)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("A 3-year-old has fever for 6 days, red eyes, strawberry tongue, swollen hands and rash. Echo shows coronary artery dilatation. Diagnosis and treatment?","Kawasaki disease. Give IVIG 2g/kg as single infusion over 12h + high-dose Aspirin 80-100mg/kg/day until fever-free for 48-72h, then low-dose Aspirin 3-5mg/kg/day for 6-8 weeks. Repeat ECHO at 2 weeks, 6-8 weeks."),
    ("Which childhood fever has a 'slapped cheek' appearance followed by lacy reticular rash?","Erythema infectiosum (Fifth disease) — Parvovirus B19. Important in pregnancy (hydrops fetalis) and sickle cell patients (aplastic crisis due to bone marrow suppression)."),
],sc["mid"]))
story.append(sp(6))

story.append(section_bar("5.2 CONGENITAL HEART DEFECTS",sc["mid"],sc["light"]))
story.append(sp(4))
t = std_table(
    ["CHD","Type","Murmur","Key Feature"],
    [["VSD","L→R shunt (acyanotic)","Pansystolic murmur at LLSB","Most common CHD (32%); Eisenmenger if large"],
     ["ASD","L→R shunt (acyanotic)","Ejection systolic murmur at ULSB + Fixed split S2","Secundum most common; AF in adults"],
     ["PDA","L→R shunt (acyanotic)","Continuous 'machinery' murmur at ULSB","Premature infants; close with Indomethacin; keep open with PGE1"],
     ["ToF","R→L shunt (cyanotic)","Ejection systolic murmur (pulmonary stenosis)","Most common cyanotic CHD; Boot-shaped heart; Tet spells; knee-chest position"],
     ["TGA","R→L (cyanotic)","Variable","Most common cyanotic CHD presenting at birth; egg-on-side heart; PGE1 to maintain PDA; balloon atrial septostomy"],
     ["Coarctation of aorta","Obstructive","Systolic murmur at left infraclavicular","Rib notching; radio-femoral delay; HTN in upper limbs; association with Turner syndrome"],
    ],
    [3*cm,3.5*cm,3.5*cm,7*cm],sc["dark"],sc["light"]
)
story.append(t)
story.append(sp(4))
story.append(h("Eisenmenger syndrome: Reversal of L→R to R→L shunt due to pulmonary HTN → cyanosis. Inoperable.",st))
story.append(h("5 Ts of cyanotic CHD: ToF, TGA, Truncus arteriosus, Tricuspid atresia, Total anomalous pulmonary venous return",st))
story.append(pyq_box([
    "Most common CHD overall: VSD (2020, 2021, 2022, 2023)",
    "Most common cyanotic CHD: Tetralogy of Fallot (ToF) (2020, 2022, 2024)",
    "Boot-shaped heart on CXR: ToF (2021, 2023)",
    "Drug used to close PDA: Indomethacin (NSAID inhibits PG synthesis) (2022)",
    "Drug used to KEEP PDA open: Prostaglandin E1 (PGE1/Alprostadil) (2021)",
    "Continuous machinery murmur: PDA (2020)",
],sc["mid"],sc["light"]))
story.append(sp(8))
footer_t = Table([[Paragraph("Paediatrics Notes Complete — UPSC CMS 2026",ParagraphStyle('ft',fontSize=12,fontName='Helvetica-Bold',textColor=colors.white,alignment=TA_CENTER))]],colWidths=[17*cm])
footer_t.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),colors.HexColor(sc["dark"])),('TOPPADDING',(0,0),(-1,-1),12),('BOTTOMPADDING',(0,0),(-1,-1),12)]))
story.append(footer_t)
doc.build(story)
print("Paediatrics PDF done")

~/upsc-cms-notes/gen_surgery.py

import sys
sys.path.insert(0, '/home/daytona/workspace/upsc-cms-notes')
from pdf_helpers import *
from reportlab.platypus import PageBreak

OUT = "/home/daytona/workspace/upsc-cms-notes/03_Surgery.pdf"
doc = make_doc(OUT)
sc = SUBJECT_COLORS["surgery"]
st = make_styles(sc)
story = []

story += [
    Spacer(1,2.5*cm),
    Paragraph("UPSC CMS 2026",st["cover_title"]),
    Paragraph("SUBJECT 3: SURGERY",ParagraphStyle('x',fontSize=20,textColor=colors.HexColor(sc["mid"]),alignment=TA_CENTER,spaceAfter=8,fontName='Helvetica-Bold')),
    Paragraph("40 Questions | PYQ 2020-2024 Mapped | Examiner-Style Questions",st["cover_sub"]),
    Spacer(1,0.3*cm),
    HRFlowable(width="80%",thickness=2,color=colors.HexColor(sc["dark"]),hAlign='CENTER'),
    Spacer(1,0.3*cm),
    Paragraph("EXAM: 2nd AUGUST 2026",st["cover_date"]),
    Spacer(1,0.8*cm),
]
fd=[["Chapter","Avg Qs/Year","PYQ Frequency"],
    ["Acute Abdomen/GI Surgery","6-8","⭐⭐⭐⭐⭐"],["Trauma & Shock","4-6","⭐⭐⭐⭐⭐"],
    ["Surgical Oncology (Breast/Colorectal)","4-5","⭐⭐⭐⭐"],["Urology","3-4","⭐⭐⭐⭐"],
    ["Orthopaedics","3-4","⭐⭐⭐⭐"],["Wound Healing & Infections","3-4","⭐⭐⭐"],
    ["Vascular Surgery","2-3","⭐⭐⭐"],["Head/Neck & ENT","2-3","⭐⭐⭐"],["Anaesthesia","1-2","⭐⭐"]]
story.append(std_table(fd[0],fd[1:],[6*cm,5*cm,6*cm],sc["dark"],sc["light"]))
story.append(PageBreak())

# CH1 ACUTE ABDOMEN
story.append(chapter_header("CHAPTER 1: ACUTE ABDOMEN & GI SURGERY (6-8 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("1.1 APPENDICITIS",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Alvarado Score (MANTRELS)</b>",st))
t=std_table(["Parameter","Points"],
    [["Migration of pain to RIF","1"],["Anorexia","1"],["Nausea/Vomiting","1"],
     ["RIF tenderness","2"],["Rebound tenderness","1"],["Elevated temperature (>37.3°C)","1"],
     ["Leucocytosis (WBC>10,000)","2"],["Left shift (neutrophilia)","1"],["TOTAL","10"]],
    [10*cm,7*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(sb("Score <5 = unlikely; 5-6 = possible (observe); 7-8 = likely; ≥9 = definite appendicitis",st))
story.append(b("<b>Signs</b>",st))
story.append(sb("McBurney's point: 1/3 distance from ASIS to umbilicus",st))
story.append(sb("Rovsing's sign: Pressure in LIF causes pain in RIF (peritoneal irritation)",st))
story.append(sb("Psoas sign: Pain on extending right hip (retrocaecal appendix)",st))
story.append(sb("Obturator sign: Pain on internal rotation of flexed right hip (pelvic appendix)",st))
story.append(sb("Most common position of appendix: Retrocaecal (65-70%)",st))
story.append(h("Appendix is most commonly retrocaecal — hence pain may not be classic in RIF",st))
story.append(pyq_box([
    "Most common position of appendix: Retrocaecal (2020, 2021, 2022)",
    "Rovsing's sign is positive in: Appendicitis (2023)",
    "Alvarado score for definite appendicitis: ≥7 (2022, 2024)",
    "Investigation of choice in suspected appendicitis in children/pregnancy: Ultrasound (2020)",
    "Psoas sign indicates: Retrocaecal appendix (2021)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("A pregnant woman (28 weeks) has RIF pain. What is the investigation of choice?","Ultrasound (first line; no radiation). MRI if USS inconclusive. Avoid CT in pregnancy if possible. Note: In pregnancy, appendix migrates upward with uterus — pain may be in right flank/hypochondrium."),
    ("What is an Amyand's hernia?","Appendix inside an inguinal hernia sac. Rare. If appendix is normal, return it; if inflamed, appendicectomy + hernia repair."),
],sc["mid"]))
story.append(sp(6))

story.append(section_bar("1.2 INTESTINAL OBSTRUCTION",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Feature","Small Bowel Obstruction","Large Bowel Obstruction"],
    [["Pain","Colicky, central","Colicky, lower abdomen"],
     ["Vomiting","Early, profuse","Late, faeculent"],
     ["Distension","Central (valvulae conniventes)","Peripheral (haustra)"],
     ["X-ray","Ladder pattern; valvulae cross entire lumen","Peripheral; haustra don't cross entire lumen"],
     ["Common causes","Adhesions (post-op, most common), hernias","Carcinoma colon (most common), volvulus, diverticular"],
    ],
    [4*cm,6.5*cm,6.5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(h("Sigmoid volvulus: Coffee-bean sign on AXR; Flexible sigmoidoscopy decompression first",st))
story.append(h("Caecal volvulus: Comma/kidney-shaped on AXR; needs surgical fixation",st))
story.append(b("<b>Hernia Types</b>",st))
t=std_table(["Hernia","Definition","Special Feature"],
    [["Indirect inguinal","Through deep inguinal ring → lateral to inf epigastric vessels","Most common hernia overall (both sexes); enters scrotum"],
     ["Direct inguinal","Through Hesselbach's triangle (medial to inf epigastric)","Rarely strangulates; elderly males; not into scrotum"],
     ["Femoral","Through femoral canal; below & lateral to pubic tubercle","Most common in females; high strangulation risk"],
     ["Richter's hernia","Only part of bowel wall (antimesenteric) in sac","Strangulation without obstruction; easy to miss"],
     ["Maydl's hernia","W-shaped double loop in sac","Middle loop most at risk of strangulation"],
     ["Littre's hernia","Meckel's diverticulum in hernia sac",""],
    ],
    [3.5*cm,6.5*cm,7*cm],sc["dark"],sc["light"])
story.append(t)
story.append(pyq_box([
    "Most common cause of SBO in adults: Adhesions (post-op) (2020, 2021, 2023)",
    "Coffee-bean sign on AXR: Sigmoid volvulus (2022, 2024)",
    "Hernia with highest strangulation risk: Femoral (2021, 2022)",
    "Hernia that can strangulate without obstruction: Richter's hernia (2020, 2023)",
    "Most common hernia in females: Still indirect inguinal (overall), but femoral is proportionally more common in females vs males (2024)",
],sc["mid"],sc["light"]))
story.append(sp(6))

story.append(section_bar("1.3 PANCREAS & LIVER",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Acute Pancreatitis</b>",st))
story.append(sb("Most common causes: Gallstones (55%), Alcohol (35%), others (ERCP, drugs, hypertriglyceridaemia, trauma)",st))
story.append(sb("Serum amylase >3x upper limit = diagnostic; Lipase more specific and stays elevated longer",st))
story.append(sb("Ranson's criteria: ≥3 = severe pancreatitis (high mortality)",st))
story.append(sb("Atlanta classification (2012): Mild (no organ failure, no local complications), Moderately severe (transient organ failure <48h or local complications), Severe (persistent organ failure >48h)",st))
story.append(sb("Complications: Pseudocyst, abscess, necrosis, haemorrhage",st))
story.append(sb("Grey Turner sign = flank bruising; Cullen sign = periumbilical bruising → haemorrhagic pancreatitis",st))
story.append(h("Courvoisier's law: Painless jaundice + palpable non-tender GB = Ca head of pancreas (NOT gallstones)",st))
story.append(b("<b>Liver Abscesses</b>",st))
t=std_table(["Type","Organism","Location","Features","Treatment"],
    [["Amoebic","Entamoeba histolytica","Right lobe (70%), solitary","Anchovy sauce aspirate; serological test +ve","Metronidazole; aspiration if large/no response"],
     ["Pyogenic","E.coli, Klebsiella, Staph","Any, can be multiple","Septicaemia; source from biliary/portal","IV antibiotics + drainage"],
    ],
    [2.5*cm,4*cm,3*cm,4*cm,3.5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(pyq_box([
    "Most common cause of acute pancreatitis in India: Gallstones (2020, 2022, 2023)",
    "Most specific enzyme for pancreatitis: Lipase (2021, 2024)",
    "Grey Turner sign is seen in: Haemorrhagic pancreatitis (2021)",
    "Amoebic liver abscess aspirate: Anchovy sauce / chocolate-coloured fluid (2020, 2022)",
    "Courvoisier's law exception: Gallstones usually cause fibrosis of GB wall (doesn't distend) (2023)",
],sc["mid"],sc["light"]))
story.append(PageBreak())

# CH2 TRAUMA
story.append(chapter_header("CHAPTER 2: TRAUMA, SHOCK & HEAD INJURY (4-6 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("2.1 ATLS HAEMORRHAGIC SHOCK CLASSIFICATION",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Class","Blood loss","% Blood vol","HR","BP","RR","Urine output","Mental status"],
    [["I","<750mL","<15%","<100","Normal","14-20","≥30 mL/h","Normal/slightly anxious"],
     ["II","750-1500mL","15-30%","100-120","Normal","20-30","20-30 mL/h","Mildly anxious"],
     ["III","1500-2000mL","30-40%","120-140","Decreased","30-40","5-15 mL/h","Confused, anxious"],
     ["IV",">2000mL",">40%",">140","Very low",">35","<5 mL/h","Confused, lethargic"],
    ],
    [1.5*cm,2.5*cm,2.5*cm,2.5*cm,2.5*cm,2*cm,3*cm,3*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(b("<b>Damage Control Resuscitation (DCR)</b>",st))
story.append(sb("Permissive hypotension: SBP 80-90 mmHg until haemorrhage controlled (except TBI)",st))
story.append(sb("Haemostatic resuscitation: pRBC:FFP:Platelets in 1:1:1 ratio",st))
story.append(sb("Tranexamic acid: Within 3 hours of injury (CRASH-2 trial); reduces mortality",st))
story.append(sp(6))
story.append(section_bar("2.2 HEAD INJURY",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Glasgow Coma Scale (GCS)</b>",st))
t=std_table(["Component","Score","Response"],
    [["Eye opening (E)","4","Spontaneous"],["","3","To voice"],["","2","To pain"],["","1","None"],
     ["Verbal (V)","5","Oriented"],["","4","Confused"],["","3","Inappropriate words"],["","2","Sounds"],["","1","None"],
     ["Motor (M)","6","Obeys commands"],["","5","Localises pain"],["","4","Withdrawal"],["","3","Flexion (decorticate)"],["","2","Extension (decerebrate)"],["","1","None"],
    ],
    [5*cm,3*cm,9*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(sb("GCS ≥13 = Mild TBI; 9-12 = Moderate; ≤8 = Severe (intubate)",st))
story.append(b("<b>Intracranial Haemorrhage Comparison</b>",st))
t=std_table(["Feature","Extradural (EDH)","Subdural (SDH)","Subarachnoid (SAH)"],
    [["Vessel","Middle meningeal artery","Bridging veins","Berry aneurysm (usually)"],
     ["Lucid interval","Classic (30-40%)","Absent (acute); may have in chronic","Absent"],
     ["CT shape","Biconvex (lenticular)","Crescent (concave inner)","Blood in basal cisterns/subarachnoid space"],
     ["Clinical","Young trauma + temporal fracture","Elderly, alcoholic, minor trauma","Thunderclap headache ('worst headache ever')"],
     ["Treatment","Emergency craniotomy","Burr holes/craniotomy; mild = conservative","Nimodipine to prevent vasospasm; coil/clip aneurysm"],
    ],
    [3.5*cm,4.5*cm,4.5*cm,4.5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(h("Cushing's triad: Hypertension + Bradycardia + Irregular respiration = critically raised ICP → herniation imminent",st))
story.append(h("Xanthochromia in CSF: Seen ≥2h after SAH (up to 2 weeks); distinguishes SAH from traumatic tap",st))
story.append(pyq_box([
    "Extradural haematoma: Biconvex shape CT; middle meningeal artery (repeated 2020-2024)",
    "Lucid interval associated with: EDH (2020, 2021, 2022, 2023)",
    "GCS for severe TBI: ≤8 (2021)",
    "Thunderclap headache: SAH (2022, 2024)",
    "Drug to prevent vasospasm in SAH: Nimodipine (calcium channel blocker) (2021, 2023)",
    "Xanthochromia seen in LP after SAH: ≥2 hours (2022)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("A young man is in RTA. CT shows biconvex hyperdense collection at temporal region. HR 50, BP 200/100, irregular breathing. What is the immediate management?","EDH with Cushing's triad (raised ICP). Emergency burr hole/craniotomy. IV Mannitol 1g/kg to reduce ICP while preparing for OT. Hyperventilate (PCO2 35-40 mmHg). Aim ICP <20 mmHg."),
    ("What is the Hunt and Hess grading used for?","Clinical grading of subarachnoid haemorrhage severity: Grade 1 = minimal headache; Grade 5 = deep coma, decerebrate. Higher grade = worse prognosis. Used to guide timing of surgical intervention."),
],sc["mid"]))
story.append(PageBreak())

# CH3 ONCOLOGY
story.append(chapter_header("CHAPTER 3: SURGICAL ONCOLOGY (4-5 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("3.1 BREAST CANCER",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Risk Factors & Genetics</b>",st))
story.append(sb("BRCA1 (Chr 17): Breast + ovarian cancer risk; triple-negative breast cancer",st))
story.append(sb("BRCA2 (Chr 13): Breast + ovarian + male breast cancer; also pancreatic, prostate",st))
story.append(sb("Risk factors: Early menarche, late menopause, nulliparity, late 1st pregnancy, OCP, HRT, obesity, alcohol",st))
story.append(b("<b>Triple Assessment</b>",st))
story.append(sb("1. Clinical examination; 2. Imaging (USS <35y; mammography ≥35y); 3. FNAC/Core biopsy",st))
story.append(b("<b>Pathological Types</b>",st))
story.append(sb("Invasive ductal carcinoma (IDC): Most common (70%); hard scirrhous texture",st))
story.append(sb("Invasive lobular: Second most common; Indian file pattern; bilateral more common",st))
story.append(sb("Paget's disease of nipple: Eczematoid change → underlying DCIS or invasive carcinoma",st))
story.append(sb("Inflammatory breast cancer: Skin oedema (peau d'orange), erythema, warmth; dermal lymphatic invasion",st))
story.append(b("<b>Management</b>",st))
t=std_table(["Receptor Status","Drug"],
    [["ER/PR positive (luminal A)","Tamoxifen (premenopausal) | Aromatase inhibitors: Letrozole, Anastrozole (postmenopausal)"],
     ["HER2 positive","Trastuzumab (Herceptin) ± Pertuzumab | Lapatinib (TKI)"],
     ["Triple negative (ER-,PR-,HER2-)","Chemotherapy only; platinum-based if BRCA mutation"],
    ],
    [4*cm,13*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(h("Sentinel lymph node biopsy (SLNB): Technetium-99m + patent blue dye; avoids axillary clearance if node negative",st))
story.append(pyq_box([
    "Most common type of breast cancer: Invasive ductal carcinoma (2020, 2021, 2022, 2023, 2024)",
    "Drug for ER+ve postmenopausal breast cancer: Aromatase inhibitor (Letrozole/Anastrozole) (2021, 2023)",
    "Paget's disease of nipple associated with: DCIS / invasive ductal carcinoma (2022)",
    "BRCA1 mutation associated cancer: Breast + Ovarian (triple negative subtype) (2020, 2024)",
    "Marker used to monitor breast cancer treatment: CA 15-3 (2022)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("A 45-year-old woman has a hard lump in breast with skin dimpling and bloody nipple discharge. Triple assessment findings: irregular spiculated mass on USS + malignant cells on core biopsy. Next step?","Stage with CT CAP ± bone scan. ER/PR/HER2 status on biopsy. Multidisciplinary team decision: surgery (wide local excision or mastectomy) + sentinel LN biopsy + adjuvant therapy based on receptor status."),
    ("Why is tamoxifen used in premenopausal but aromatase inhibitors in postmenopausal breast cancer?","Premenopausal: Main oestrogen source = ovaries. Aromatase inhibitors would not fully suppress ovarian oestrogen production. Tamoxifen blocks ER directly. Postmenopausal: Oestrogen made by peripheral aromatisation of androgens in fat — aromatase inhibitors effectively block this."),
],sc["mid"]))
story.append(sp(6))

story.append(section_bar("3.2 COLORECTAL CANCER + THYROID SURGERY",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Colorectal Cancer (CRC)</b>",st))
story.append(sb("FAP (Familial Adenomatous Polyposis): APC gene (Chr 5q21); >100 polyps; 100% CRC risk by 40y",st))
story.append(sb("Lynch syndrome (HNPCC): MLH1, MSH2, MSH6 — mismatch repair genes; right-sided CRC; Amsterdam II criteria",st))
story.append(sb("Dukes staging: A=mucosa/submucosa; B=through muscularis (no LN); C=LN positive; D=distant mets",st))
story.append(sb("CEA: Monitoring recurrence NOT diagnosis; elevated in smokers (normal <2.5 ng/mL in non-smokers)",st))
story.append(sb("Left-sided: Obstruction (apple-core lesion); Right-sided: Occult bleeding, anaemia",st))
story.append(b("<b>Thyroid Surgery</b>",st))
story.append(sb("Complications of thyroidectomy: Hypocalcaemia (parathyroid removal/damage), RLN injury (hoarseness), haematoma (life-threatening — reopen wound)",st))
story.append(sb("RLN (Recurrent Laryngeal Nerve) anatomy: Right RLN loops around subclavian; Left loops around arch of aorta",st))
story.append(sb("Post-thyroidectomy hypocalcaemia: Carpopedal spasm; Trousseau sign; Chvostek sign; IV Calcium gluconate",st))
story.append(pyq_box([
    "FAP gene mutation: APC gene on chromosome 5 (2020, 2022)",
    "Lynch syndrome gene: MLH1, MSH2 (mismatch repair) (2021, 2023)",
    "Apple-core lesion on barium enema: Carcinoma colon (2022)",
    "Post-thyroidectomy complication causing stridor: Bilateral RLN palsy (2021)",
    "Immediate complication after thyroidectomy threatening airway: Haematoma (2024)",
    "Dukes C colorectal cancer: LN positive (2020)",
],sc["mid"],sc["light"]))
story.append(PageBreak())

# CH4 UROLOGY
story.append(chapter_header("CHAPTER 4: UROLOGY (3-4 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("4.1 URINARY CALCULI, BPH, CARCINOMA",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Stone type","Composition","Radiodensity","Predisposing condition"],
    [["Calcium oxalate","CaOx monohydrate/dihydrate","Radiopaque (most dense)","Hypercalciuria, hyperoxaluria, low urine volume; most common (80%)"],
     ["Struvite","Mg NH4 PO4 (triple phosphate)","Radiopaque; staghorn","Urease-producing organisms (Proteus, Klebsiella, Pseudomonas)"],
     ["Uric acid","Urate","RADIOLUCENT (not seen on plain X-ray)","Gout, hyperuricaemia, acidic urine; treat: alkalinise urine"],
     ["Cystine","Cystine","Faintly radiopaque (ground glass)","Cystinuria (AR); hexagonal crystals on urine microscopy"],
    ],
    [2.5*cm,4*cm,3.5*cm,7*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(b("<b>Management by Stone Size</b>",st))
story.append(sb("<4mm: 95% pass spontaneously; analgesia (Diclofenac), hydration",st))
story.append(sb("4-10mm: Alpha-blockers (Tamsulosin) — medical expulsive therapy; analgesia",st))
story.append(sb(">10mm (renal) or >5mm (ureteric, failed MET): ESWL or Ureteroscopy (URS) or PCNL",st))
story.append(sb("Staghorn calculus (>2cm): PCNL (Percutaneous Nephrolithotomy) — gold standard",st))
story.append(b("<b>BPH</b>",st))
story.append(sb("IPSS score: 0-7 mild; 8-19 moderate; 20-35 severe",st))
story.append(sb("Medical: Alpha-1 blockers (Tamsulosin — relaxes smooth muscle; quickest symptom relief)",st))
story.append(sb("5-alpha reductase inhibitors (Finasteride, Dutasteride): Shrinks prostate; takes 6 months; lowers PSA by 50%",st))
story.append(sb("Surgery: TURP (gold standard); complication = retrograde ejaculation (most common post-TURP)",st))
story.append(pyq_box([
    "Radiolucent renal stone: Uric acid (2020, 2021, 2022, 2023, 2024 — EVERY YEAR)",
    "Stone associated with staghorn calculus: Struvite/triple phosphate (2020, 2022)",
    "Medical expulsive therapy for ureteric stone: Alpha-blocker (Tamsulosin) (2021, 2023)",
    "TURP most common complication: Retrograde ejaculation (2021)",
    "Treatment of large staghorn calculus: PCNL (2022, 2024)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("A patient has a 6mm ureteric stone at VUJ (vesicoureteric junction). No infection, creatinine normal. What is the first-line management?","Medical expulsive therapy (MET): Tamsulosin 0.4mg OD + adequate analgesia (Diclofenac). Follow up with KUB X-ray or USS. If not passed in 4 weeks or develops complications → URS (ureteroscopy)."),
    ("PSA level and BPH — can PSA be used to diagnose prostate cancer?","PSA is not specific — elevated in BPH, prostatitis, UTI, post-catheterisation. PSA density, PSA velocity, and free:total PSA ratio improve specificity. Biopsy (TRUS-guided) is needed for diagnosis. MRI first (mpMRI) to detect significant cancer."),
],sc["mid"]))
story.append(sp(6))

story.append(section_bar("4.2 ORTHOPAEDICS (3-4 Qs/Year)",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Fractures — High-Yield</b>",st))
t=std_table(["Fracture","Key Feature","Complication"],
    [["Colles' fracture","Dorsal displacement/angulation of distal radius; fall on outstretched hand","Malunion (dinner-fork deformity), carpal tunnel syndrome"],
     ["Scaphoid fracture","Anatomical snuffbox tenderness; young adults","Avascular necrosis (proximal pole — watershed zone)"],
     ["Neck of femur","Shortened externally rotated limb; elderly osteoporotic","AVN of femoral head (blood supply: retinacular vessels)"],
     ["Supracondylar humerus","Children 5-7y; extension type (posterior displacement)","Anterior interosseous nerve (AIN) injury; Volkmann's ischaemia"],
     ["Monteggia fracture","Ulna fracture + radial head dislocation","Radial nerve (PIN — posterior interosseous nerve) injury"],
     ["Galeazzi fracture","Radius fracture + DRUJ dislocation","Ulnar nerve injury"],
    ],
    [3.5*cm,5.5*cm,8*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(h("Volkmann's ischaemic contracture: Untreated compartment syndrome → muscle necrosis → fibrosis → flexion deformity of wrist/fingers",st))
story.append(h("Compartment syndrome: 6 Ps: Pain (disproportionate, on passive stretch), Pressure, Pallor, Pulselessness, Paraesthesia, Paralysis",st))
story.append(pyq_box([
    "Fracture with most risk of AVN: Scaphoid (proximal pole) and Neck of femur (2020, 2021, 2022)",
    "Complication of supracondylar fracture: Anterior interosseous nerve + Volkmann's contracture (2021, 2023)",
    "Dinner-fork deformity: Colles' fracture (2020, 2022)",
    "Nerve injured in Monteggia fracture: PIN (Posterior Interosseous Nerve — branch of radial nerve) (2022, 2024)",
    "Treatment for compartment syndrome: Emergency fasciotomy (2021)",
],sc["mid"],sc["light"]))
story.append(sp(8))
footer_t=Table([[Paragraph("Surgery Notes Complete — UPSC CMS 2026",ParagraphStyle('ft',fontSize=12,fontName='Helvetica-Bold',textColor=colors.white,alignment=TA_CENTER))]],colWidths=[17*cm])
footer_t.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),colors.HexColor(sc["dark"])),('TOPPADDING',(0,0),(-1,-1),12),('BOTTOMPADDING',(0,0),(-1,-1),12)]))
story.append(footer_t)
doc.build(story)
print("Surgery PDF done")

~/upsc-cms-notes/gen_obsgyn.py

import sys
sys.path.insert(0, '/home/daytona/workspace/upsc-cms-notes')
from pdf_helpers import *
from reportlab.platypus import PageBreak

OUT = "/home/daytona/workspace/upsc-cms-notes/04_ObsGyn.pdf"
doc = make_doc(OUT)
sc = SUBJECT_COLORS["obsgyn"]
st = make_styles(sc)
story = []

story += [
    Spacer(1,2.5*cm),
    Paragraph("UPSC CMS 2026",st["cover_title"]),
    Paragraph("SUBJECT 4: GYNAECOLOGY & OBSTETRICS",ParagraphStyle('x',fontSize=18,textColor=colors.HexColor(sc["mid"]),alignment=TA_CENTER,spaceAfter=8,fontName='Helvetica-Bold')),
    Paragraph("40 Questions | PYQ 2020-2024 Mapped | Examiner-Style Questions",st["cover_sub"]),
    Spacer(1,0.3*cm),
    HRFlowable(width="80%",thickness=2,color=colors.HexColor(sc["dark"]),hAlign='CENTER'),
    Spacer(1,0.3*cm),
    Paragraph("EXAM: 2nd AUGUST 2026",st["cover_date"]),
    Spacer(1,0.8*cm),
]
fd=[["Chapter","Avg Qs/Year","PYQ Frequency"],
    ["Obstetrics: HTN disorders / APH / PPH","6-8","⭐⭐⭐⭐⭐"],
    ["Normal Obstetrics / Labour","4-5","⭐⭐⭐⭐"],
    ["Gynaecological oncology","4-5","⭐⭐⭐⭐⭐"],
    ["Benign gynaecology (Fibroids, Endo, PCOS)","4-5","⭐⭐⭐⭐"],
    ["Ante-natal care / Abnormal pregnancy","3-4","⭐⭐⭐⭐"],
    ["Family planning / MTP","2-3","⭐⭐⭐"],
    ["Infections in genital tract","2-3","⭐⭐⭐"],
]
story.append(std_table(fd[0],fd[1:],[7*cm,4*cm,6*cm],sc["dark"],sc["light"]))
story.append(PageBreak())

# OBSTETRICS
story.append(chapter_header("CHAPTER 1: OBSTETRICS — HTN DISORDERS (6-8 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("1.1 PRE-ECLAMPSIA & ECLAMPSIA",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Definitions</b>",st))
story.append(sb("Gestational HTN: BP ≥140/90 after 20 weeks; NO proteinuria; NO features of pre-eclampsia",st))
story.append(sb("Pre-eclampsia: BP ≥140/90 after 20 weeks + proteinuria (≥300mg/24h or PCR ≥30mg/mmol) OR any severe feature",st))
story.append(sb("Severe features: BP ≥160/110 OR headache/visual disturbance/epigastric pain/oliguria/IUGR/thrombocytopenia <100,000/elevated LFTs",st))
story.append(sb("Eclampsia: Convulsions in a pre-eclamptic patient (not explained by another cause)",st))
story.append(sb("HELLP: Haemolysis + Elevated Liver enzymes (AST/ALT) + Low Platelets (<100,000)",st))
story.append(b("<b>Magnesium Sulphate (MgSO4) Protocol — Very High Yield</b>",st))
story.append(sb("Regimen (Pritchard): Loading 4g IV over 20 min + 10g IM (5g each buttock) → Maintenance 5g IM every 4h",st))
story.append(sb("IV regimen: Loading 4g over 20 min → maintenance 1-2g/h IV infusion",st))
story.append(sb("Monitoring: Patellar reflex (loss = first sign of toxicity), RR >12/min, Urine output >25mL/h, SpO2",st))
story.append(sb("MgSO4 toxicity signs: Loss of patellar reflex (Mg 7-10 mEq/L) → Respiratory depression (>10) → Cardiac arrest (>15)",st))
story.append(sb("Antidote: Calcium gluconate 10mL of 10% solution IV slowly",st))
story.append(h("Definitive treatment of pre-eclampsia/eclampsia = DELIVERY (regardless of gestation if severe)",st))
story.append(b("<b>Antihypertensive in Pregnancy</b>",st))
t=std_table(["Situation","Drug of Choice"],
    [["Acute severe HTN (BP ≥160/110)","IV Labetalol (first line) OR Oral Nifedipine (immediate release) OR IV Hydralazine"],
     ["Chronic HTN maintenance in pregnancy","Methyldopa (safest; most data) OR Labetalol OR Nifedipine (slow release)"],
     ["AVOID in pregnancy","ACEi/ARB (teratogenic — oligohydramnios, renal dysplasia, skull defects); Atenolol (IUGR)"],
    ],
    [5*cm,12*cm],sc["dark"],sc["light"])
story.append(t)
story.append(pyq_box([
    "MgSO4 first sign of toxicity: Loss of patellar reflex (2020, 2021, 2022, 2023, 2024 — EVERY YEAR)",
    "Antidote of MgSO4 toxicity: Calcium gluconate (repeated every year)",
    "Pre-eclampsia definition: BP ≥140/90 after 20 weeks + proteinuria (2020, 2021, 2022)",
    "HELLP syndrome triad: Haemolysis + Elevated LFTs + Low Platelets (2021, 2023)",
    "Drug contraindicated for HTN in pregnancy: ACEi/ARB (2020, 2022, 2024)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("A primigravida at 36 weeks has BP 170/110, headache, proteinuria +++. MgSO4 loading dose has been given. She still has a seizure. What next?","Give further 2g MgSO4 IV slowly. If seizures continue → Diazepam/Lorazepam. Ensure airway (lateral position, O2). Deliver baby after stabilisation. Check FHR throughout."),
    ("Why is MgSO4 superior to Diazepam/Phenytoin in eclampsia?","MgSO4 (MAGPIE trial): Reduces risk of eclampsia by 58% in severe pre-eclampsia; reduces maternal mortality; fewer maternal/neonatal adverse effects compared to Diazepam (respiratory depression) and Phenytoin (no proven fetal safety, cardiac arrhythmia risk)."),
],sc["mid"]))
story.append(sp(6))

story.append(section_bar("1.2 ANTEPARTUM HAEMORRHAGE (APH)",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Feature","Placenta Praevia","Placental Abruption"],
    [["Pain","PAINLESS bright red bleeding","PAINFUL, constant (board-like uterus)"],
     ["Onset","Often spontaneous, after 28 weeks","After trauma, PIH; any time after 20w"],
     ["Bleeding","Always revealed; recurrent warnings","May be concealed (most dangerous); revealed or mixed"],
     ["Uterus","Soft, non-tender; malpresentation common","Woody-hard, tender; hypertonic"],
     ["Fetal heart","Usually normal","Distressed or absent (fetal mortality 30%)"],
     ["Diagnosis","TVS (transvaginal USS) — gold standard; DO NOT do PV","Clinical primarily; USS may not show retroplacental clot"],
     ["Management","Stabilise; steroids if <34w; CS if grade III/IV; expectant if minor","Mild: conservative + monitor; Severe: emergency CS + blood products"],
    ],
    [3.5*cm,6.5*cm,7*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(h("NEVER do vaginal examination in placenta praevia — risk of catastrophic haemorrhage",st))
story.append(h("Placenta praevia grading: Grade I=placenta in lower segment (away from os); Grade II=reaches os; Grade III=covers os partially; Grade IV=complete/central praevia",st))
story.append(sp(6))

story.append(section_bar("1.3 POSTPARTUM HAEMORRHAGE (PPH)",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Definition & Causes</b>",st))
story.append(sb("Primary PPH: ≥500mL blood loss within 24h of vaginal delivery; ≥1000mL after CS",st))
story.append(sb("Secondary PPH: Abnormal bleeding between 24h and 12 weeks postpartum",st))
story.append(b("<b>4 Ts of PPH Causes</b>",st))
t=std_table(["Cause","Frequency","Examples","Management"],
    [["TONE (Atony)","70-80%","Uterine atony — uterus not contracting","Uterine massage → Oxytocin → Ergometrine → Carboprost (PGF2α) → Misoprostol → Bakri balloon → B-Lynch suture → Hysterectomy"],
     ["TISSUE","10%","Retained placenta/membranes","Manual removal of placenta; USS guided curettage"],
     ["TRAUMA","10%","Perineal tears, vaginal lacerations, uterine rupture","Repair; examination under anaesthesia"],
     ["THROMBIN","1-2%","Coagulopathy (DIC, ITP, von Willebrand)","FFP, platelets, cryoprecipitate, tranexamic acid"],
    ],
    [2.5*cm,3*cm,5*cm,6.5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(h("Active management of 3rd stage (AMTSL): Oxytocin 10 IU IM within 1 min of delivery + controlled cord traction + uterine massage = most important intervention to prevent PPH",st))
story.append(h("Ergometrine contraindicated in: HTN, cardiac disease, asthma",st))
story.append(h("Carboprost (PGF2α) contraindicated in: Asthma",st))
story.append(pyq_box([
    "Most common cause of PPH: Uterine atony (2020, 2021, 2022, 2023, 2024)",
    "Active management of 3rd stage of labour includes: Oxytocin 10 IU IM (2020, 2021, 2023)",
    "Drug contraindicated in PPH management (asthma): Carboprost/Ergometrine (2022)",
    "Blood loss definition for PPH after CS: ≥1000 mL (2022, 2024)",
    "B-Lynch suture is used for: Uterine atony (compression suture) (2021)",
],sc["mid"],sc["light"]))
story.append(PageBreak())

# GYNAECOLOGY
story.append(chapter_header("CHAPTER 2: GYNAECOLOGICAL ONCOLOGY (4-5 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("2.1 CERVICAL CANCER",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>HPV & Cervical Dysplasia</b>",st))
story.append(sb("High-risk HPV (cancer): 16, 18 (70% of cervical cancers), 31, 33, 45",st))
story.append(sb("Low-risk HPV (warts): 6, 11 (condylomata acuminata)",st))
story.append(sb("CIN grading: CIN 1 = mild dysplasia; CIN 2 = moderate; CIN 3 = severe/CIS (full thickness)",st))
story.append(sb("CIN 1: Observe/colposcopy; CIN 2-3: LLETZ (Large Loop Excision of TZ) — gold standard treatment",st))
story.append(sb("Bethesda system: ASC-US → HPV reflex testing; LSIL → colposcopy; HSIL → colposcopy/LLETZ",st))
story.append(b("<b>Staging (FIGO 2018) & Treatment</b>",st))
t=std_table(["Stage","Description","Treatment"],
    [["IA1 (<3mm invasion)","Microinvasive","Conisation (if fertility desired) or Simple hysterectomy"],
     ["IA2 (3-5mm)","Microinvasive","Modified radical hysterectomy OR Cone + pelvic LN sampling"],
     ["IB-IIA (<4cm)","Confined to cervix/upper vagina","Wertheim's radical hysterectomy + pelvic LND OR Chemoradiation (equally effective)"],
     ["IIB and above","Parametrial involvement or beyond","Concurrent chemoradiation (Cisplatin-based) — INOPERABLE"],
     ["IVB","Distant metastases","Palliative chemotherapy"],
    ],
    [3.5*cm,5*cm,8.5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(h("Wertheim's hysterectomy: Total hysterectomy + upper 1/3 vagina + parametria + pelvic LN dissection",st))
story.append(pyq_box([
    "Most common type of cervical cancer: Squamous cell carcinoma (80%) (2020, 2021, 2023)",
    "HPV strains causing cervical cancer: HPV 16 and 18 (2020, 2022, 2024)",
    "Treatment of CIN 2-3: LLETZ/LEEP (2021, 2023)",
    "Inoperable cervical cancer (from stage): IIB onwards (parametrial involvement) (2022, 2024)",
    "Wertheim's hysterectomy for: Stage IB-IIA cervical cancer (2021)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("A 35-year-old woman has Pap smear showing HSIL. Colposcopy shows CIN 3. What is the management?","LLETZ (Large Loop Excision of Transformation Zone) — diagnostic and therapeutic. Send specimen for histology. Follow up with Pap smear/HPV test at 6 and 12 months. If margins clear and no invasion, no further surgery needed."),
    ("HPV vaccination — what types does it cover and when is it given?","Cervarix (bivalent): HPV 16,18. Gardasil-4 (quadrivalent): 16,18,6,11. Gardasil-9: Above + 5 more. India NIS (2023): Gardasil-4 for girls 9-14 years; 2 doses (0 and 6 months). Most effective before sexual debut."),
],sc["mid"]))
story.append(sp(6))

story.append(section_bar("2.2 OVARIAN & UTERINE CANCER",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Tumour","Type","Marker","Special Feature"],
    [["Serous cystadenocarcinoma","Malignant, epithelial","CA-125","Most common malignant ovarian tumour; bilateral; psammoma bodies"],
     ["Serous cystadenoma","Benign, epithelial","CA-125","Most common benign ovarian tumour overall; bilateral"],
     ["Mucinous cystadenoma","Benign, epithelial","CA 19-9","Largest abdominal tumours; pseudomyxoma peritonei if ruptures"],
     ["Dermoid cyst (Mature teratoma)","Benign, germ cell","Alpha-FP, βHCG if immature","Most common ovarian tumour in young women; contains hair/teeth/skin; calcification on X-ray; risk of torsion"],
     ["Dysgerminoma","Malignant, germ cell","LDH, placental ALP","Most common malignant germ cell; radiosensitive; equivalent of seminoma"],
     ["Granulosa cell tumour","Sex cord-stromal","Inhibin B, oestrogen","Oestrogen-secreting → endometrial hyperplasia/cancer; Call-Exner bodies"],
     ["Krukenberg tumour","Metastatic","As per primary","Bilateral; signet ring cells; primary most often stomach; also colon, breast"],
    ],
    [4*cm,3*cm,3.5*cm,6.5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(b("<b>Endometrial Cancer</b>",st))
story.append(sb("Most common gynaecological malignancy in developed world; post-menopausal bleeding = endometrial Ca until proven otherwise",st))
story.append(sb("Type 1 (endometrioid, 80%): Oestrogen-driven; associated with obesity, nulliparity, DM, PCOS, tamoxifen use",st))
story.append(sb("Type 2 (serous/clear cell, 20%): Not oestrogen-driven; worse prognosis",st))
story.append(sb("Diagnosis: Transvaginal USS (endometrial thickness >4mm post-menopausal = refer) → pipelle biopsy",st))
story.append(pyq_box([
    "Most common malignant ovarian tumour: Serous cystadenocarcinoma (2020, 2021, 2022)",
    "Most common benign ovarian tumour in young females: Mature teratoma (dermoid cyst) (2021, 2023)",
    "Krukenberg tumour: Metastatic to ovary; bilateral; signet ring cells; stomach primary (2020, 2022, 2024)",
    "Granulosa cell tumour marker: Inhibin B (2022, 2023)",
    "Post-menopausal bleeding: Endometrial carcinoma until proven otherwise (2021, 2024)",
    "Call-Exner bodies: Granulosa cell tumour (2023)",
],sc["mid"],sc["light"]))
story.append(PageBreak())

# BENIGN GYN
story.append(chapter_header("CHAPTER 3: BENIGN GYNAECOLOGY — FIBROIDS, PCOS, ENDOMETRIOSIS",sc["dark"]))
story.append(sp(6))
story.append(section_bar("3.1 UTERINE FIBROIDS (LEIOMYOMA)",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Key Facts</b>",st))
story.append(sb("Most common benign uterine tumour (and most common solid pelvic tumour in women)",st))
story.append(sb("Oestrogen-dependent; regress post-menopause; worsened by pregnancy",st))
story.append(sb("Most common type: Intramural (within myometrium)",st))
story.append(sb("Most symptomatic: Submucous (under endometrium) → heavy menstrual bleeding (HMB)",st))
story.append(sb("Subserous: Pressure symptoms (urinary frequency, constipation); pedunculated can undergo torsion",st))
story.append(sb("Carneous (red) degeneration: In pregnancy; acute pain; haematoma formation",st))
story.append(b("<b>Management</b>",st))
story.append(sb("Medical (HMB only): Tranexamic acid, NSAIDs, Combined OCP, LNG-IUS (Mirena)",st))
story.append(sb("GnRH agonists: Pre-operative shrinkage (max 3-6 months — bone loss); Ulipristal acetate (SPRM)",st))
story.append(sb("Surgical: Myomectomy (preserve uterus); Hysterectomy (definitive); UAE (Uterine Artery Embolisation)",st))
story.append(section_bar("3.2 PCOS (STEIN-LEVENTHAL SYNDROME)",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Rotterdam Criteria — Diagnose if 2 of 3 present</b>",st))
story.append(sb("1. Oligo/anovulation (irregular cycles)",st))
story.append(sb("2. Clinical or biochemical hyperandrogenism (hirsutism, acne, elevated testosterone/DHEAS)",st))
story.append(sb("3. Polycystic ovaries on USS (≥12 follicles 2-9mm OR ovarian volume >10mL)",st))
story.append(b("<b>Management (Stepwise)</b>",st))
t=std_table(["Problem","First-Line Treatment"],
    [["Menstrual irregularity","Combined oral contraceptive pill (OCP); Progestogen cyclic therapy"],
     ["Hirsutism/acne","OCP + Spironolactone (anti-androgen); Eflornithine cream"],
     ["Insulin resistance/DM risk","Metformin 500mg BD-TID; lifestyle modification"],
     ["Infertility (anovulation)","Letrozole (now preferred over Clomiphene — PPCOSIG guidelines 2023)"],
     ["Refractory infertility","Gonadotrophins; Laparoscopic ovarian drilling; IVF"],
    ],
    [5*cm,12*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(section_bar("3.3 ENDOMETRIOSIS",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(sb("Ectopic endometrial glands + stroma outside uterus; cyclical oestrogen-driven",st))
story.append(sb("Classic triad: Dysmenorrhoea (cyclical), Deep dyspareunia, Infertility",st))
story.append(sb("Endometrioma (chocolate cyst): Ovarian endometriosis; thick brown fluid ('old blood')",st))
story.append(sb("Gold standard diagnosis: Laparoscopy + biopsy (powder-burn/gunshot lesions seen)",st))
story.append(sb("Staging: rAFS/ASRM staging I-IV (minimal to severe)",st))
story.append(sb("Medical: NSAIDs; Combined OCP; Progestogens; GnRH agonists; Danazol (androgenic — side effects)",st))
story.append(sb("Surgical: Conservative (laparoscopic ablation/excision); Radical (hysterectomy + BSO for severe)",st))
story.append(pyq_box([
    "PCOS diagnostic criteria: Rotterdam criteria 2 of 3 (2020, 2021, 2022, 2023)",
    "Drug of choice for anovulatory infertility in PCOS: Letrozole (updated 2023; previously Clomiphene) (2024)",
    "Chocolate cyst is a feature of: Endometriosis (ovarian endometrioma) (2020, 2022)",
    "Gold standard diagnosis of endometriosis: Laparoscopy + biopsy (2021, 2023)",
    "Most symptomatic fibroid type: Submucous (2021)",
    "Degeneration of fibroid in pregnancy: Carneous (red) degeneration (2020, 2022)",
],sc["mid"],sc["light"]))
story.append(sp(8))
footer_t=Table([[Paragraph("Obs-Gyn Notes Complete — UPSC CMS 2026",ParagraphStyle('ft',fontSize=12,fontName='Helvetica-Bold',textColor=colors.white,alignment=TA_CENTER))]],colWidths=[17*cm])
footer_t.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),colors.HexColor(sc["dark"])),('TOPPADDING',(0,0),(-1,-1),12),('BOTTOMPADDING',(0,0),(-1,-1),12)]))
story.append(footer_t)
doc.build(story)
print("ObsGyn PDF done")

~/upsc-cms-notes/gen_psm.py

import sys
sys.path.insert(0, '/home/daytona/workspace/upsc-cms-notes')
from pdf_helpers import *
from reportlab.platypus import PageBreak

OUT = "/home/daytona/workspace/upsc-cms-notes/05_PSM.pdf"
doc = make_doc(OUT)
sc = SUBJECT_COLORS["psm"]
st = make_styles(sc)
story = []

story += [
    Spacer(1,2.5*cm),
    Paragraph("UPSC CMS 2026",st["cover_title"]),
    Paragraph("SUBJECT 5: PREVENTIVE & SOCIAL MEDICINE",ParagraphStyle('x',fontSize=17,textColor=colors.HexColor(sc["mid"]),alignment=TA_CENTER,spaceAfter=8,fontName='Helvetica-Bold')),
    Paragraph("40 Questions | PYQ 2020-2024 Mapped | Examiner-Style Questions",st["cover_sub"]),
    Spacer(1,0.3*cm),
    HRFlowable(width="80%",thickness=2,color=colors.HexColor(sc["dark"]),hAlign='CENTER'),
    Spacer(1,0.3*cm),
    Paragraph("EXAM: 2nd AUGUST 2026",st["cover_date"]),
    Spacer(1,0.8*cm),
]
fd=[["Chapter","Avg Qs/Year","PYQ Frequency"],
    ["Epidemiology & Biostatistics","8-10","⭐⭐⭐⭐⭐ Most Important"],
    ["National Health Programmes","6-8","⭐⭐⭐⭐⭐ Very High"],
    ["Health Administration & Infrastructure","4-5","⭐⭐⭐⭐"],
    ["Communicable Disease Control","4-5","⭐⭐⭐⭐"],
    ["Nutrition & Diet","2-3","⭐⭐⭐"],
    ["Environment & Occupational Health","3-4","⭐⭐⭐⭐"],
    ["Demography & Vital Statistics","3-4","⭐⭐⭐⭐"],
]
story.append(std_table(fd[0],fd[1:],[7*cm,4*cm,6*cm],sc["dark"],sc["light"]))
story.append(PageBreak())

# CH1 EPIDEMIOLOGY
story.append(chapter_header("CHAPTER 1: EPIDEMIOLOGY & BIOSTATISTICS (8-10 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("1.1 STUDY DESIGNS",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Study Design","Direction","Measure of Association","Best For","Key Bias"],
    [["Case-Control","Retrospective (past exposure)","Odds Ratio (OR)","Rare diseases; quick, cheap","Recall bias, Selection bias"],
     ["Cohort (prospective)","Forward (exposure → outcome)","Relative Risk (RR); Incidence","Causation; incidence measurement","Attrition/loss to follow-up bias"],
     ["Cohort (retrospective)","Backward using records","RR; Incidence","When prospective not feasible","Incomplete records"],
     ["RCT","Prospective; experimental","ARR, RRR, NNT","Gold standard for causation","Ethical constraints; expensive"],
     ["Cross-sectional","Snapshot in time","Prevalence; Prevalence ratio","Prevalence; planning health services","Survivor bias; Cannot establish causation"],
     ["Ecological","Population-level data","Correlation","Hypothesis generation","Ecological fallacy"],
     ["Systematic review","Combines multiple studies","Pooled estimates","Best evidence overview","Publication bias"],
     ["Meta-analysis","Quantitative synthesis","Pooled OR/RR/SMD","Statistical combination of RCTs","Heterogeneity"],
    ],
    [3.5*cm,3.5*cm,3*cm,3.5*cm,3.5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(section_bar("1.2 MEASURES OF DISEASE FREQUENCY",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Incidence & Prevalence</b>",st))
story.append(sb("Incidence rate = New cases in time period / Population at risk × Time",st))
story.append(sb("Prevalence = Existing cases / Total population at a point in time",st))
story.append(sb("Prevalence ≈ Incidence × Duration (for stable chronic disease)",st))
story.append(sb("Point prevalence = at a specific moment; Period prevalence = over a period of time",st))
story.append(sb("Attack rate = Cases during outbreak / Population at risk at start × 100 (expressed as %)",st))
story.append(sb("Secondary attack rate = New cases in contacts of primary case / Susceptible contacts × 100",st))
story.append(b("<b>Measures of Association</b>",st))
story.append(sb("Relative Risk (RR) = Incidence in exposed / Incidence in unexposed; only in cohort/RCT",st))
story.append(sb("Odds Ratio (OR) = (a×d)/(b×c) from 2×2 table; used in case-control; approximates RR when disease is rare",st))
story.append(sb("Attributable Risk (AR) = Incidence in exposed - Incidence in unexposed",st))
story.append(sb("Population Attributable Risk (PAR) = Incidence in total population - Incidence in unexposed",st))
story.append(sb("NNT (Number Needed to Treat) = 1/ARR; NNH = 1/ARI",st))
story.append(sp(4))
story.append(section_bar("1.3 SCREENING TESTS — VERY HIGH YIELD",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Parameter","Formula","What it means"],
    [["Sensitivity","TP / (TP+FN)","Proportion of TRUE DISEASE correctly identified; rules OUT disease (SnNOut); best for screening"],
     ["Specificity","TN / (TN+FP)","Proportion of TRUE NORMALS correctly identified; rules IN disease (SpPin); best for confirmation"],
     ["PPV (Positive Predictive Value)","TP / (TP+FP)","Probability of disease given positive test; INCREASES with prevalence"],
     ["NPV (Negative Predictive Value)","TN / (TN+FN)","Probability of no disease given negative test; DECREASES with prevalence"],
     ["Likelihood Ratio +ve","Sensitivity / (1-Specificity)","How much more likely is a +ve test in disease vs no disease"],
     ["Likelihood Ratio -ve","(1-Sensitivity) / Specificity","How much more likely is a -ve test in no disease vs disease"],
    ],
    [4*cm,4*cm,9*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(h("As Prevalence increases → PPV increases, NPV decreases",st))
story.append(h("SnNOut: High SENSITIVITY test if Negative rules OUT disease (e.g., ELISA for HIV)",st))
story.append(h("SpPin: High SPECIFICITY test if Positive rules IN disease (e.g., Western Blot for HIV)",st))
story.append(mn("Wilson & Jungner criteria for screening: SWAT — Suitable disease, Worthwhile treatment, Accepted test, Treatment available for detected cases",st))
story.append(pyq_box([
    "Gold standard study design for causation: RCT (2020, 2021, 2022)",
    "Recall bias is associated with: Case-control study (2020, 2022, 2023)",
    "PPV depends on: Prevalence (2021, 2022, 2024)",
    "Sensitivity formula: TP/(TP+FN) (2020, 2021, 2023, 2024)",
    "Measure of association in case-control: Odds Ratio (2020, 2021, 2022, 2023)",
    "NNT = 1/ARR — Number needed to treat (2023, 2024)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("A new test for TB has sensitivity 90% and specificity 70%. In a population where TB prevalence is 1%, what happens to PPV?","PPV will be LOW despite high sensitivity, because prevalence is very low — most positive tests will be false positives. This is why screening tests in low-prevalence populations yield many false positives."),
    ("In an epidemic investigation, you calculate secondary attack rate of 60%. What does this mean?","60% of susceptible contacts of a primary case developed the disease — this measures how contagious the disease is (transmissibility). Compare to primary attack rate which measures overall outbreak severity."),
],sc["mid"]))
story.append(PageBreak())

# CH2 NATIONAL HEALTH PROGRAMMES
story.append(chapter_header("CHAPTER 2: NATIONAL HEALTH PROGRAMMES (6-8 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("2.1 MATERNAL & CHILD HEALTH PROGRAMMES",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Programme","Full Form","Key Feature","Benefit/Target"],
    [["JSSK","Janani Shishu Suraksha Karyakram (2011)","Free delivery (normal + CS), drugs, diagnostics, blood, diet, transport at govt hospitals","Reduces OOP expenditure; covers mother + sick newborn up to 1 year"],
     ["JSY","Janani Suraksha Yojana (2005)","Conditional cash transfer for institutional delivery","LPS states: Rs.1400 rural, Rs.1000 urban; HPS states: Rs.700 rural, Rs.600 urban"],
     ["PMMVY","PM Matru Vandana Yojana","Rs.5000 maternity benefit; 3 instalments; 1st living child","Compensates for wage loss during pregnancy/lactation"],
     ["RBSK","Rashtriya Bal Swasthya Karyakram (2013)","Screening 0-18 years for 4Ds","4Ds: Defects at birth, Deficiencies, Diseases, Developmental delays; DEIC at district level"],
     ["MAA","Mothers' Absolute Affection Programme","Promotion of breastfeeding; health worker counselling","Exclusive breastfeeding for 6 months + complementary feeding"],
     ["RMNCH+A","Reproductive Maternal Newborn Child + Adolescent Health","Continuum of care from pre-pregnancy to adolescence","Integrates all MCH services"],
    ],
    [2.5*cm,4.5*cm,5.5*cm,4.5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(section_bar("2.2 DISEASE-SPECIFIC NATIONAL PROGRAMMES",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Programme","Disease Target","Key Strategy","Current Status"],
    [["NTEP (National TB Elimination Programme)","Tuberculosis","DOTS strategy; Ni-kshay Mitra; Universal Drug Susceptibility Testing","Target: Eliminate TB by 2025 (<1/10 lakh population)"],
     ["NVBDCP","Malaria, Dengue, Filaria, Kala-azar, JE, Chikungunya","IRS (indoor residual spraying), ITNs, vector surveillance, MDA","Malaria elimination target: 2027; Filaria: 2030"],
     ["NACP (Phase 4)","HIV/AIDS","ICTC, PPTCT, ART centres, targeted interventions","90-90-90 target: 90% diagnosed, 90% on ART, 90% virally suppressed"],
     ["NPCDCS","DM, HTN, Cancers (oral/cervical/breast)","Screening at PHC level; NCD clinics at CHC/district level","30+ districts initially; now pan-India"],
     ["NHM","Overall health system strengthening","NRHM (rural) + NUHM (urban) = NHM; launched 2005","ASHA, Janani Suraksha, mobile medical units"],
     ["NMHP","Mental health","District Mental Health Programme (DMHP); CAP","Integration of mental health into primary care"],
    ],
    [3.5*cm,3.5*cm,5.5*cm,4.5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(pyq_box([
    "Full form of RBSK: Rashtriya Bal Swasthya Karyakram (2021, 2022, 2023)",
    "JSY beneficiary cash amount in LPS rural: Rs.1400 (2020, 2021)",
    "4 Ds of RBSK: Defects at birth, Deficiencies, Diseases, Developmental delays (2022, 2024)",
    "NTEP target for TB elimination in India: 2025 (2022, 2023)",
    "Full form of PMMVY: Pradhan Mantri Matru Vandana Yojana (2021)",
    "90-90-90 target is for: HIV/AIDS (NACP) (2022, 2024)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("What is the difference between JSY and JSSK?","JSY: Cash incentive (conditional cash transfer) to encourage institutional delivery; paid to mother. JSSK: Entitlement-based scheme — provides free services (delivery, drugs, diagnostics, diet, transport) at government hospitals. Launched 2011. JSSK covers sick newborn up to 1 year."),
    ("ASHA is a frontline health worker. What are her key roles?","1) Mobilise community for health services; 2) Facilitate institutional delivery (JSY); 3) DOTS treatment supporter for TB; 4) Antenatal registration; 5) Malaria rapid test + treatment; 6) Dispense ORS, iron-folate, condoms, OCP; 7) Newborn care promotion. Performance-based incentive."),
],sc["mid"]))
story.append(PageBreak())

# CH3 HEALTH ADMINISTRATION
story.append(chapter_header("CHAPTER 3: HEALTH ADMINISTRATION & INFRASTRUCTURE (4-5 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("3.1 RURAL HEALTH INFRASTRUCTURE",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Facility","Population served","Staff","Beds","Key Functions"],
    [["Sub-Centre","5000 (plains); 3000 (hilly/tribal)","1 ANM + 1 male health worker (MPW); 1 ASHA per 1000 population","None","First point of contact; MCH, FP, immunisation, basic drugs"],
     ["PHC (Primary Health Centre)","30,000 (plains); 20,000 (hilly/tribal)","1 Medical Officer + 14 paramedical staff","6 (4 indoor + 2 obs)","Referral unit from sub-centres; OPD, deliveries, lab, cold chain, MCH"],
     ["CHC (Community Health Centre)","1,20,000 (plains); 80,000 (hilly/tribal)","4 specialists (Physician, Surgeon, Obs-Gyn, Paediatrician) + 21 paramedical","30","First referral unit (FRU); 24h emergency, blood storage, OT"],
     ["Sub-district / Taluk Hospital","3-5 lakh","General specialists","60-100","Specialist care; referral from CHCs"],
     ["District Hospital","10-20 lakh","All specialties","100-500+","Apex at district; teaching if attached to medical college"],
    ],
    [2.5*cm,3.5*cm,5*cm,2*cm,4*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(h("IPHS (Indian Public Health Standards): Minimum standards defined by MoHFW for each level",st))
story.append(h("CHC = First Referral Unit (FRU) — must have 24h C-section, blood transfusion, EmOC",st))
story.append(section_bar("3.2 KEY HEALTH WORKERS",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Worker","Posted At","Population","Key Roles"],
    [["ASHA","Village level","1 per 1000 population","Community mobilisation; DOTS; JSY; malaria testing; newborn care; link worker between community and health system"],
     ["ANM (Auxiliary Nurse Midwife)","Sub-centre (2 ANMs per sub-centre now)","5000","MCH services; immunisation; FP; ante-natal care; home deliveries"],
     ["Anganwadi Worker (AWW)","ICDS centre (Anganwadi)","400-800","6 ICDS services: supplementary nutrition, immunisation, health check-up, referral, pre-school education, health+nutrition education"],
     ["MPW (Multipurpose Worker)","Sub-centre","5000","Disease surveillance; vector control; sanitation"],
    ],
    [3.5*cm,3.5*cm,3*cm,7*cm],sc["dark"],sc["light"])
story.append(t)
story.append(pyq_box([
    "Population served by Sub-Centre (plains): 5000 (2020, 2021, 2022, 2023)",
    "Population served by PHC (plains): 30,000 (2020, 2022, 2024)",
    "Number of beds at CHC: 30 beds (2021, 2023)",
    "ASHA population coverage: 1 per 1000 population (2020, 2021, 2022)",
    "First Referral Unit (FRU): CHC (2022, 2024)",
    "Anganwadi serves population of: 400-800 (2021)",
],sc["mid"],sc["light"]))
story.append(PageBreak())

# CH4 VITAL STATISTICS & DEMOGRAPHY
story.append(chapter_header("CHAPTER 4: VITAL STATISTICS & DEMOGRAPHY (3-4 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("4.1 CURRENT INDIA INDICATORS (SRS 2020 / NFHS-5)",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Indicator","Definition","Current India Value","SDG Target / Goal"],
    [["MMR (Maternal Mortality Ratio)","Maternal deaths per 1,00,000 live births","97 (SRS 2018-20); 103 (SRS 2017-19)","SDG: <70 by 2030"],
     ["IMR (Infant Mortality Rate)","Deaths <1 year per 1000 live births","28 (SRS 2020)","SDG: ≤12 by 2030; NHP: 28"],
     ["NMR (Neonatal Mortality Rate)","Deaths <28 days per 1000 live births","20 (SRS 2020)",""],
     ["U5MR (Under-5 Mortality Rate)","Deaths <5 years per 1000 live births","32 (SRS 2020)","SDG: ≤25 by 2030"],
     ["TFR (Total Fertility Rate)","Average children per woman in lifetime","2.0 (SRS 2020); 2.1 (NFHS-5 2019-21)","Replacement level: 2.1"],
     ["CBR (Crude Birth Rate)","Live births per 1000 population","19.5 (SRS 2020)",""],
     ["CDR (Crude Death Rate)","Deaths per 1000 population","6.0 (SRS 2020)",""],
     ["Life expectancy at birth","Average years of life","69.7 years (2015-19); Male 68.2, Female 71.1",""],
    ],
    [3.5*cm,5*cm,5.5*cm,3*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(b("<b>Best Registrar General of India source: Sample Registration System (SRS)</b>",st))
story.append(sb("SRS: Continuous demographic data; civil registration; provides IMR, MMR, TFR, CBR, CDR",st))
story.append(sb("NFHS (National Family Health Survey): Household survey; health, nutrition, family planning data; NFHS-5 = 2019-21",st))
story.append(sb("Census: Every 10 years; last = 2011; next = 2021 (delayed due to COVID)",st))
story.append(pyq_box([
    "Current IMR of India (SRS): 28/1000 live births (2022, 2023, 2024)",
    "MMR of India: ~97/1,00,000 live births (2022, 2023)",
    "TFR of India: 2.0 (SRS 2020); replacement level = 2.1 (2021, 2022, 2024)",
    "Best source for IMR in India: SRS (Sample Registration System) (2020, 2021)",
    "NFHS-5 conducted in: 2019-21 (2022)",
],sc["mid"],sc["light"]))
story.append(PageBreak())

# CH5 COMMUNICABLE DISEASE CONTROL
story.append(chapter_header("CHAPTER 5: COMMUNICABLE DISEASE CONTROL (4-5 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("5.1 MODES OF TRANSMISSION & DISEASE STATUS",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Disease","Eradication/Elimination Status","Key Fact"],
    [["Smallpox","Globally eradicated 1980; India 1977 (last case Ali Maow Maalin was Somalia 1977; India's last 1975 Bihar)","Only disease eradicated globally; WHO certified 1980"],
     ["Polio","India declared polio-free: 27 March 2014 (WHO certified)","Last case: Jan 2011 — Rukhsar Khatoon, Howrah, WB (P1 strain)"],
     ["Guinea worm (Dracunculiasis)","Near global eradication; India eliminated","No drug/vaccine; only mechanical extraction"],
     ["Yaws","Eliminated in India: 1970s; re-emerged in some areas","Treponema pallidum pertenue; Penicillin treatment"],
     ["Kala-azar","Elimination target: <1/10,000 population at sub-district level","MDA strategy; sandfly vector (Phlebotomus argentipes)"],
     ["Leprosy","Eliminated at national level in India: Dec 2005 (<1/10,000)","Still endemic in some districts; multidrug therapy (MDT)"],
     ["Filariasis","MDA programme ongoing; elimination target 2030","DEC + Albendazole MDA annually in endemic areas"],
    ],
    [3*cm,4.5*cm,9.5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(section_bar("5.2 EPIDEMICS & HERD IMMUNITY",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Disease","R0 (Basic Reproduction Number)","Herd Immunity Threshold","Vaccine"],
    [["Measles","12-18 (most infectious respiratory)","92-95%","MMR; 2 doses"],
     ["Chickenpox","8-10","85-90%","Varicella vaccine"],
     ["Polio","5-7","80-86%","OPV/IPV"],
     ["Mumps","4-7","75-86%","MMR"],
     ["Diphtheria","6-7","85%","DPT"],
     ["Rubella","5-7","83-85%","MMR"],
     ["COVID-19 (Omicron variant)","8-15","88-92%","mRNA/vector vaccines"],
    ],
    [4*cm,4*cm,4*cm,5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(sp(4))
story.append(h("Herd immunity threshold = 1 - (1/R0) × 100%",st))
story.append(pyq_box([
    "Last polio case in India: January 2011, Howrah, West Bengal (2021, 2022, 2023)",
    "India declared polio-free: 27 March 2014 (2020, 2022)",
    "Disease eradicated globally: Smallpox (1980) (2020, 2021, 2022, 2023, 2024)",
    "Highest R0 (most infectious): Measles (R0=12-18) (2022, 2024)",
    "Herd immunity formula: 1-(1/R0) (2023)",
    "Leprosy eliminated from India: December 2005 (2021, 2024)",
],sc["mid"],sc["light"]))
story.append(PageBreak())

# CH6 ENVIRONMENT & OCCUPATIONAL HEALTH
story.append(chapter_header("CHAPTER 6: ENVIRONMENT & OCCUPATIONAL HEALTH (3-4 Qs/Year)",sc["dark"]))
story.append(sp(6))
story.append(section_bar("6.1 WATER QUALITY & PURIFICATION",sc["mid"],sc["light"]))
story.append(sp(4))
story.append(b("<b>Drinking Water Standards (WHO & BIS)</b>",st))
story.append(sb("WHO: E.coli = 0 per 100mL (piped); Turbidity <1 NTU; pH 6.5-8.5; Fluoride 0.5-1.5 mg/L; Nitrate <50 mg/L",st))
story.append(sb("Coliforms = indicator organisms of faecal contamination (E.coli = most specific for faecal)",st))
story.append(sb("MPN (Most Probable Number) test: Presumptive, confirmatory, completed test (3-step)",st))
story.append(b("<b>Chlorination</b>",st))
story.append(sb("Residual chlorine: 0.5 mg/L after 30 minutes contact time (chlorine demand met)",st))
story.append(sb("Break-point chlorination: Adding enough chlorine to destroy all organic matter + ammonia; residual after break point = free residual chlorine",st))
story.append(sb("Super chlorination: >5 mg/L for emergencies; followed by dechlorination with sodium thiosulphate",st))
story.append(section_bar("6.2 OCCUPATIONAL DISEASES",sc["mid"],sc["light"]))
story.append(sp(4))
t=std_table(["Disease","Causative agent","Occupation","Key Feature"],
    [["Silicosis","Free crystalline silica (quartz)","Mining, quarrying, sandblasting, pottery","Most fibrogenic dust; eggshell calcification of hilar LN; increases TB risk"],
     ["Asbestosis","Asbestos fibres (amphibole > serpentine)","Asbestos mining, insulation, shipbuilding","Diffuse pleural plaques; Mesothelioma (pleural); Ferruginous bodies (asbestos bodies) on BAL"],
     ["CWP (Coal workers' pneumoconiosis)","Coal dust","Coal mining","Simple (black lung) → progressive massive fibrosis (PMF)"],
     ["Byssinosis","Cotton/jute/flax dust","Textile workers","Monday morning fever; chest tightness on return from weekend"],
     ["Bagassosis","Bagasse (sugarcane residue)","Sugar cane workers","Extrinsic allergic alveolitis (hypersensitivity pneumonitis)"],
     ["Farmer's lung","Thermophilic actinomycetes (Micropolyspora faeni)","Farmers handling mouldy hay","Extrinsic allergic alveolitis"],
     ["Anthrax","Bacillus anthracis","Wool sorters (woolsorter's disease), tanners","Cutaneous (most common), inhalational (most lethal)"],
     ["Lead poisoning","Lead (Pb)","Battery workers, painters (lead paint), plumbers","Burton's line (blue-black gum line); basophilic stippling; motor neuropathy (wrist drop)"],
    ],
    [3*cm,4*cm,3.5*cm,6.5*cm],sc["dark"],sc["light"])
story.append(t)
story.append(pyq_box([
    "Most fibrogenic dust: Silica (2020, 2021, 2022, 2023)",
    "Byssinosis caused by: Cotton/jute dust (2020, 2022, 2024)",
    "Monday morning fever in: Byssinosis (2021, 2023)",
    "Mesothelioma caused by: Asbestos (2020, 2021, 2022, 2023)",
    "Eggshell calcification of hilar LN: Silicosis (2021, 2024)",
    "Woolsorter's disease caused by: Anthrax (Bacillus anthracis) (2022)",
    "Lead poisoning sign on gum: Burton's line (2021, 2023)",
],sc["mid"],sc["light"]))
story.append(examiner_box([
    ("A 45-year-old coal miner has progressive dyspnoea. CXR shows large confluent upper lobe opacities. Diagnosis?","Progressive Massive Fibrosis (PMF) — advanced coal workers' pneumoconiosis. These 'complicated' CWP lesions are >1cm and cause significant respiratory disability. No effective treatment; supportive care, avoid further exposure."),
    ("What is the difference between silicosis and asbestosis?","Silicosis: Upper lobe fibrosis, eggshell calcification of hilar LN, nodular; increases TB risk. Asbestosis: Lower lobe fibrosis, pleural plaques/mesothelioma, ferruginous (asbestos) bodies; increases lung cancer + mesothelioma risk. Asbestos = 'complete' carcinogen."),
],sc["mid"]))
story.append(sp(8))
footer_t=Table([[Paragraph("PSM Notes Complete — UPSC CMS 2026",ParagraphStyle('ft',fontSize=12,fontName='Helvetica-Bold',textColor=colors.white,alignment=TA_CENTER))]],colWidths=[17*cm])
footer_t.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),colors.HexColor(sc["dark"])),('TOPPADDING',(0,0),(-1,-1),12),('BOTTOMPADDING',(0,0),(-1,-1),12)]))
story.append(footer_t)
doc.build(story)
print("PSM PDF done")

cd /home/daytona/workspace/upsc-cms-notes && python gen_paediatrics.py && python…