NEET PG surgery most frequently asked topics PYQ high yield 2024 2025

https://www.diginerve.com/blogs/surgery-rapid-revision-neet-…

mkdir -p /home/daytona/workspace/surgery-neet-pg && ls /home/daytona/workspace/

mkdir -p /home/daytona/workspace/surgery-neet-pg && python3 -c "import reportlab…

~/surgery-neet-pg/generate_surgery_pdf.py

#!/usr/bin/env python3
"""NEET PG Surgery Rapid Revision PDF Generator"""

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

OUTPUT = "/home/daytona/workspace/surgery-neet-pg/NEET_PG_Surgery_Revision.pdf"

# ── Colour palette ──────────────────────────────────────────────────────────
C_NAVY   = colors.HexColor("#1a2e5a")
C_TEAL   = colors.HexColor("#0d7377")
C_ORANGE = colors.HexColor("#e07b3a")
C_RED    = colors.HexColor("#c0392b")
C_GREEN  = colors.HexColor("#1e8449")
C_YELLOW = colors.HexColor("#f4d03f")
C_LIGHT  = colors.HexColor("#eaf4fb")
C_LGREEN = colors.HexColor("#eafaf1")
C_LRED   = colors.HexColor("#fdf2f2")
C_LYELLOW= colors.HexColor("#fefde7")
C_LGREY  = colors.HexColor("#f8f9fa")
C_WHITE  = colors.white

# ── Styles ───────────────────────────────────────────────────────────────────
base = getSampleStyleSheet()

def S(name, parent="Normal", **kw):
    s = ParagraphStyle(name, parent=base[parent], **kw)
    return s

COVER_TITLE = S("CoverTitle", fontSize=32, textColor=C_WHITE,
                alignment=TA_CENTER, spaceAfter=6, fontName="Helvetica-Bold")
COVER_SUB   = S("CoverSub",   fontSize=16, textColor=C_YELLOW,
                alignment=TA_CENTER, spaceAfter=4, fontName="Helvetica-Bold")
COVER_INFO  = S("CoverInfo",  fontSize=11, textColor=C_WHITE,
                alignment=TA_CENTER, spaceAfter=3)

CH_TITLE = S("ChTitle", fontSize=20, textColor=C_WHITE,
             fontName="Helvetica-Bold", alignment=TA_LEFT,
             spaceAfter=4, spaceBefore=2)
CH_SUB   = S("ChSub",   fontSize=13, textColor=C_TEAL,
             fontName="Helvetica-Bold", spaceBefore=10, spaceAfter=3)
CH_SUB2  = S("ChSub2",  fontSize=11, textColor=C_NAVY,
             fontName="Helvetica-Bold", spaceBefore=6, spaceAfter=2)

BODY     = S("Body",    fontSize=9.5, leading=14, spaceAfter=3, alignment=TA_JUSTIFY)
BULLET   = S("Bullet",  fontSize=9.5, leading=14, leftIndent=14, spaceAfter=2,
             bulletIndent=4)
PYQ_S    = S("PYQ",     fontSize=9,   textColor=C_NAVY, leading=13,
             leftIndent=8, fontName="Helvetica-Oblique")
IMP_S    = S("ImpBox",  fontSize=9,   textColor=C_RED,  leading=13,
             fontName="Helvetica-Bold", leftIndent=8)
TIP_S    = S("Tip",     fontSize=9,   textColor=C_GREEN, leading=13,
             leftIndent=8, fontName="Helvetica-Bold")
BOLD_S   = S("BoldS",   fontSize=9.5, fontName="Helvetica-Bold", leading=14)
TOC_S    = S("TOC",     fontSize=11,  leading=18, leftIndent=10)

def header_table(text, bg=C_NAVY, fg=C_WHITE, fontsize=16):
    """Full-width coloured header band."""
    st = ParagraphStyle("ht", fontSize=fontsize, textColor=fg,
                        fontName="Helvetica-Bold", alignment=TA_LEFT, leading=fontsize+4)
    t = Table([[Paragraph(text, st)]], colWidths=[170*mm])
    t.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), bg),
        ("TOPPADDING",    (0,0), (-1,-1), 6),
        ("BOTTOMPADDING", (0,0), (-1,-1), 6),
        ("LEFTPADDING",   (0,0), (-1,-1), 10),
        ("RIGHTPADDING",  (0,0), (-1,-1), 6),
    ]))
    return t

def box_table(rows_data, bg=C_LIGHT, border_color=C_TEAL, col_widths=None):
    """Simple info box."""
    if col_widths is None:
        col_widths = [170*mm]
    t = Table(rows_data, colWidths=col_widths)
    t.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), bg),
        ("BOX",           (0,0), (-1,-1), 1.5, border_color),
        ("TOPPADDING",    (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 5),
        ("LEFTPADDING",   (0,0), (-1,-1), 8),
        ("RIGHTPADDING",  (0,0), (-1,-1), 8),
        ("VALIGN",        (0,0), (-1,-1), "TOP"),
    ]))
    return t

def pyq_box(questions):
    """Orange-bordered PYQ box."""
    rows = []
    rows.append([Paragraph("★ PYQ / FREQUENTLY ASKED", S("ph", fontSize=9,
                  fontName="Helvetica-Bold", textColor=C_ORANGE))])
    for q in questions:
        rows.append([Paragraph("• " + q, PYQ_S)])
    t = Table(rows, colWidths=[170*mm])
    t.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), C_LYELLOW),
        ("BOX",           (0,0), (-1,-1), 2,   C_ORANGE),
        ("LINEBELOW",     (0,0), (0,0),   0.5, C_ORANGE),
        ("TOPPADDING",    (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING",   (0,0), (-1,-1), 8),
        ("RIGHTPADDING",  (0,0), (-1,-1), 8),
    ]))
    return t

def imp_box(points):
    """Red high-importance box."""
    rows = [[Paragraph("🔴 HIGH YIELD / REMEMBER", S("rh", fontSize=9,
              fontName="Helvetica-Bold", textColor=C_RED))]]
    for p in points:
        rows.append([Paragraph("► " + p, IMP_S)])
    t = Table(rows, colWidths=[170*mm])
    t.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), C_LRED),
        ("BOX",           (0,0), (-1,-1), 2,   C_RED),
        ("LINEBELOW",     (0,0), (0,0),   0.5, C_RED),
        ("TOPPADDING",    (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING",   (0,0), (-1,-1), 8),
        ("RIGHTPADDING",  (0,0), (-1,-1), 8),
    ]))
    return t

def tip_box(points):
    """Green mnemonic/tip box."""
    rows = [[Paragraph("💡 MNEMONIC / TIP", S("gh", fontSize=9,
              fontName="Helvetica-Bold", textColor=C_GREEN))]]
    for p in points:
        rows.append([Paragraph("✓ " + p, TIP_S)])
    t = Table(rows, colWidths=[170*mm])
    t.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), C_LGREEN),
        ("BOX",           (0,0), (-1,-1), 2,   C_GREEN),
        ("LINEBELOW",     (0,0), (0,0),   0.5, C_GREEN),
        ("TOPPADDING",    (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING",   (0,0), (-1,-1), 8),
        ("RIGHTPADDING",  (0,0), (-1,-1), 8),
    ]))
    return t

def two_col_table(left_data, right_data, header_left="", header_right=""):
    """Two-column comparison table."""
    col_w = [83*mm, 83*mm]
    rows = []
    if header_left or header_right:
        hs = S("th", fontSize=9, fontName="Helvetica-Bold",
               textColor=C_WHITE, alignment=TA_CENTER)
        rows.append([Paragraph(header_left, hs), Paragraph(header_right, hs)])
    max_len = max(len(left_data), len(right_data))
    for i in range(max_len):
        l = Paragraph("• " + left_data[i],  BULLET) if i < len(left_data)  else Paragraph("", BODY)
        r = Paragraph("• " + right_data[i], BULLET) if i < len(right_data) else Paragraph("", BODY)
        rows.append([l, r])
    style = [
        ("BACKGROUND",    (0,0), (-1,-1), C_LGREY),
        ("BOX",           (0,0), (-1,-1), 1, C_TEAL),
        ("INNERGRID",     (0,0), (-1,-1), 0.5, colors.HexColor("#b0bec5")),
        ("TOPPADDING",    (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING",   (0,0), (-1,-1), 6),
        ("RIGHTPADDING",  (0,0), (-1,-1), 6),
        ("VALIGN",        (0,0), (-1,-1), "TOP"),
    ]
    if header_left or header_right:
        style += [("BACKGROUND", (0,0), (1,0), C_NAVY),
                  ("FONTNAME",   (0,0), (1,0), "Helvetica-Bold")]
    t = Table(rows, colWidths=col_w)
    t.setStyle(TableStyle(style))
    return t

def data_table(header_row, data_rows, col_widths=None):
    """Generic data table with header."""
    if col_widths is None:
        n = len(header_row)
        col_widths = [170*mm/n]*n
    hs = S("dth", fontSize=9, fontName="Helvetica-Bold", textColor=C_WHITE, alignment=TA_CENTER)
    rows = [[Paragraph(h, hs) for h in header_row]]
    bs = S("dtr", fontSize=9, leading=13)
    for row in data_rows:
        rows.append([Paragraph(str(c), bs) for c in row])
    style = [
        ("BACKGROUND",    (0,0), (-1,0),  C_NAVY),
        ("BACKGROUND",    (0,1), (-1,-1), C_LGREY),
        ("ROWBACKGROUNDS",(0,1), (-1,-1), [C_WHITE, C_LGREY]),
        ("BOX",           (0,0), (-1,-1), 1,   C_NAVY),
        ("INNERGRID",     (0,0), (-1,-1), 0.5, colors.HexColor("#b0bec5")),
        ("TOPPADDING",    (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING",   (0,0), (-1,-1), 6),
        ("RIGHTPADDING",  (0,0), (-1,-1), 6),
        ("VALIGN",        (0,0), (-1,-1), "TOP"),
    ]
    t = Table(rows, colWidths=col_widths)
    t.setStyle(TableStyle(style))
    return t

sp  = lambda h=6: Spacer(1, h)
hr  = lambda: HRFlowable(width="100%", thickness=0.5, color=C_TEAL, spaceAfter=4, spaceBefore=4)

# ════════════════════════════════════════════════════════════════════════════
# CONTENT BUILDER
# ════════════════════════════════════════════════════════════════════════════
def build_story():
    story = []

    # ── COVER PAGE ────────────────────────────────────────────────────────
    cover_bg = Table(
        [[Paragraph("NEET PG", COVER_TITLE)],
         [Paragraph("SURGERY", S("cs2", fontSize=44, textColor=C_YELLOW,
                                  fontName="Helvetica-Bold", alignment=TA_CENTER))],
         [Paragraph("RAPID REVISION NOTES", COVER_SUB)],
         [sp(8)],
         [Paragraph("2-Day Complete Surgery Revision", COVER_INFO)],
         [Paragraph("High-Yield • PYQs • Mnemonics • Clinical Algorithms", COVER_INFO)],
         [sp(4)],
         [Paragraph("Topics: General Surgery • Trauma • GI • Hepatobiliary • Breast • Thyroid •", COVER_INFO)],
         [Paragraph("Hernia • Urology • Burns • Vascular • Paediatric Surgery • Oncology", COVER_INFO)],
         [sp(20)],
         [Paragraph("Prepared for NEET PG / INI-CET / FMGE  |  July 2026", COVER_INFO)],
        ],
        colWidths=[190*mm]
    )
    cover_bg.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), C_NAVY),
        ("TOPPADDING",    (0,0), (-1,-1), 12),
        ("BOTTOMPADDING", (0,0), (-1,-1), 12),
        ("LEFTPADDING",   (0,0), (-1,-1), 20),
        ("RIGHTPADDING",  (0,0), (-1,-1), 20),
    ]))
    story.append(cover_bg)
    story.append(PageBreak())

    # ── TABLE OF CONTENTS ─────────────────────────────────────────────────
    story.append(header_table("  TABLE OF CONTENTS", C_TEAL))
    story.append(sp(6))
    toc_items = [
        ("1", "General Surgery Principles", "Wound Healing • Shock • Fluids • Sterilisation • Sutures"),
        ("2", "Trauma & Emergency Surgery", "ATLS • Burns • Head Injury • Abdominal Trauma"),
        ("3", "Gastrointestinal Surgery", "Appendicitis • Peptic Ulcer • Intestinal Obstruction • GI Cancers"),
        ("4", "Hepatobiliary & Pancreas", "Gallstones • Pancreatitis • Liver Abscess • Jaundice"),
        ("5", "Breast Surgery",            "Breast Lumps • Carcinoma • Staging • Operations"),
        ("6", "Thyroid & Parathyroid",      "Goitre • Carcinoma • Hyperthyroidism • Parathyroid"),
        ("7", "Hernia",                     "Inguinal • Femoral • Special Hernias • Complications"),
        ("8", "Urology",                    "Renal Stones • BPH • Bladder CA • Testicular Torsion"),
        ("9", "Vascular Surgery",           "AAA • DVT • Varicose Veins • Peripheral Vascular Disease"),
        ("10","Paediatric Surgery",         "Pyloric Stenosis • Intussusception • Hirschsprung • CDH"),
        ("11","Surgical Oncology",          "Staging • TNM • Tumour Markers • Biopsy Types"),
        ("12","Surgical Instruments & Procedures", "Key Instruments • Drains • Anastomosis • Laparoscopy"),
    ]
    for num, title, subtopics in toc_items:
        row = [[Paragraph(f"<b>{num}.</b>  <b>{title}</b>", TOC_S),
                Paragraph(f"<i>{subtopics}</i>", S("ts", fontSize=9, textColor=colors.grey, leading=14))]]
        t = Table(row, colWidths=[65*mm, 105*mm])
        t.setStyle(TableStyle([
            ("TOPPADDING",    (0,0), (-1,-1), 3),
            ("BOTTOMPADDING", (0,0), (-1,-1), 3),
            ("LEFTPADDING",   (0,0), (-1,-1), 4),
            ("LINEBELOW",     (0,0), (-1,-1), 0.3, colors.HexColor("#cfd8dc")),
        ]))
        story.append(t)
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 1 - GENERAL SURGERY PRINCIPLES
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 1 - GENERAL SURGERY PRINCIPLES"))
    story.append(sp(8))

    story.append(Paragraph("1.1  WOUND HEALING", CH_SUB))
    story.append(data_table(
        ["Type", "Definition", "Examples", "Healing Time"],
        [
            ["Primary (1st) Intention", "Clean wound closed within 6-8 hrs; edges approximated", "Surgical incisions, sutured lacerations", "7-10 days"],
            ["Secondary (2nd) Intention", "Wound left open; heals by granulation, contraction, epithelialisation", "Infected wounds, ulcers, abscesses", "Weeks-months"],
            ["Tertiary (3rd) Intention\n(Delayed 1st)", "Wound initially left open; closed later after infection controlled", "Contaminated wounds", "Variable"],
        ],
        col_widths=[38*mm, 48*mm, 52*mm, 30*mm]
    ))
    story.append(sp(6))
    story.append(Paragraph("Phases of Wound Healing", CH_SUB2))
    story.append(data_table(
        ["Phase", "Timing", "Key Events", "Cells Involved"],
        [
            ["Haemostasis", "Immediate (0-hrs)", "Vasoconstriction, platelet plug, clot formation, fibrin mesh", "Platelets"],
            ["Inflammation", "Day 1-4", "Vasodilation, WBC migration, phagocytosis, debridement", "Neutrophils (1st 48h), then Macrophages"],
            ["Proliferation", "Day 4 - 3 weeks", "Fibroblast migration, collagen synthesis (Type III first), angiogenesis, granulation tissue", "Fibroblasts, Endothelial cells"],
            ["Remodelling/Maturation", "3 wks - 2 yrs", "Type III collagen replaced by Type I, wound contracts, scar matures. Max tensile strength 80% at 3 months", "Myofibroblasts"],
        ],
        col_widths=[36*mm, 28*mm, 72*mm, 34*mm]
    ))
    story.append(sp(4))
    story.append(imp_box([
        "Collagen TYPE III produced first in granulation tissue -> replaced by Type I in remodelling",
        "Max wound tensile strength = 80% of normal (never 100%) - reached at ~3 months",
        "MACROPHAGES are the most important cells for wound healing overall",
        "Neutrophils dominate in first 48 hours; Macrophages take over after 48-72 hours",
        "Vitamin C deficiency -> poor collagen synthesis -> wound dehiscence (scurvy)",
        "Zinc deficiency -> impaired wound healing; Zinc is cofactor for DNA polymerase",
    ]))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Which type of collagen is first synthesised during wound healing? Ans: Type III (later replaced by Type I)",
        "Q: Maximum tensile strength of a healed wound is? Ans: 80% of original tissue strength",
        "Q: Most important cell in wound healing? Ans: Macrophage",
        "Q: Which vitamin is essential for collagen cross-linking in wound healing? Ans: Vitamin C (ascorbic acid)",
        "Q: Wound contraction is mediated by? Ans: Myofibroblasts",
    ]))
    story.append(sp(6))

    story.append(Paragraph("1.2  SHOCK", CH_SUB))
    story.append(data_table(
        ["Class", "Blood Loss", "% Blood Vol", "HR", "BP", "RR", "Urine Output", "Mental Status"],
        [
            ["Class I",   "<750 mL",    "<15%",  "<100", "Normal",   "14-20", ">30 mL/hr",  "Normal/anxious"],
            ["Class II",  "750-1500",   "15-30%", "100-120","Normal","20-30", "20-30 mL/hr","Anxious"],
            ["Class III", "1500-2000",  "30-40%", "120-140","Decreased","30-40","5-15 mL/hr","Confused"],
            ["Class IV",  ">2000 mL",   ">40%",   ">140",  "Very low","  >35", "<5 mL/hr",  "Lethargic/comatose"],
        ],
        col_widths=[18*mm,22*mm,18*mm,18*mm,22*mm,16*mm,22*mm,32*mm]
    ))
    story.append(sp(4))
    story.append(tip_box([
        "MNEMONIC for Shock Types: H-D-N-S = Hypovolaemic, Distributive (Septic/Anaphylactic/Neurogenic), Neurogenic, Spinal",
        "Obstructive shock: Tension pneumothorax, cardiac tamponade, massive PE",
        "Neurogenic shock: Bradycardia + Hypotension (unlike other shock types with tachycardia)",
        "First line for hypovolaemic shock: IV crystalloid (Ringer's Lactate) - 2 large bore cannulae",
    ]))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Neurogenic shock is characterised by? Ans: Bradycardia + hypotension (warm peripheries)",
        "Q: Best initial fluid for haemorrhagic shock? Ans: Ringer's Lactate (Hartmann's solution)",
        "Q: Urine output of <0.5 mL/kg/hr indicates? Ans: Inadequate tissue perfusion / shock",
        "Q: Beck's triad in cardiac tamponade? Ans: Hypotension, JVD (raised JVP), muffled heart sounds",
    ]))
    story.append(PageBreak())

    story.append(Paragraph("1.3  SURGICAL SITE INFECTION (SSI) & WOUND CLASSIFICATION", CH_SUB))
    story.append(data_table(
        ["Wound Class", "Definition", "Infection Risk"],
        [
            ["Class I - Clean",           "Elective, no GI/GU/Respiratory tract entered, no inflammation", "1-5%"],
            ["Class II - Clean-Contaminated", "GI/GU/Respiratory entered under controlled conditions", "5-15%"],
            ["Class III - Contaminated",  "Open fresh traumatic wound, gross spillage from GI tract", "15-30%"],
            ["Class IV - Dirty/Infected", "Old traumatic wound, perforated viscus, clinical infection present", ">30%"],
        ],
        col_widths=[52*mm, 88*mm, 28*mm]
    ))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Appendicectomy for non-perforated appendicitis = which wound class? Ans: Class II (Clean-Contaminated)",
        "Q: Elective cholecystectomy wound class? Ans: Class II",
        "Q: Prophylactic antibiotic for clean surgery? Ans: Not required routinely (Class I)",
        "Q: Most common organism in SSI? Ans: Staphylococcus aureus",
    ]))

    story.append(Paragraph("1.4  SUTURES & SURGICAL MATERIALS", CH_SUB))
    story.append(data_table(
        ["Suture", "Type", "Uses", "Absorption"],
        [
            ["Catgut (Plain)",    "Absorbable, natural",    "Mucosa, ligation",              "10-14 days"],
            ["Chromic Catgut",    "Absorbable, natural",    "GI, GU tracts",                 "21-28 days"],
            ["Vicryl (Polyglactin)", "Absorbable, synthetic","Fascial closure, subcutaneous","56-70 days"],
            ["PDS (Polydioxanone)","Absorbable, synthetic", "Abdominal wall, tendon repair", "180+ days"],
            ["Prolene (Polypropylene)","Non-absorbable, synthetic","Vascular anastomosis, hernia","Permanent"],
            ["Nylon (Ethilon)",   "Non-absorbable, synthetic","Skin closure, tendons",       "Permanent"],
            ["Silk",              "Non-absorbable, natural","Ligation, skin",                "Permanent (but degrades)"],
        ],
        col_widths=[42*mm, 40*mm, 55*mm, 31*mm]
    ))
    story.append(sp(4))
    story.append(imp_box([
        "Strongest suture per diameter: Prolene > Nylon > Silk",
        "Best suture for vascular anastomosis: Prolene (monofilament, non-thrombogenic)",
        "Absorbable suture NOT to use in infected field: Catgut (rapid degradation)",
        "DELAYED ABSORBABLE sutures (PDS, Maxon) preferred for abdominal wall closure",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 2 - TRAUMA & BURNS
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 2 - TRAUMA & EMERGENCY SURGERY"))
    story.append(sp(8))

    story.append(Paragraph("2.1  BURNS", CH_SUB))
    story.append(Paragraph("Rule of Nines (Wallace's Rule) - Adult", CH_SUB2))
    story.append(data_table(
        ["Body Region", "% TBSA", "Notes"],
        [
            ["Head + Neck",    "9%",   "Head 7% + Neck 2%"],
            ["Each Upper Limb","9% each (18% total)", "Arm 4% + Forearm 3% + Hand 2%"],
            ["Anterior Trunk", "18%",  "Chest 9% + Abdomen 9%"],
            ["Posterior Trunk","18%",  "Upper back 9% + Lower back 9%"],
            ["Each Lower Limb","18% each (36% total)","Thigh 9% + Leg 6% + Foot 3%"],
            ["Perineum/Genitalia","1%",""],
            ["TOTAL",          "100%", ""],
        ],
        col_widths=[55*mm, 60*mm, 55*mm]
    ))
    story.append(sp(4))
    story.append(tip_box([
        "Lund & Browder Chart: MORE ACCURATE than Rule of Nines, especially in CHILDREN",
        "Palmar method: Patient's palm (fingers included) = 1% TBSA - useful for patchy burns",
        "CHILDREN: Head proportionally larger (18% at birth) -> Berkow formula / Lund-Browder",
    ]))
    story.append(sp(4))
    story.append(Paragraph("Burns Depth Classification", CH_SUB2))
    story.append(data_table(
        ["Degree", "Depth", "Appearance", "Sensation", "Healing", "Treatment"],
        [
            ["1st Degree\n(Superficial)", "Epidermis only", "Red, dry, no blisters", "Painful", "3-5 days", "Conservative"],
            ["2nd Degree Superficial\n(Partial thickness)", "Epidermis + Superficial dermis", "Blisters, moist, pink", "Very painful", "14-21 days", "Dressings"],
            ["2nd Degree Deep\n(Deep partial thickness)", "Epidermis + Deep dermis", "Pale/mottled, less moist", "Reduced pain", "21-35 days, may need graft", "Grafting"],
            ["3rd Degree\n(Full thickness)", "All skin layers", "White/charred/leathery", "Painless", "No self-healing", "Excision + Grafting"],
            ["4th Degree", "Skin + subcutaneous tissue, muscle, bone", "Charred, eschar", "Painless", "Amputation/major reconstruction", "Surgical"],
        ],
        col_widths=[30*mm, 32*mm, 32*mm, 24*mm, 28*mm, 24*mm]
    ))
    story.append(sp(4))
    story.append(Paragraph("Fluid Resuscitation in Burns", CH_SUB2))
    story.append(box_table([
        [Paragraph("<b>Parkland Formula (Most used in India/NEET PG):</b>", BOLD_S)],
        [Paragraph("Total fluid in 24 hrs = 4 mL x Weight (kg) x % TBSA burn (2nd + 3rd degree only)", BODY)],
        [Paragraph("• Give HALF in first 8 hours (from time of burn, not from hospital arrival)", BODY)],
        [Paragraph("• Give REMAINING HALF over next 16 hours", BODY)],
        [Paragraph("• Fluid: Ringer's Lactate (Hartmann's solution)", BODY)],
        [Paragraph("<b>Muir & Barclay Formula:</b> (UK/older)", BOLD_S)],
        [Paragraph("= Weight (kg) x % TBSA / 2 = per period (6 periods: 4h, 4h, 4h, 6h, 6h, 12h)", BODY)],
        [Paragraph("• Fluid: Colloid (Human Albumin Solution / FFP)", BODY)],
    ]))
    story.append(sp(4))
    story.append(imp_box([
        "Parkland formula - fluid: Ringer's Lactate; Muir-Barclay formula - fluid: Colloid",
        "Children: Add maintenance fluid (dextrose saline) to Parkland formula",
        "Target urine output: Adult = 0.5-1 mL/kg/hr; Children = 1 mL/kg/hr",
        "Burns >15% TBSA in adults / >10% in children = MAJOR BURN requiring IV resuscitation",
        "Smoke inhalation injury = strong indication for early intubation",
        "Circumferential full-thickness burns -> ESCHAROTOMY to prevent compartment syndrome",
    ]))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Parkland formula for burn resuscitation? Ans: 4 mL x kg x % TBSA; half in first 8 hrs, RL solution",
        "Q: Rule of nines - TBSA of lower limb in adult? Ans: 18% each (9% thigh + 9% leg/foot)",
        "Q: Most accurate method for calculating burns in children? Ans: Lund and Browder Chart",
        "Q: Which type of burn is PAINLESS? Ans: Full thickness (3rd degree) - nerve endings destroyed",
        "Q: Earliest sign of adequate fluid resuscitation in burns? Ans: Adequate urine output (0.5 mL/kg/hr)",
        "Q: Escharotomy is done for? Ans: Circumferential full-thickness burns - to prevent compartment syndrome",
    ]))
    story.append(PageBreak())

    story.append(Paragraph("2.2  ATLS PRIMARY SURVEY (ABCDE)", CH_SUB))
    story.append(data_table(
        ["Step", "Stands For", "Action", "Key Points"],
        [
            ["A", "Airway + C-spine", "Clear airway, chin lift/jaw thrust, C-spine immobilisation", "Assume C-spine injury in all blunt trauma until proven otherwise"],
            ["B", "Breathing + Ventilation", "Look-listen-feel, O2, treat pneumothorax", "Life threats: Tension PTX, Open PTX, Haemothorax, Flail chest"],
            ["C", "Circulation + Haemorrhage", "2 large bore IVs, fluid resuscitation, control external bleeding", "FAST exam, pelvic binder if pelvic fracture"],
            ["D", "Disability (Neuro)", "GCS, pupils, glucose, AVPU scale", "GCS <8 -> intubate; unilateral dilated pupil = herniation"],
            ["E", "Exposure + Environment", "Undress patient, prevent hypothermia", "Log roll, check back and perineum"],
        ],
        col_widths=[12*mm, 38*mm, 62*mm, 58*mm]
    ))
    story.append(sp(4))
    story.append(Paragraph("2.3  TENSION PNEUMOTHORAX vs CARDIAC TAMPONADE", CH_SUB))
    story.append(two_col_table(
        ["Tracheal deviation AWAY from affected side",
         "Absent breath sounds on affected side",
         "Hypotension + tachycardia",
         "JVP raised",
         "Treatment: Immediate needle decompression (2nd ICS MCL), then chest drain"],
        ["Tracheal deviation - midline (no deviation)",
         "Heart sounds muffled",
         "Hypotension + tachycardia",
         "JVP raised (Beck's triad)",
         "Treatment: Pericardiocentesis (emergent), pericardial window"],
        "Tension Pneumothorax", "Cardiac Tamponade"
    ))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Triad of cardiac tamponade (Beck's triad)? Ans: Hypotension, raised JVP, muffled heart sounds",
        "Q: Kussmaul's sign is seen in? Ans: Cardiac tamponade (JVP rises on inspiration)",
        "Q: Treatment of tension pneumothorax? Ans: Immediate needle decompression - 2nd ICS midclavicular line",
        "Q: Most common cause of haemothorax in trauma? Ans: Intercostal vessel injury",
        "Q: Flail chest definition? Ans: 3+ consecutive ribs fractured at 2+ sites each - paradoxical movement",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 3 - GI SURGERY
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 3 - GASTROINTESTINAL SURGERY"))
    story.append(sp(8))

    story.append(Paragraph("3.1  ACUTE APPENDICITIS", CH_SUB))
    story.append(box_table([
        [Paragraph("<b>Classic Presentation:</b> Central colicky pain -> shifting to RIF (McBurney's point) + fever + nausea/vomiting", BODY)],
        [Paragraph("<b>McBurney's Point:</b> Junction of lateral 1/3 and medial 2/3 of line joining ASIS to umbilicus", BODY)],
        [Paragraph("<b>Rovsing's Sign:</b> Pressure on LIF causes pain in RIF (peritoneal irritation)", BODY)],
        [Paragraph("<b>Psoas Sign:</b> Pain on extending right hip (retrocaecal appendix)", BODY)],
        [Paragraph("<b>Obturator Sign:</b> Pain on internal rotation of flexed right hip (pelvic appendix)", BODY)],
    ], bg=C_LIGHT))
    story.append(sp(4))
    story.append(Paragraph("Alvarado Score (MANTRELS)", CH_SUB2))
    story.append(data_table(
        ["Criterion", "Score"],
        [
            ["Migration of pain to RIF", "1"],
            ["Anorexia", "1"],
            ["Nausea/Vomiting", "1"],
            ["Tenderness in RIF", "2"],
            ["Rebound tenderness", "1"],
            ["Elevated temperature (>37.3°C)", "1"],
            ["Leukocytosis (WBC >10,000)", "2"],
            ["Shift to left (neutrophilia)", "1"],
            ["TOTAL", "10"],
        ],
        col_widths=[130*mm, 38*mm]
    ))
    story.append(sp(4))
    story.append(tip_box([
        "MANTRELS mnemonic: Migration, Anorexia, Nausea, Tenderness RIF, Rebound, Elevated Temp, Leukocytosis, Shift left",
        "Score 7-10 = High probability -> Surgery; Score 5-6 = Observe; Score <5 = Low probability",
        "Score of 2 each for: RIF Tenderness + Leukocytosis (highest weighted criteria)",
    ]))
    story.append(sp(4))
    story.append(imp_box([
        "Best investigation for appendicitis: CT scan (most accurate 94-98% sensitivity)",
        "Preferred in children/pregnancy: Ultrasound first (no radiation), then MRI",
        "Position of appendix most common: Retrocaecal (65%)",
        "Pelvic appendix -> Dysuria, frequency (mimics UTI)",
        "Perforation risk increases dramatically after 24-36 hours",
        "Laparoscopic appendicectomy = gold standard (less infection, faster recovery)",
    ]))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Most common position of appendix? Ans: Retrocaecal (65%)",
        "Q: Best investigation for appendicitis? Ans: CT scan (most accurate); USG first in children/pregnant",
        "Q: Alvarado score of 7-10 indicates? Ans: High probability appendicitis - proceed to surgery",
        "Q: Rovsing's sign is? Ans: Pressure on LIF causes pain in RIF",
        "Q: Appendicectomy incision? Ans: Grid-iron incision (Lanz incision for cosmesis)",
    ]))
    story.append(sp(6))

    story.append(Paragraph("3.2  INTESTINAL OBSTRUCTION", CH_SUB))
    story.append(two_col_table(
        ["Most common cause adult small bowel: Adhesions (post-op)",
         "Most common cause large bowel: Carcinoma",
         "Features: Colicky pain, vomiting, distension, constipation",
         "High obstruction: Vomiting early, distension mild",
         "Low obstruction: Vomiting late/feculent, distension marked",
         "X-ray: Dilated loops, air-fluid levels, step-ladder pattern",
         "Small bowel: Valvulae conniventes (cross whole width)",
         "Large bowel: Haustra (partial width)",
         "Treatment: NBM, NGT, IV fluids, then surgery if needed"],
        ["Strangulation signs: Continuous pain (not colicky), fever, peritonism",
         "Closed loop obstruction: Most dangerous - rapid vascular compromise",
         "Volvulus: Sigmoid (most common) or Caecal",
         "Sigmoid volvulus X-ray: Coffee bean/bent inner tube sign",
         "Caecal volvulus X-ray: Kidney bean sign",
         "Intussusception: Children 6mo-2yr, currant jelly stools",
         "Richter's hernia: Knuckle of bowel - no complete obstruction",
         "Gallstone ileus: Air in biliary tree (pneumobilia)",
         "Ogilvie's syndrome: Pseudo-obstruction of colon (no mechanical cause)"],
        "Mechanical Obstruction Features", "Important Subtypes"
    ))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Most common cause of small bowel obstruction in adults? Ans: Adhesions (post-operative)",
        "Q: Most common cause of large bowel obstruction? Ans: Carcinoma of colon",
        "Q: Currant jelly stools in a child suggests? Ans: Intussusception",
        "Q: Coffee bean sign on X-ray? Ans: Sigmoid volvulus",
        "Q: Gallstone ileus - pathognomonic finding on X-ray? Ans: Air in biliary tree (pneumobilia / Rigler's triad)",
        "Q: Intussusception treatment in children? Ans: Air/hydrostatic enema reduction (first line); Surgery if failed/peritonitis",
    ]))
    story.append(PageBreak())

    story.append(Paragraph("3.3  PEPTIC ULCER DISEASE", CH_SUB))
    story.append(two_col_table(
        ["DU: Pain relieved by food (Hunger pain)",
         "DU: Hypersecretory state",
         "DU: More common (4x than GU)",
         "DU: Posterior DU -> bleeds from Gastroduodenal artery",
         "DU: Anterior DU -> perforates (peritonitis)",
         "DU: H. pylori in 95-100%",
         "DU: Rarely malignant"],
        ["GU: Pain WORSENED by food (Fear of food)",
         "GU: Normal/hypo secretory state",
         "GU: Less common, but ALWAYS exclude malignancy",
         "GU: Posterior GU -> bleeds from Left Gastric artery",
         "GU: Lesser curve most common site",
         "GU: H. pylori in 70-80%",
         "GU: 5% risk of malignancy - always biopsy"],
        "Duodenal Ulcer (DU)", "Gastric Ulcer (GU)"
    ))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Artery eroded in bleeding posterior DU? Ans: Gastroduodenal artery",
        "Q: Artery eroded in bleeding lesser curve GU? Ans: Left gastric artery",
        "Q: Most common complication of peptic ulcer? Ans: Bleeding (haemorrhage)",
        "Q: Most common site of perforation in PUD? Ans: Anterior wall of first part of duodenum",
        "Q: H. pylori eradication regimen (Triple therapy)? Ans: PPI + Amoxicillin + Clarithromycin x 7-14 days",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 4 - HEPATOBILIARY
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 4 - HEPATOBILIARY & PANCREATIC SURGERY"))
    story.append(sp(8))

    story.append(Paragraph("4.1  GALLSTONES (CHOLELITHIASIS)", CH_SUB))
    story.append(data_table(
        ["Type", "Composition", "Association", "X-ray Visible?"],
        [
            ["Cholesterol stones", "Cholesterol >50%", "Obesity, OCP, Pregnancy, Female, 40yr (5 F's)", "No (80% radiolucent)"],
            ["Pigment - Black stones", "Calcium bilirubinate", "Haemolytic anaemia, Cirrhosis", "Yes (radio-opaque)"],
            ["Pigment - Brown stones", "Calcium bilirubinate + fatty acids", "Bacterial/parasitic infection, bile stasis", "Partially"],
            ["Mixed stones", "Cholesterol + Pigment", "Most common type (80%)", "Variable"],
        ],
        col_widths=[40*mm, 42*mm, 56*mm, 32*mm]
    ))
    story.append(sp(4))
    story.append(tip_box([
        "5 F's of cholesterol gallstones: Fat, Female, Fertile, Forty, Fair (Caucasian)",
        "Charcot's triad of cholangitis: Fever + Jaundice + RUQ Pain",
        "Reynold's pentad: Charcot's triad + Hypotension + Confusion (severe cholangitis/sepsis)",
        "Courvoisier's Law: Palpable GB + painless jaundice = NOT gallstones (= periampullary malignancy)",
        "Murphy's sign: Cessation of inspiration on deep palpation of RUQ (acute cholecystitis)",
    ]))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Charcot's triad of cholangitis? Ans: Fever, Jaundice, RUQ Pain",
        "Q: Courvoisier's law? Ans: Palpable GB + painless jaundice usually NOT due to stones (implies malignancy)",
        "Q: Best investigation for gallstones? Ans: Ultrasound (USG) - gold standard",
        "Q: Treatment of choice for symptomatic gallstones? Ans: Laparoscopic cholecystectomy",
        "Q: ERCP is done for? Ans: Common bile duct stones (CBD stones), before/after cholecystectomy",
        "Q: Mirizzi syndrome? Ans: External compression of CHD by stone in cystic duct/Hartmann's pouch -> jaundice",
    ]))
    story.append(sp(6))

    story.append(Paragraph("4.2  ACUTE PANCREATITIS", CH_SUB))
    story.append(box_table([
        [Paragraph("<b>Common causes (GET SMASHED):</b> Gallstones (40%), Ethanol (35%), Trauma, Steroids, Mumps/Autoimmune, Scorpion/Spider venom, Hyperlipidaemia/Hypercalcaemia, ERCP/Emboli, Drugs (azathioprine, thiazides)", BODY)],
    ], bg=C_LYELLOW, border_color=C_ORANGE))
    story.append(sp(4))
    story.append(Paragraph("Ranson's Criteria (prognostic scoring)", CH_SUB2))
    story.append(data_table(
        ["At Admission", "At 48 Hours"],
        [
            ["Age >55 years", "Haematocrit fall >10%"],
            ["WBC >16,000/mm3", "BUN rise >5 mg/dL"],
            ["Blood glucose >200 mg/dL", "Serum Ca <8 mg/dL"],
            ["LDH >350 IU/L", "PaO2 <60 mmHg"],
            ["AST >250 IU/L", "Base deficit >4 mEq/L"],
            ["", "Fluid sequestration >6 L"],
        ],
        col_widths=[85*mm, 85*mm]
    ))
    story.append(sp(4))
    story.append(imp_box([
        "Ranson score: <3 = mild; 3-5 = moderate; >5 = severe (>6 = near 100% mortality)",
        "Best imaging for pancreatitis complications: CT scan (CECT abdomen)",
        "CT Severity Index (Balthazar score): Grade A-E based on CT findings",
        "Cullen's sign: Periumbilical bruising (haemorrhagic pancreatitis - retroperitoneal bleed)",
        "Grey-Turner's sign: Flank bruising (same significance)",
        "Amylase vs Lipase: Lipase is MORE SPECIFIC for acute pancreatitis",
        "Pancreatic necrosis + infection -> Infected necrotising pancreatitis -> Surgery / Drainage",
    ]))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Most common cause of acute pancreatitis in India? Ans: Gallstones",
        "Q: Most specific enzyme for pancreatitis? Ans: Lipase (more specific than amylase)",
        "Q: Cullen's sign is seen in? Ans: Haemorrhagic pancreatitis (periumbilical bruising)",
        "Q: Ranson score >5 suggests? Ans: Severe pancreatitis with high mortality",
        "Q: Most common complication of acute pancreatitis? Ans: Pancreatic pseudocyst",
        "Q: Pseudocyst management if >6cm and persistent >6wks? Ans: Internal drainage (cystogastrostomy)",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 5 - BREAST SURGERY
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 5 - BREAST SURGERY"))
    story.append(sp(8))

    story.append(Paragraph("5.1  BREAST LUMPS - DIFFERENTIAL DIAGNOSIS", CH_SUB))
    story.append(data_table(
        ["Condition", "Age", "Features", "Consistency"],
        [
            ["Fibroadenoma", "15-30 yrs", "'Breast mouse' - mobile, smooth, well-defined, non-tender, no skin changes", "Firm, rubbery"],
            ["Fibrocystic disease\n(ANDI)", "30-50 yrs", "Cyclical pain/tenderness, multiple lumps, worse pre-menstrual, bilateral", "Nodular"],
            ["Breast Cyst",   "35-55 yrs", "Smooth, well-defined, tense, transilluminates, aspirated", "Cystic/firm"],
            ["Carcinoma",     ">40 yrs",   "Hard, irregular, poorly defined, skin tethering, nipple retraction, LN involved", "Hard, stony"],
            ["Abscess/Mastitis", "Lactating women", "Red, hot, tender, fluctuant, fever, WBC raised", "Fluctuant"],
            ["Fat Necrosis",  "Any age (trauma)", "History of trauma, hard lump, skin retraction - mimics CA", "Hard"],
        ],
        col_widths=[38*mm, 26*mm, 72*mm, 32*mm]
    ))
    story.append(sp(4))
    story.append(Paragraph("5.2  BREAST CARCINOMA", CH_SUB))
    story.append(imp_box([
        "Most common breast cancer histological type: Invasive Ductal Carcinoma (IDC) - 75-80%",
        "Most common site: Upper outer quadrant (50%)",
        "Inflammatory breast cancer: Peau d'orange skin (dermal lymphatic invasion), worst prognosis",
        "BRCA1 mutation: Breast + Ovarian cancer risk; BRCA2: Breast + Pancreatic/Prostate cancer",
        "Triple assessment for breast lump: Clinical examination + Imaging (USG/Mammography) + FNAC/Biopsy",
        "Sentinel lymph node biopsy: First node to drain tumour - if negative, avoids axillary dissection",
    ]))
    story.append(sp(4))
    story.append(Paragraph("Breast Cancer Staging (TNM Summary)", CH_SUB2))
    story.append(data_table(
        ["Stage", "TNM", "Features", "5-yr Survival"],
        [
            ["Stage I",   "T1, N0, M0", "Tumour <2cm, no node involvement, no mets", "~95%"],
            ["Stage IIA", "T0-2, N1, M0 or T2N0", "Mobile ipsilateral axillary nodes or T2 no nodes", "~85%"],
            ["Stage IIB", "T2N1 or T3N0", "T2 + mobile nodes, or T3 no nodes", "~70%"],
            ["Stage IIIA", "T0-3, N2, M0 or T3N1", "Fixed axillary nodes", "~55%"],
            ["Stage IIIB", "T4, any N, M0", "Chest wall/skin involvement (incl inflammatory)", "~40%"],
            ["Stage IV",  "Any T, Any N, M1", "Distant metastases", "~25%"],
        ],
        col_widths=[20*mm, 38*mm, 72*mm, 28*mm]
    ))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Most common type of breast cancer? Ans: Invasive Ductal Carcinoma (IDC)",
        "Q: Most common site of breast cancer? Ans: Upper outer quadrant",
        "Q: Paget's disease of nipple is associated with? Ans: Underlying intraductal carcinoma",
        "Q: Triple assessment of breast lump? Ans: Clinical exam + Imaging + Pathology (FNAC/Biopsy)",
        "Q: Sentinel lymph node drainage site for breast? Ans: Axillary nodes (level I first)",
        "Q: Tamoxifen is used in? Ans: ER/PR positive breast cancer (pre and post-menopausal); SERM",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 6 - THYROID & PARATHYROID
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 6 - THYROID & PARATHYROID SURGERY"))
    story.append(sp(8))

    story.append(Paragraph("6.1  THYROID CANCER - TYPES & FEATURES", CH_SUB))
    story.append(data_table(
        ["Type", "Incidence", "Age/Sex", "Spread", "Prognosis", "Special Features"],
        [
            ["Papillary", "70-80% (most common)", "Young females", "Lymphatic (LN)", "Excellent (>95% 10yr)", "Psammoma bodies, Orphan Annie eye nuclei, Intranuclear inclusions"],
            ["Follicular", "15-20%", "Middle age", "Haematogenous (lung, bone)", "Good", "Vascular invasion diagnostic; not diagnose by FNAC (capsule needed)"],
            ["Medullary", "5%", "Familial (MEN 2A/2B)", "Both LN + haematogenous", "Moderate", "Calcitonin as tumour marker; amyloid deposits; RET proto-oncogene"],
            ["Anaplastic", "<5% (rarest)", "Elderly", "Local invasion + widespread", "Very poor (<6 months)", "Most aggressive; radio-resistant; airway compromise"],
        ],
        col_widths=[26*mm, 28*mm, 26*mm, 30*mm, 26*mm, 32*mm]
    ))
    story.append(sp(4))
    story.append(imp_box([
        "Most common thyroid cancer: Papillary (70-80%)",
        "Best prognosis: Papillary > Follicular > Medullary > Anaplastic (worst)",
        "Psammoma bodies seen in: Papillary thyroid CA, Meningioma, Serous papillary ovarian CA",
        "MEN 2A: Medullary thyroid CA + Phaeochromocytoma + Primary hyperparathyroidism",
        "MEN 2B: Medullary thyroid CA + Phaeochromocytoma + Mucosal neuromas + Marfanoid habitus",
        "Calcitonin = tumour marker for Medullary thyroid carcinoma",
        "Recurrent laryngeal nerve (RLN) injury during thyroid surgery -> hoarseness",
        "Bilateral RLN injury -> stridor, respiratory distress - EMERGENCY tracheotomy needed",
    ]))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Most common thyroid cancer? Ans: Papillary carcinoma",
        "Q: Psammoma bodies are seen in which thyroid cancer? Ans: Papillary carcinoma",
        "Q: Tumour marker for medullary thyroid cancer? Ans: Calcitonin",
        "Q: Follicular carcinoma is diagnosed by? Ans: Histopathology (capsular/vascular invasion) - NOT by FNAC",
        "Q: Most aggressive thyroid cancer? Ans: Anaplastic (undifferentiated) carcinoma",
        "Q: MEN 2A components? Ans: Medullary thyroid CA + Phaeochromocytoma + Hyperparathyroidism",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 7 - HERNIA
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 7 - HERNIA"))
    story.append(sp(8))

    story.append(Paragraph("7.1  INGUINAL HERNIA - INDIRECT vs DIRECT", CH_SUB))
    story.append(two_col_table(
        ["Through deep inguinal ring -> inguinal canal -> superficial ring",
         "Younger age group (congenital persistent processus vaginalis)",
         "More common overall (3:1 ratio over direct)",
         "Lateral to inferior epigastric vessels",
         "Covered by all three layers of spermatic cord",
         "Can descend into scrotum",
         "Higher risk of strangulation",
         "Hesselbach's triangle: Lateral border"],
        ["Through Hesselbach's triangle (posterior wall weakness)",
         "Older age (acquired - weakness of transversalis fascia)",
         "Less common than indirect",
         "Medial to inferior epigastric vessels",
         "Not covered by internal spermatic fascia",
         "Rarely descends into scrotum",
         "Lower risk of strangulation",
         "Hesselbach's triangle: Medial border"],
        "INDIRECT Inguinal Hernia", "DIRECT Inguinal Hernia"
    ))
    story.append(sp(4))
    story.append(box_table([
        [Paragraph("<b>Hesselbach's Triangle boundaries:</b> Medial = Lateral border of rectus abdominis | Lateral = Inferior epigastric vessels | Inferior = Inguinal ligament", BODY)],
        [Paragraph("<b>Inguinal canal boundaries:</b> Anterior wall = External oblique aponeurosis | Posterior wall = Transversalis fascia (+ conjoined tendon medially) | Roof = Transversus + internal oblique | Floor = Inguinal ligament", BODY)],
    ]))
    story.append(sp(4))

    story.append(Paragraph("7.2  FEMORAL HERNIA", CH_SUB))
    story.append(box_table([
        [Paragraph("<b>Site:</b> Through femoral ring, femoral canal - BELOW and LATERAL to pubic tubercle", BODY)],
        [Paragraph("<b>Demographics:</b> More common in women (due to wider pelvis) but inguinal hernia is STILL more common in women overall", BODY)],
        [Paragraph("<b>Neck of femoral ring boundaries:</b> Medially = Lacunar ligament | Laterally = Femoral vein | Anteriorly = Inguinal ligament | Posteriorly = Pectineal ligament (Cooper's ligament)", BODY)],
        [Paragraph("<b>High strangulation risk</b> due to narrow, unyielding neck (lacunar ligament medially)", BODY)],
    ]))
    story.append(sp(4))

    story.append(Paragraph("7.3  SPECIAL HERNIAS (HIGH YIELD!)", CH_SUB))
    story.append(data_table(
        ["Type", "Definition", "Clinical Significance"],
        [
            ["Richter's Hernia", "Only antimesenteric wall of bowel in sac (knuckle) - NO complete obstruction", "Can strangulate WITHOUT obstruction - DANGEROUS, easily missed"],
            ["Littre's Hernia", "Meckel's diverticulum in hernial sac", "Diverticulum strangulates"],
            ["Maydl's Hernia\n(W hernia)", "Two loops of bowel in sac forming W shape - middle loop inside abdomen strangulates", "Dangerous - intraabdominal loop strangulates unnoticed"],
            ["Spigelian Hernia", "Through spigelian fascia (lateral border of rectus, at linea semilunaris)", "Interparietal hernia - difficult to detect clinically"],
            ["Obturator Hernia", "Through obturator foramen - elderly thin women", "Howship-Romberg sign: medial thigh pain radiating on hip movement"],
            ["Sliding Hernia\n(en Glissade)", "Wall of viscus forms part of the sac", "Sigmoid colon (left) or caecum (right) most common"],
            ["Pantaloon Hernia", "Combined direct + indirect hernia straddling inferior epigastric vessels", "Both medial and lateral components"],
        ],
        col_widths=[38*mm, 72*mm, 58*mm]
    ))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Which hernia can strangulate without obstruction? Ans: Richter's hernia",
        "Q: Littre's hernia contains? Ans: Meckel's diverticulum",
        "Q: Howship-Romberg sign is seen in? Ans: Obturator hernia",
        "Q: Femoral hernia passes below which landmark? Ans: Below and lateral to pubic tubercle",
        "Q: Inguinal hernia passes above which landmark? Ans: Above and medial to pubic tubercle",
        "Q: Most common type of hernia in females? Ans: Inguinal hernia (indirect) - inguinal > femoral in females too",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 8 - UROLOGY
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 8 - UROLOGY"))
    story.append(sp(8))

    story.append(Paragraph("8.1  URINARY STONES (UROLITHIASIS)", CH_SUB))
    story.append(data_table(
        ["Stone Type", "% of Stones", "Radio-opacity", "Associations", "Urine pH"],
        [
            ["Calcium Oxalate\n(most common)", "70-80%", "Radio-opaque", "Hypercalciuria, hyperoxaluria, Crohn's disease", "Acidic"],
            ["Uric Acid", "5-10%", "Radiolucent (pure)", "Gout, dehydration, high purine diet, myeloproliferative", "Acidic (<5.5)"],
            ["Struvite (triple phosphate)", "10-15%", "Radio-opaque (staghorn)", "Urease-producing organisms (Proteus, Klebsiella)", "Alkaline (>7)"],
            ["Cystine", "1-3%", "Faintly opaque", "Cystinuria (AR) - defective tubular reabsorption", "Acidic"],
            ["Calcium Phosphate", "5-10%", "Radio-opaque", "Hyperparathyroidism, RTA type I", "Alkaline"],
        ],
        col_widths=[32*mm, 20*mm, 28*mm, 58*mm, 26*mm]
    ))
    story.append(sp(4))
    story.append(tip_box([
        "Most radio-opaque: Calcium oxalate > Calcium phosphate > Struvite > Cystine > Uric acid (radiolucent)",
        "Staghorn calculi = Struvite stones (fill renal pelvis + calyces)",
        "Treatment of uric acid stones: Urinary alkalinisation (potassium citrate) + hydration",
        "First-line investigation: KUB X-ray + USG; CT-KUB (non-contrast) = gold standard",
        "ESWL (Extracorporeal Shock Wave Lithotripsy): Best for stones <2cm in renal pelvis",
        "PCNL (Percutaneous Nephrolithotomy): Stones >2cm or staghorn calculi",
    ]))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Most common renal stone? Ans: Calcium oxalate (70-80%)",
        "Q: Only radiolucent stone on plain X-ray? Ans: Uric acid stone",
        "Q: Staghorn calculus is composed of? Ans: Struvite (magnesium ammonium phosphate - triple phosphate)",
        "Q: Organism causing struvite stones? Ans: Proteus mirabilis (urease-producing)",
        "Q: ESWL is suitable for stones of what size? Ans: <2 cm in renal pelvis",
        "Q: Investigation of choice for ureteric colic? Ans: Non-contrast CT-KUB (NCCT abdomen)",
    ]))
    story.append(sp(6))

    story.append(Paragraph("8.2  BPH (BENIGN PROSTATIC HYPERPLASIA)", CH_SUB))
    story.append(box_table([
        [Paragraph("<b>Zone affected:</b> Transitional zone (central) | Prostate CA affects Peripheral zone", BODY)],
        [Paragraph("<b>Features - LUTS:</b> Frequency, urgency, nocturia, poor stream, hesitancy, terminal dribbling, incomplete emptying", BODY)],
        [Paragraph("<b>PSA:</b> Raised (but not diagnostic of CA alone - also raised in BPH, prostatitis, UTI)", BODY)],
        [Paragraph("<b>Rectal exam:</b> Enlarged, smooth, firm, non-tender, median groove preserved (vs CA: hard, irregular, nodular)", BODY)],
        [Paragraph("<b>Treatment:</b> Alpha-blockers (tamsulosin, alfuzosin) first line for symptoms | 5-alpha reductase inhibitors (finasteride) for large glands | TURP (gold standard surgical treatment)", BODY)],
    ]))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Zone of prostate affected in BPH? Ans: Transitional (central) zone",
        "Q: Zone affected in prostate carcinoma? Ans: Peripheral zone",
        "Q: Gold standard surgical treatment of BPH? Ans: TURP (TransUrethral Resection of Prostate)",
        "Q: TUR syndrome is caused by? Ans: Absorption of hypotonic irrigation fluid -> dilutional hyponatraemia",
        "Q: First line medical treatment of BPH? Ans: Alpha-1 blockers (tamsulosin, alfuzosin)",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 9 - VASCULAR SURGERY
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 9 - VASCULAR SURGERY"))
    story.append(sp(8))

    story.append(Paragraph("9.1  ABDOMINAL AORTIC ANEURYSM (AAA)", CH_SUB))
    story.append(box_table([
        [Paragraph("<b>Definition:</b> Dilatation of aorta >3 cm (normal <2.5cm) | TRUE aneurysm involves all 3 layers", BODY)],
        [Paragraph("<b>Risk factors:</b> Atherosclerosis, Smoking (strongest RF), Male, Age >65, Hypertension, Family history", BODY)],
        [Paragraph("<b>Most common site:</b> Infrarenal aorta (90%)", BODY)],
        [Paragraph("<b>Indications for surgery:</b> >5.5 cm | Rapidly expanding (>1 cm/year) | Symptomatic | Ruptured", BODY)],
        [Paragraph("<b>Ruptured AAA triad:</b> Sudden severe back/flank pain + Hypotension + Pulsatile abdominal mass", BODY)],
        [Paragraph("<b>Treatment:</b> EVAR (Endovascular Aneurysm Repair) preferred if anatomy suitable; Open repair alternatively", BODY)],
    ]))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Most common site of AAA? Ans: Infrarenal aorta",
        "Q: When is elective AAA repair indicated? Ans: Diameter >5.5 cm or expanding >1 cm/year",
        "Q: Classical triad of ruptured AAA? Ans: Sudden back pain + Hypotension + Pulsatile abdominal mass",
        "Q: Most common cause of AAA? Ans: Atherosclerosis",
    ]))
    story.append(sp(6))

    story.append(Paragraph("9.2  DEEP VEIN THROMBOSIS (DVT) & PULMONARY EMBOLISM", CH_SUB))
    story.append(data_table(
        ["Feature", "DVT", "Pulmonary Embolism"],
        [
            ["Presentation", "Unilateral leg swelling, pain, warmth, Homan's sign (unreliable)", "Dyspnoea, pleuritic chest pain, haemoptysis, tachycardia"],
            ["Investigation", "Doppler USG (first line); D-dimer screening", "CTPA (gold standard); V/Q scan; ECG: S1Q3T3"],
            ["Treatment", "LMWH/Heparin -> Warfarin/DOAC for 3-6 months; compression stockings", "Anticoagulation; Thrombolysis if haemodynamically unstable; IVC filter"],
            ["Prophylaxis", "LMWH, early mobilisation, compression stockings, hydration", "Same as DVT prophylaxis"],
        ],
        col_widths=[28*mm, 70*mm, 70*mm]
    ))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: ECG finding in massive PE? Ans: S1Q3T3 pattern (S wave in lead I, Q wave and T inversion in lead III)",
        "Q: Gold standard investigation for PE? Ans: CT Pulmonary Angiography (CTPA)",
        "Q: Virchow's triad for DVT? Ans: Stasis + Endothelial injury + Hypercoagulability",
        "Q: Most common source of pulmonary embolism? Ans: DVT of lower limb (femoral/iliac veins)",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 10 - PAEDIATRIC SURGERY
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 10 - PAEDIATRIC SURGERY"))
    story.append(sp(8))

    story.append(data_table(
        ["Condition", "Age", "Presentation", "Investigation", "Treatment"],
        [
            ["Pyloric Stenosis", "2-6 weeks (M>F 4:1)", "Projectile non-bilious vomiting, 'olive' mass, hungry baby", "USG (pyloric muscle thickness >4mm, length >16mm); Metabolic alkalosis", "Ramstedt's pyloromyotomy (after correction of electrolytes)"],
            ["Intussusception", "6 months-2 years", "Colicky pain, vomiting, currant jelly stools, sausage mass in RUQ", "USG: Target sign / Doughnut sign", "Air/hydrostatic enema (first line); Surgery if failed or peritonitis"],
            ["Hirschsprung's Disease", "Neonates/infants", "Delayed meconium passage (>48hrs), abdominal distension, ribbon stools", "Rectal biopsy (gold standard): absence of ganglion cells; Anorectal manometry", "Surgical pull-through procedure (Swenson/Duhamel/Soave)"],
            ["Congenital Diaphragmatic Hernia (CDH)", "Neonate", "Respiratory distress, scaphoid abdomen, bowel sounds in chest", "CXR: bowel in chest", "Stabilise first, then surgical repair; Left side more common (Bochdalek)"],
            ["Tracheo-Oesophageal Fistula (TOF)", "Neonate", "Coughing/choking on feeding, respiratory distress, copious secretions", "NGT coiling on CXR; H-type detected by contrast study", "Surgical repair; most common type C (blind upper pouch + fistula lower)"],
            ["Meckel's Diverticulum", "Any age (usually 2 yrs)", "Rule of 2s: 2% pop, 2 inches long, 2 feet from ileocaecal valve, 2x more in males", "Tc-99m pertechnetate scan (ectopic gastric mucosa)", "Surgical excision if symptomatic"],
        ],
        col_widths=[36*mm, 24*mm, 44*mm, 36*mm, 38*mm]
    ))
    story.append(sp(4))
    story.append(imp_box([
        "Pyloric stenosis: Metabolic alkalosis with hypochloraemia and hypokalaemia - correct BEFORE surgery",
        "Hirschsprung's disease: Absent ganglion cells in Meissner's and Auerbach's plexuses (gold standard = rectal biopsy)",
        "Meckel's Rule of 2s: 2% population, 2 inches, 2 feet from ileocaecal valve, presents before age 2",
        "Most common site for ectopic tissue in Meckel's: Gastric mucosa (causes bleeding)",
        "Most common type of TOF: Type C (85%) - proximal oesophageal atresia + distal tracheo-oesophageal fistula",
    ]))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Meckel's diverticulum - rule of 2s? Ans: 2% population, 2 inches, 2 feet from IC valve, M:F = 2:1",
        "Q: Diagnosis of Hirschsprung's disease? Ans: Rectal biopsy showing absent ganglion cells",
        "Q: Currant jelly stools are characteristic of? Ans: Intussusception",
        "Q: Investigation for pyloric stenosis? Ans: USG (muscle thickness >4mm); Metabolic alkalosis on bloods",
        "Q: Technetium scan is used for? Ans: Meckel's diverticulum (ectopic gastric mucosa)",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 11 - ONCOLOGY
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 11 - SURGICAL ONCOLOGY"))
    story.append(sp(8))

    story.append(Paragraph("11.1  TUMOUR MARKERS", CH_SUB))
    story.append(data_table(
        ["Tumour Marker", "Associated Tumour", "Notes"],
        [
            ["CEA (Carcinoembryonic Antigen)", "Colorectal CA (primary monitoring)", "Also: gastric, pancreatic, breast, lung CA; smokers"],
            ["AFP (Alpha-fetoprotein)", "Hepatocellular CA, Germ cell tumours (non-seminoma)", "Also elevated in pregnancy, liver disease"],
            ["PSA (Prostate Specific Antigen)", "Prostate carcinoma", "Also raised in BPH, prostatitis; organ-specific not cancer-specific"],
            ["CA 19-9", "Pancreatic CA (primary), biliary CA", "Best tumour marker for pancreatic CA monitoring"],
            ["CA 125", "Ovarian CA (epithelial)", "Also in endometriosis, fibroids, pelvic inflammation"],
            ["CA 15-3", "Breast carcinoma", "Used for monitoring, not screening"],
            ["Calcitonin", "Medullary thyroid carcinoma", "Also used to screen family members (MEN 2)"],
            ["Beta-hCG", "Choriocarcinoma, Gestational trophoblastic disease, Testicular CA (non-seminoma)", ""],
            ["LDH", "Seminoma, Lymphoma, Ewing's sarcoma", "Non-specific marker"],
            ["S-100", "Melanoma, Schwannoma, Astrocytoma", "Neural crest cell tumours"],
        ],
        col_widths=[48*mm, 72*mm, 48*mm]
    ))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: Tumour marker for pancreatic carcinoma? Ans: CA 19-9",
        "Q: Tumour marker for hepatocellular carcinoma? Ans: AFP (alpha-fetoprotein)",
        "Q: Best marker for monitoring colorectal cancer? Ans: CEA",
        "Q: Tumour marker for medullary thyroid cancer? Ans: Calcitonin",
        "Q: Which tumour marker is raised in seminoma? Ans: LDH (AFP and beta-hCG typically negative in pure seminoma)",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # CHAPTER 12 - INSTRUMENTS & PROCEDURES
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  CHAPTER 12 - SURGICAL INSTRUMENTS & PROCEDURES"))
    story.append(sp(8))

    story.append(Paragraph("12.1  KEY SURGICAL DRAINS", CH_SUB))
    story.append(data_table(
        ["Drain", "Type", "Uses"],
        [
            ["Corrugated rubber drain", "Passive, open", "Superficial wounds, subcutaneous drains"],
            ["Robinson drain (straight tube)", "Active closed (suction)", "Post-op abdominal, orthopaedic surgery"],
            ["Jackson-Pratt (JP)", "Active closed (bulb suction)", "After mastectomy, neck dissection, TRAM flap"],
            ["Blake drain", "Active closed", "Thoracic, cardiac surgery"],
            ["Chest drain (intercostal)", "Water-seal or Heimlich valve", "Haemothorax, pneumothorax, pleural effusion"],
            ["Sump drain (double lumen)", "Active irrigation + drainage", "Subphrenic abscess, bile leaks"],
            ["T-tube drain", "Passive", "CBD after choledochotomy for stones"],
        ],
        col_widths=[48*mm, 45*mm, 75*mm]
    ))
    story.append(sp(4))
    story.append(pyq_box([
        "Q: T-tube drain is used after? Ans: Choledochotomy (CBD exploration for stones) - maintains bile drainage",
        "Q: Drain used after mastectomy? Ans: Jackson-Pratt drain (closed suction)",
        "Q: Chest drain goes through which space? Ans: 5th ICS, midaxillary line (safe triangle)",
    ]))
    story.append(sp(6))

    story.append(Paragraph("12.2  STERILISATION METHODS", CH_SUB))
    story.append(data_table(
        ["Method", "Temperature", "Best For", "Cannot Use For"],
        [
            ["Autoclave (Steam sterilisation)", "121°C/15 psi x 15 min or 134°C x 3 min", "Metal instruments, drapes, gowns, glass, rubber", "Heat-sensitive equipment"],
            ["Dry Heat (hot air oven)", "160°C x 1hr or 180°C x 30min", "Glassware, oils, powders, sharp instruments (no steam blunting)", "Rubber, plastics, paper"],
            ["Ethylene Oxide (EO)", "50-60°C", "Endoscopes, plastics, rubber, electronics - heat sensitive", "Prolonged aeration needed (toxic residue)"],
            ["Glutaraldehyde (2%)", "Room temp", "Endoscopes (high-level disinfection)", "Not true sterilisation"],
            ["Gamma Radiation", "Room temp", "Disposables, sutures, packaged sterile items", "Industrial use; not bedside"],
            ["Plasma/Hydrogen peroxide", "50°C", "Delicate instruments, fibre optics", "Cellulose, linens"],
        ],
        col_widths=[42*mm, 36*mm, 52*mm, 38*mm]
    ))
    story.append(sp(4))
    story.append(imp_box([
        "Autoclave = moist heat = most reliable, most common method for surgical instruments",
        "Prions (CJD) are resistant to standard autoclaving - require 134°C x 18 min extended cycle or incineration",
        "Ethylene oxide: Toxic, carcinogenic, long aeration time (8-12 hrs) needed",
        "Best method for sharp instruments (to prevent blunting): Dry heat or Ethylene oxide",
    ]))
    story.append(sp(4))
    story.append(pyq_box([
            "Q: Most reliable method of sterilisation? Ans: Autoclave (moist heat under pressure)",
            "Q: Sterilisation of laparoscopes/endoscopes? Ans: Glutaraldehyde (2%) for high-level disinfection; EO for sterilisation",
            "Q: Which organisms are most resistant to sterilisation? Ans: Prions > Bacterial spores > Mycobacteria > Fungi > Viruses > Vegetative bacteria",
    ]))
    story.append(PageBreak())

    # ════════════════════════════════════════════════════════════════════════
    # QUICK REFERENCE - LAST MINUTE REVISION
    # ════════════════════════════════════════════════════════════════════════
    story.append(header_table("  QUICK REFERENCE - LAST MINUTE HIGH-YIELD FACTS", C_RED))
    story.append(sp(8))

    story.append(Paragraph("MUST-KNOW MNEMONICS", CH_SUB))
    story.append(data_table(
        ["Mnemonic", "Stands For", "Topic"],
        [
            ["MANTRELS", "Migration, Anorexia, Nausea, Tenderness RIF, Rebound, Elevated Temp, Leukocytosis, Shift left", "Alvarado Score for Appendicitis"],
            ["GET SMASHED", "Gallstones, Ethanol, Trauma, Steroids, Mumps, Autoimmune, Scorpion, Hyperlipidaemia, ERCP, Drugs", "Causes of Acute Pancreatitis"],
            ["5 F's", "Fat, Female, Fertile, Forty, Fair", "Risk factors for Cholesterol Gallstones"],
            ["AMPLE", "Allergies, Medications, Past history, Last meal, Events leading to injury", "ATLS History Taking"],
            ["Rule of 2s", "2% pop, 2 inches, 2 feet from IC valve, 2 yr age, 2:1 M:F", "Meckel's Diverticulum"],
            ["ABCDE", "Airway, Breathing, Circulation, Disability, Exposure", "Primary Survey in Trauma (ATLS)"],
            ["Virchow's Triad", "Stasis + Endothelial injury + Hypercoagulability", "DVT Formation"],
            ["Beck's Triad", "Hypotension + Muffled heart sounds + Raised JVP", "Cardiac Tamponade"],
            ["Charcot's Triad", "Fever + Jaundice + RUQ Pain", "Acute Cholangitis"],
            ["Reynolds Pentad", "Charcot's Triad + Hypotension + Confusion", "Severe/Suppurative Cholangitis"],
        ],
        col_widths=[32*mm, 90*mm, 46*mm]
    ))
    story.append(sp(6))

    story.append(Paragraph("TOP 30 MOST REPEATED SURGERY PYQs IN NEET PG", CH_SUB))
    pyq_final = [
        "1.  Most common position of appendix: RETROCAECAL (65%)",
        "2.  Most common cause of intestinal obstruction in adults: ADHESIONS (post-op) for SB; CARCINOMA for LB",
        "3.  Rule of nines: Lower limb = 18%, Upper limb = 9%, Head = 9%, Trunk (ant+post) = 36%",
        "4.  Parkland formula: 4 x kg x %TBSA in RL; half in first 8 hours",
        "5.  Most common thyroid cancer: Papillary (psammoma bodies, lymphatic spread, best prognosis)",
        "6.  Charcot's triad: Fever + Jaundice + RUQ pain = Cholangitis",
        "7.  Courvoisier's law: Palpable GB + painless jaundice = malignancy (NOT stones)",
        "8.  Beck's triad (cardiac tamponade): Hypotension + muffled sounds + raised JVP",
        "9.  Most common type of hernia (overall): INDIRECT inguinal hernia",
        "10. Richter's hernia: Strangulates WITHOUT complete obstruction (knuckle of bowel wall)",
        "11. Best prognosis thyroid cancer: Papillary; Worst: Anaplastic",
        "12. Tumour marker: Pancreatic CA = CA 19-9; Hepatoma = AFP; Medullary thyroid = Calcitonin",
        "13. Meckel's diverticulum rule of 2s - Tc-99m pertechnetate scan for diagnosis",
        "14. Hirschsprung's disease: Absent ganglion cells on rectal biopsy (gold standard)",
        "15. Intussusception: Currant jelly stools + sausage mass + USG target sign",
        "16. Most common type of wound healing: PRIMARY intention (clean surgical wound)",
        "17. Collagen type first in wound healing: Type III -> replaced by Type I",
        "18. Maximum tensile strength of healed wound: 80% (at 3 months)",
        "19. Most important cell in wound healing: MACROPHAGE",
        "20. Most common cause of SSI: Staphylococcus aureus",
        "21. TURP syndrome: Dilutional hyponatraemia from hypotonic irrigation fluid absorption",
        "22. Most common renal stone: Calcium oxalate (70-80%); Only radiolucent: Uric acid",
        "23. Struvite (staghorn) stone organism: Proteus mirabilis (urease-producing)",
        "24. Ranson score >5 = severe pancreatitis; Cullen's sign = periumbilical bruising",
        "25. Lithotripsy (ESWL) best for: Stones <2 cm in renal pelvis",
        "26. Sentinel lymph node biopsy: First line axillary staging for early breast cancer",
        "27. MEN 2A: Medullary thyroid CA + Pheochromocytoma + Hyperparathyroidism",
        "28. Best investigation for gallstones: Ultrasound (USG) - gold standard",
        "29. S1Q3T3 on ECG = Pulmonary Embolism; CTPA = gold standard investigation",
        "30. Tension pneumothorax: Immediate needle decompression at 2nd ICS midclavicular line",
    ]
    for q in pyq_final:
        story.append(Paragraph(q, BULLET))
    story.append(sp(4))

    # ── FINAL PAGE ──────────────────────────────────────────────────────────
    story.append(PageBreak())
    footer_table = Table(
        [[Paragraph("ALL THE BEST FOR NEET PG!", S("ft", fontSize=22,
           textColor=C_WHITE, fontName="Helvetica-Bold", alignment=TA_CENTER))],
         [Paragraph("You've got this! Revise smart, not hard.", S("fs", fontSize=13,
           textColor=C_YELLOW, alignment=TA_CENTER))],
         [sp(10)],
         [Paragraph("Sources: Bailey & Love 28e | Schwartz's Surgery 11e | Current Surgical Therapy 14e | Sabiston Surgery | Tintinalli Emergency Medicine | Maingot's Abdominal Operations", S("fsrc", fontSize=8, textColor=C_WHITE, alignment=TA_CENTER))],
        ],
        colWidths=[190*mm]
    )
    footer_table.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), C_NAVY),
        ("TOPPADDING",    (0,0), (-1,-1), 14),
        ("BOTTOMPADDING", (0,0), (-1,-1), 14),
        ("LEFTPADDING",   (0,0), (-1,-1), 20),
    ]))
    story.append(footer_table)

    return story


# ── Page Template (header + footer) ─────────────────────────────────────────
from reportlab.platypus import Frame, PageTemplate
from reportlab.platypus.doctemplate import BaseDocTemplate

class SurgeryDoc(BaseDocTemplate):
    def __init__(self, filename, **kwargs):
        super().__init__(filename, **kwargs)
        frame = Frame(self.leftMargin, self.bottomMargin,
                      self.width, self.height, id='main')
        template = PageTemplate(id='main', frames=[frame],
                                onPage=self._add_page_decor)
        self.addPageTemplates([template])

    def _add_page_decor(self, canvas, doc):
        canvas.saveState()
        # Top thin stripe
        canvas.setFillColor(C_TEAL)
        canvas.rect(0, A4[1]-8, A4[0], 8, fill=1, stroke=0)
        # Bottom thin stripe
        canvas.setFillColor(C_NAVY)
        canvas.rect(0, 0, A4[0], 20, fill=1, stroke=0)
        # Footer text
        canvas.setFillColor(C_WHITE)
        canvas.setFont("Helvetica", 7)
        canvas.drawString(15*mm, 7, "NEET PG Surgery Rapid Revision Notes  |  2-Day Complete Revision")
        canvas.drawRightString(A4[0]-15*mm, 7, f"Page {doc.page}")
        canvas.restoreState()


def main():
    doc = SurgeryDoc(
        OUTPUT,
        pagesize=A4,
        leftMargin=18*mm, rightMargin=18*mm,
        topMargin=16*mm, bottomMargin=22*mm,
        title="NEET PG Surgery Rapid Revision Notes",
        author="Orris AI",
    )
    story = build_story()
    doc.build(story)
    print(f"PDF generated: {OUTPUT}")

if __name__ == "__main__":
    main()

cd /home/daytona/workspace/surgery-neet-pg && python3 generate_surgery_pdf.py 2>…

ls -lh /home/daytona/workspace/surgery-neet-pg/NEET_PG_Surgery_Revision.pdf