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

OUTPUT = "/home/daytona/workspace/resp-pharm/Resp_Pharmacology_HKMLE.pdf"

# ── Colour palette (matches Cardio style) ──────────────────────────────────────
C_NAVY      = colors.HexColor("#1B3A5C")   # header / title background
C_ACCENT    = colors.HexColor("#2E86AB")   # section title bar
C_LIGHT     = colors.HexColor("#D6EAF8")   # alt-row / light header
C_MUTED     = colors.HexColor("#F0F4F8")   # pearl box background
C_WARN      = colors.HexColor("#FFF3CD")   # trap/warning boxes
C_GREEN     = colors.HexColor("#D5F5E3")   # green header rows
C_GREEN_D   = colors.HexColor("#1E8449")   # dark green text
C_RED       = colors.HexColor("#FADBD8")   # danger highlight
C_WHITE     = colors.white
C_BLACK     = colors.HexColor("#1A1A1A")
C_GREY_LINE = colors.HexColor("#BDC3C7")

W = A4[0] - 28*mm   # usable width

# ── Styles ─────────────────────────────────────────────────────────────────────
styles = getSampleStyleSheet()

def S(name, **kw):
    return ParagraphStyle(name, **kw)

TITLE   = S("T",  fontName="Helvetica-Bold",   fontSize=18, textColor=C_WHITE,   alignment=TA_CENTER, spaceAfter=2)
SUBTITLE= S("ST", fontName="Helvetica",         fontSize=10, textColor=C_LIGHT,   alignment=TA_CENTER, spaceAfter=6)
SEC     = S("SE", fontName="Helvetica-Bold",    fontSize=12, textColor=C_WHITE,   alignment=TA_LEFT,   spaceAfter=2, spaceBefore=4)
BODY    = S("B",  fontName="Helvetica",         fontSize=9,  textColor=C_BLACK,   leading=13, spaceAfter=2)
BOLD    = S("BD", fontName="Helvetica-Bold",    fontSize=9,  textColor=C_BLACK,   leading=13, spaceAfter=2)
SMALL   = S("SM", fontName="Helvetica",         fontSize=8,  textColor=C_BLACK,   leading=11)
SMALL_B = S("SB", fontName="Helvetica-Bold",    fontSize=8,  textColor=C_BLACK,   leading=11)
MNE     = S("MN", fontName="Helvetica-BoldOblique", fontSize=9, textColor=C_NAVY, leading=13, spaceAfter=2)
PEARL   = S("PL", fontName="Helvetica",         fontSize=8.5,textColor=C_BLACK,   leading=12, spaceAfter=1)
TRAP_S  = S("TR", fontName="Helvetica-BoldOblique", fontSize=8.5, textColor=colors.HexColor("#7D3C00"), leading=12)
TH      = S("TH", fontName="Helvetica-Bold",    fontSize=8.5,textColor=C_WHITE,   alignment=TA_CENTER, leading=11)
TC      = S("TC", fontName="Helvetica",         fontSize=8.5,textColor=C_BLACK,   leading=11)
TC_B    = S("TCB",fontName="Helvetica-Bold",    fontSize=8.5,textColor=C_BLACK,   leading=11)
TC_I    = S("TCI",fontName="Helvetica-Oblique", fontSize=8.5,textColor=C_BLACK,   leading=11)

def ph(text, style=BODY): return Paragraph(text, style)
def sp(h=4):              return Spacer(1, h*mm)
def hr():                 return HRFlowable(width="100%", thickness=0.5, color=C_GREY_LINE, spaceAfter=3, spaceBefore=3)

# ── Section header bar ─────────────────────────────────────────────────────────
def sec_header(text, color=C_ACCENT):
    t = Table([[ph(text, SEC)]], colWidths=[W])
    t.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), 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),
    ]))
    return t

# ── Coloured box (mnemonic / pearl / trap) ─────────────────────────────────────
def box(text, bg=C_MUTED, style=PEARL, label=None):
    content = (f"<b>{label}</b>  " if label else "") + text
    t = Table([[ph(content, style)]], colWidths=[W])
    t.setStyle(TableStyle([
        ("BACKGROUND",(0,0),(-1,-1), bg),
        ("TOPPADDING",(0,0),(-1,-1), 5),
        ("BOTTOMPADDING",(0,0),(-1,-1), 5),
        ("LEFTPADDING",(0,0),(-1,-1), 8),
        ("RIGHTPADDING",(0,0),(-1,-1), 8),
        ("BOX",(0,0),(-1,-1),0.5,C_GREY_LINE),
    ]))
    return t

def mne_box(text):  return box(text, bg=C_LIGHT,  style=MNE,  label="Mnemonic:")
def pearl_box(text):return box(text, bg=C_MUTED,  style=PEARL,label="HKMLE Pearl:")
def trap_box(text): return box(text, bg=C_WARN,   style=TRAP_S,label="Exam Trap:")
def paper_box(text):return box(f"<b>Paper:</b> {text}", bg=C_GREEN, style=PEARL)

# ── Generic table builder ──────────────────────────────────────────────────────
def build_table(headers, rows, col_widths, zebra=True, header_color=C_NAVY):
    header_row = [ph(h, TH) for h in headers]
    data = [header_row]
    for i, row in enumerate(rows):
        bg = C_LIGHT if (zebra and i % 2 == 0) else C_WHITE
        data.append([ph(str(c), TC) for c in row])

    style = [
        ("BACKGROUND",   (0,0), (-1,0),  header_color),
        ("ROWBACKGROUNDS",(0,1),(-1,-1), [C_LIGHT, C_WHITE] if zebra else [C_WHITE]),
        ("GRID",         (0,0), (-1,-1), 0.4, C_GREY_LINE),
        ("TOPPADDING",   (0,0), (-1,-1), 4),
        ("BOTTOMPADDING",(0,0), (-1,-1), 4),
        ("LEFTPADDING",  (0,0), (-1,-1), 5),
        ("RIGHTPADDING", (0,0), (-1,-1), 5),
        ("VALIGN",       (0,0), (-1,-1), "TOP"),
    ]
    t = Table(data, colWidths=col_widths)
    t.setStyle(TableStyle(style))
    return t

# ══════════════════════════════════════════════════════════════════════════════
# DOCUMENT CONTENT
# ══════════════════════════════════════════════════════════════════════════════
story = []

# ── TITLE BLOCK ────────────────────────────────────────────────────────────────
title_data = [[
    ph("HKMLE HIGH-YIELD", TITLE),
    ph("RESPIRATORY PHARMACOLOGY", TITLE),
]]
# Single-cell banner
banner = Table([[ph("HKMLE HIGH-YIELD: RESPIRATORY PHARMACOLOGY", TITLE)]], colWidths=[W])
banner.setStyle(TableStyle([
    ("BACKGROUND",(0,0),(-1,-1), C_NAVY),
    ("TOPPADDING",(0,0),(-1,-1), 10),
    ("BOTTOMPADDING",(0,0),(-1,-1), 6),
    ("LEFTPADDING",(0,0),(-1,-1), 10),
]))
story.append(banner)

sub = Table([[ph("Compiled from Katzung · Lippincott · Goodman & Gilman · Murray & Nadel", SUBTITLE)]], colWidths=[W])
sub.setStyle(TableStyle([
    ("BACKGROUND",(0,0),(-1,-1), C_ACCENT),
    ("TOPPADDING",(0,0),(-1,-1), 4),
    ("BOTTOMPADDING",(0,0),(-1,-1), 4),
]))
story.append(sub)
story.append(sp(3))

story.append(mne_box('"BALTICS" — Beta-2 agonists | Anticholinergics | Leukotriene modifiers | Theophylline | ICS | Chromones | Steroids (systemic) + biologics'))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# 1. BETA-2 AGONISTS
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("1. BETA-2 AGONISTS"))
story.append(sp(2))
story.append(ph("<b>SABA:</b> Salbutamol (albuterol), Terbutaline     <b>LABA:</b> Salmeterol, Formoterol", BODY))
story.append(sp(2))

b2_headers = ["", "SABA", "LABA"]
b2_rows = [
    ["Mechanism", "Beta-2 agonist → cAMP ↑ → airway smooth muscle relaxation", "Same, longer duration"],
    ["Indication", "Acute asthma rescue; acute COPD exacerbation", "Step 3+ asthma (with ICS); COPD maintenance"],
    ["SE", "Tremor, tachycardia, hypokalaemia, hyperglycaemia", "Same + asthma death risk if used without ICS"],
    ["CI", "None absolute", "Monotherapy in asthma (black box)"],
]
story.append(build_table(b2_headers, b2_rows, [25*mm, 75*mm, 75*mm]))
story.append(sp(2))
story.append(paper_box("I (mechanism, SE)  |  III (step therapy)"))
story.append(sp(1))
story.append(trap_box(
    "Trap 1: Salbutamol → hypokalaemia (beta-2 drives K+ into cells). Tested in overdose/ICU scenarios.  "
    "Trap 2: LABA alone in asthma = contraindicated — must always combine with ICS.  "
    "Formoterol has fast onset (can double as rescue); salmeterol does not."
))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# 2. ANTICHOLINERGICS
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("2. ANTICHOLINERGICS (SAMA / LAMA)"))
story.append(sp(2))
story.append(mne_box('"I\'m SAMA, Tio\'s LAMA" — Ipratropium = SAMA;  Tiotropium = LAMA'))
story.append(sp(2))

ac_headers = ["", "Ipratropium (SAMA)", "Tiotropium (LAMA)"]
ac_rows = [
    ["Mechanism", "M3 antagonist → blocks bronchoconstriction", "Same, higher affinity, once-daily"],
    ["Indication", "Acute severe asthma (ER add-on to SABA); COPD exacerbation", "COPD maintenance (1st line); add-on in severe asthma"],
    ["SE", "Dry mouth, urinary retention, blurred vision, constipation", "Same (minimal systemic — quaternary compound, poor absorption)"],
    ["CI", "Narrow-angle glaucoma, BPH (relative)", "Same"],
]
story.append(build_table(ac_headers, ac_rows, [25*mm, 82*mm, 68*mm]))
story.append(sp(2))
story.append(paper_box("I (mechanism)  |  III (COPD management)"))
story.append(sp(1))
story.append(trap_box(
    "Quaternary ammonium structure = does NOT cross BBB = no CNS effects. Inhaled only.  "
    "Tiotropium in COPD reduces exacerbations and improves exercise tolerance."
))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# 3. ICS
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("3. INHALED CORTICOSTEROIDS (ICS)"))
story.append(sp(2))
story.append(ph("<b>Drugs:</b> Beclomethasone, Budesonide, Fluticasone, Mometasone", BODY))
story.append(mne_box('"Rinse or you\'ll get Thrush" — rinse mouth after every dose'))
story.append(sp(2))

ics_headers = ["Feature", "Details"]
ics_rows = [
    ["Mechanism",    "Glucocorticoid receptor activation → suppress eosinophilic airway inflammation"],
    ["Indication",   "Persistent asthma (step 2 onward); COPD with recurrent exacerbations (combined with LABA)"],
    ["Local SE",     "Oral candidiasis, dysphonia (hoarseness)"],
    ["Systemic SE",  "Rare at low dose; high dose → adrenal suppression, growth retardation (children), osteoporosis, cataracts"],
    ["Prevention",   "Rinse mouth after use; use spacer"],
    ["CI",           "No absolute CI; caution in active TB"],
]
story.append(build_table(ics_headers, ics_rows, [35*mm, 140*mm]))
story.append(sp(2))
story.append(paper_box("I (SE, mechanism)  |  III (step-up therapy, paediatric asthma)"))
story.append(sp(1))
story.append(trap_box("ICS do NOT cause systemic Cushing's at standard doses. Growth suppression is the paediatric exam question."))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# 4. THEOPHYLLINE
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("4. THEOPHYLLINE"))
story.append(sp(2))
story.append(mne_box('"TANS" — Theophylline toxicity: Tachycardia | Arrhythmia | Nausea | Seizures'))
story.append(sp(2))

theo_headers = ["Feature", "Details"]
theo_rows = [
    ["Mechanism",         "PDE inhibitor → cAMP ↑ → bronchodilation; also adenosine receptor antagonist"],
    ["Indication",        "Chronic asthma/COPD (3rd line); IV aminophylline for acute severe asthma"],
    ["Therapeutic range", "10–20 mg/L (narrow therapeutic index)"],
    ["Toxic SE (>20 mg/L)","Seizures, ventricular arrhythmias, N&V, tachycardia"],
    ["CI",                "Epilepsy, cardiac arrhythmias"],
]
story.append(build_table(theo_headers, theo_rows, [40*mm, 135*mm]))
story.append(sp(2))

# Drug interactions sub-table
story.append(ph("<b>Drug Interactions (heavily tested):</b>", BOLD))
story.append(sp(1))
di_headers = ["Increases Theophylline Levels (toxicity risk)", "Decreases Theophylline Levels"]
di_rows = [["Ciprofloxacin, Erythromycin, Cimetidine (CYP1A2 inhibitors)", "Rifampicin, Phenytoin, Smoking (CYP1A2 inducers)"]]
story.append(build_table(di_headers, di_rows, [87.5*mm, 87.5*mm]))
story.append(sp(2))
story.append(paper_box("I (interactions, toxicity — high yield)  |  II (toxicology/prescribing)"))
story.append(sp(1))
story.append(trap_box("Patient on theophylline starts ciprofloxacin for chest infection → theophylline toxicity. Classic HKMLE scenario."))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# 5. LEUKOTRIENE MODIFIERS
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("5. LEUKOTRIENE MODIFIERS"))
story.append(sp(2))
story.append(ph("<b>Drugs:</b> Montelukast (LTRA), Zafirlukast (LTRA), Zileuton (5-LOX inhibitor)", BODY))
story.append(mne_box('"Montelukast for Aspirin Asthma & Allergic Athletes"'))
story.append(sp(2))

lt_headers = ["Feature", "Details"]
lt_rows = [
    ["Mechanism",    "Block CysLT1 receptors → reduce bronchoconstriction + eosinophil recruitment"],
    ["Indication",   "Mild persistent asthma (add-on or ICS alternative); aspirin/NSAID-exacerbated asthma; allergic rhinitis; exercise-induced bronchospasm"],
    ["SE",           "Neuropsychiatric effects (depression, suicidality — FDA black box); Churg-Strauss vasculitis (rare, on steroid taper)"],
    ["Advantage",    "Oral; useful in aspirin-sensitive asthma"],
    ["CI",           "Caution with psychiatric history"],
]
story.append(build_table(lt_headers, lt_rows, [35*mm, 140*mm]))
story.append(sp(2))
story.append(paper_box("I  |  III"))
story.append(sp(1))
story.append(trap_box(
    "Trap 1: Drug of choice for aspirin-sensitive (AERD) asthma = LTRA. Very high-yield.  "
    "Trap 2: Churg-Strauss — eosinophilic vasculitis appearing when oral steroids are tapered."
))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# 6. MAST CELL STABILISERS
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("6. MAST CELL STABILISERS"))
story.append(sp(2))
story.append(ph("<b>Drugs:</b> Sodium cromoglicate (cromolyn), Nedocromil", BODY))
story.append(sp(2))

mc_headers = ["Feature", "Details"]
mc_rows = [
    ["Mechanism",  "Inhibit mast cell degranulation → block histamine + leukotriene release"],
    ["Indication", "Prophylaxis: mild asthma, exercise-induced bronchospasm, allergic rhinitis"],
    ["SE",         "Minimal; cough/throat irritation"],
    ["CI",         "NOT for acute attacks — prophylaxis only"],
]
story.append(build_table(mc_headers, mc_rows, [35*mm, 140*mm]))
story.append(sp(2))
story.append(paper_box("I"))
story.append(sp(1))
story.append(pearl_box("Rarely used in practice but appear in mechanism-type Paper I MCQs."))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# 7. BIOLOGICS
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("7. BIOLOGICS"))
story.append(sp(2))
story.append(mne_box('"O-M-D targets IgE, IL-5, IL-4" — Omalizumab | Mepolizumab | Dupilumab'))
story.append(sp(2))

bio_headers = ["Drug", "Target", "Indication", "Key SE"]
bio_rows = [
    ["Omalizumab",                   "Anti-IgE",             "Severe allergic asthma (elevated IgE, allergen sensitised)",         "Anaphylaxis (30-min observation required), injection site reactions"],
    ["Mepolizumab /\nBenralizumab",  "Anti-IL-5 (↓ eosinophils)", "Severe eosinophilic asthma",                                   "Injection site reactions"],
    ["Dupilumab",                    "Anti-IL-4/IL-13",      "Severe type-2 asthma; also atopic dermatitis + nasal polyps",       "Injection site; transient eosinophilia"],
]
story.append(build_table(bio_headers, bio_rows, [35*mm, 32*mm, 65*mm, 43*mm]))
story.append(sp(2))
story.append(paper_box("I (mechanism)  |  III (patient selection)"))
story.append(sp(1))
story.append(pearl_box("Omalizumab prerequisite: elevated serum IgE AND documented allergen sensitisation."))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# COMPARISON TABLE
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("ASTHMA vs COPD: DRUG OF CHOICE SUMMARY", color=C_NAVY))
story.append(sp(2))

cmp_headers = ["Drug Class", "Asthma", "COPD"]
cmp_rows = [
    ["SABA",                    "1st-line rescue",                          "Rescue (as needed)"],
    ["LABA",                    "Add-on to ICS only",                       "1st-line maintenance (can use alone)"],
    ["LAMA (Tiotropium)",       "Add-on in severe/uncontrolled",            "1st-line maintenance (preferred)"],
    ["ICS",                     "Cornerstone (step 2+)",                    "Only if frequent exacerbations"],
    ["Theophylline",            "3rd line",                                  "3rd line"],
    ["LTRA",                    "Add-on / aspirin asthma",                  "Not indicated"],
    ["Biologics",               "Severe uncontrolled",                      "Not indicated"],
]
story.append(build_table(cmp_headers, cmp_rows, [45*mm, 72.5*mm, 57.5*mm]))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# TOP EXAM TRAPS
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("TOP EXAM TRAPS AT A GLANCE", color=colors.HexColor("#7D3C00")))
story.append(sp(2))

trap_headers = ["Scenario", "Answer"]
trap_rows = [
    ["Salbutamol overdose → low K+",             "Beta-2 agonist shifts K+ intracellularly"],
    ["LABA without ICS in asthma",               "Contraindicated — increases asthma mortality"],
    ["Aspirin-sensitive asthma drug",             "Montelukast (LTRA)"],
    ["Theophylline + ciprofloxacin",              "Toxicity (CYP1A2 inhibition ↑ theophylline levels)"],
    ["Theophylline + rifampicin/smoking",         "Sub-therapeutic levels (CYP1A2 induction)"],
    ["ICS side effect prevented by rinsing mouth","Oral candidiasis"],
    ["Tiotropium vs Ipratropium",                 "Tiotropium = LAMA, once daily, COPD maintenance"],
    ["Omalizumab requirement",                    "High IgE + allergen sensitisation"],
    ["Montelukast CNS warning",                   "Depression / suicidal ideation"],
    ["LABA monotherapy: OK in COPD?",             "Yes. OK in COPD, NOT in asthma"],
]
t = Table(
    [[ph(r[0], TC_B), ph(r[1], TC)] for r in [["Scenario","Answer"]] + trap_rows],
    colWidths=[87.5*mm, 87.5*mm]
)
t.setStyle(TableStyle([
    ("BACKGROUND",   (0,0), (-1,0),  colors.HexColor("#7D3C00")),
    ("ROWBACKGROUNDS",(0,1),(-1,-1), [C_WARN, C_WHITE]),
    ("GRID",         (0,0), (-1,-1), 0.4, C_GREY_LINE),
    ("TOPPADDING",   (0,0), (-1,-1), 4),
    ("BOTTOMPADDING",(0,0), (-1,-1), 4),
    ("LEFTPADDING",  (0,0), (-1,-1), 5),
    ("VALIGN",       (0,0), (-1,-1), "TOP"),
    ("FONTNAME",     (0,0), (-1,0),  "Helvetica-Bold"),
    ("FONTCOLOR",    (0,0), (-1,0),  C_WHITE),
    ("FONTSIZE",     (0,0), (-1,-1), 8.5),
]))
story.append(t)
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# PAGE BREAK → NEW SECTIONS
# ══════════════════════════════════════════════════════════════════════════════
story.append(PageBreak())

# ══════════════════════════════════════════════════════════════════════════════
# SECTION A: TB DRUGS
# ══════════════════════════════════════════════════════════════════════════════
tb_banner = Table([[ph("SECTION A: TB DRUGS (RIPE)", TITLE)]], colWidths=[W])
tb_banner.setStyle(TableStyle([
    ("BACKGROUND",(0,0),(-1,-1), C_NAVY),
    ("TOPPADDING",(0,0),(-1,-1), 8),
    ("BOTTOMPADDING",(0,0),(-1,-1), 6),
    ("LEFTPADDING",(0,0),(-1,-1), 10),
]))
story.append(tb_banner)
story.append(sp(3))

story.append(mne_box(
    '"RIP PE" — Rifampicin (orange urine/secretions) | INH (neuropathy/hepatitis) | '
    'Pyrazinamide (urate/gout) | Pyridoxine needed for INH | Ethambutol (Eyes — optic neuritis)'
))
story.append(sp(3))

tb_headers = ["Drug", "Mechanism (1 line)", "Unique Toxicity", "HKMLE Pearl"]
tb_rows = [
    [
        "Rifampicin",
        "Inhibits bacterial DNA-dependent RNA polymerase",
        "Orange/red discolouration of urine, tears, sweat; hepatotoxicity; potent CYP450 inducer (↓ OCP, warfarin, many drugs)",
        "Classic exam question: patient on OCP + rifampicin → unintended pregnancy. Always warn about drug interactions.",
    ],
    [
        "Isoniazid (INH)",
        "Inhibits mycolic acid synthesis (InhA)",
        "Peripheral neuropathy (B6 deficiency → give pyridoxine prophylactically); hepatotoxicity; SLE-like syndrome (slow acetylators)",
        "Give pyridoxine (Vit B6) with INH to prevent neuropathy. Slow acetylators at higher toxicity risk.",
    ],
    [
        "Pyrazinamide",
        "Disrupts mycobacterial cell membrane pH",
        "Hyperuricaemia/gout (most common); hepatotoxicity; arthralgia",
        "PZA causes gout — check uric acid. Causes most hepatotoxicity in RIPE regimen.",
    ],
    [
        "Ethambutol",
        "Inhibits arabinosyl transferase (cell wall)",
        "Optic neuritis: reduced visual acuity, red-green colour blindness (dose-dependent, usually reversible)",
        "Always check baseline and monitor visual acuity. Stop immediately if visual changes occur.",
    ],
]
story.append(build_table(tb_headers, tb_rows, [25*mm, 42*mm, 58*mm, 50*mm]))
story.append(sp(2))
story.append(paper_box("I (mechanism, drug interactions)  |  II (TB drug emergency — hepatotoxicity, optic neuritis)"))
story.append(sp(2))
story.append(trap_box(
    "Trap 1: Rifampicin is a potent CYP450 inducer — reduces efficacy of OCP, warfarin, antiretrovirals, methadone.  "
    "Trap 2: INH neuropathy prevented by pyridoxine (B6).  "
    "Trap 3: Ethambutol — stop the drug if ANY visual change reported.  "
    "Trap 4: All four drugs cause hepatotoxicity — check LFTs at baseline and during treatment."
))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# SECTION B: PNEUMONIA ANTIBIOTICS
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("SECTION B: PNEUMONIA ANTIBIOTICS (CAP vs HAP)"))
story.append(sp(2))

pna_headers = ["Setting", "First-Line", "Alternative"]
pna_rows = [
    [
        "CAP — Outpatient\n(no comorbidities)",
        "Amoxicillin PO\nor\nDoxycycline PO",
        "Azithromycin PO (if low resistance)\nLevofloxacin PO (respiratory quinolone)",
    ],
    [
        "CAP — Outpatient\n(with comorbidities: DM, CKD, heart/lung disease)",
        "Amoxicillin-clavulanate PO\n+ Azithromycin PO\nor Respiratory quinolone (levofloxacin) PO",
        "Moxifloxacin PO",
    ],
    [
        "CAP — Inpatient\n(non-ICU)",
        "Beta-lactam IV (ampicillin-sulbactam or ceftriaxone)\n+ Azithromycin IV/PO\nor\nRespiratory quinolone alone",
        "Ceftriaxone + Doxycycline",
    ],
    [
        "CAP — Inpatient\n(ICU / severe)",
        "Beta-lactam IV + Azithromycin IV\nor\nBeta-lactam IV + Respiratory quinolone IV",
        "If Pseudomonas risk: pip-tazo or cefepime + ciprofloxacin",
    ],
    [
        "HAP — Non-severe\n(no MRSA risk, no Pseudomonas risk)",
        "Piperacillin-tazobactam IV\nor\nCeftriaxone IV",
        "Levofloxacin IV",
    ],
    [
        "HAP — Severe\n(MRSA risk, late-onset, prior antibiotics)",
        "Vancomycin IV or Linezolid IV\n+ Anti-pseudomonal beta-lactam\n(pip-tazo or meropenem)",
        "Ceftazidime or cefepime + vancomycin",
    ],
]
story.append(build_table(pna_headers, pna_rows, [42*mm, 77*mm, 56*mm]))
story.append(sp(2))
story.append(paper_box("I (antibiotic mechanism/spectrum)  |  III (clinical prescribing scenarios)"))
story.append(sp(1))
story.append(pearl_box(
    "Atypical cover (Legionella, Mycoplasma, Chlamydophila) requires azithromycin or a quinolone — beta-lactam alone is insufficient. "
    "In HK, always consider TB before starting empirical antibiotics for unresolved pneumonia."
))
story.append(sp(1))
story.append(trap_box(
    "Trap 1: Macrolide (azithromycin) or doxycycline for atypical CAP — these cover Mycoplasma, Legionella, Chlamydophila.  "
    "Trap 2: HAP = pneumonia developing ≥48 h after hospital admission. Broader cover needed.  "
    "Trap 3: MRSA-risk patients (prior MRSA, penetrating chest wound) require vancomycin or linezolid."
))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# SECTION C: INHALER DEVICES
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("SECTION C: INHALER DEVICES"))
story.append(sp(2))

dev_headers = ["Device", "When to Use", "Key Point"]
dev_rows = [
    [
        "MDI\n(Metered Dose Inhaler)",
        "Standard first-line delivery device for all ages (with spacer in children/elderly)",
        "Requires good coordination between actuation and inhalation. CFC-free now standard. Requires slow, deep inhalation.",
    ],
    [
        "DPI\n(Dry Powder Inhaler)\ne.g. Turbuhaler, Accuhaler",
        "Patients who cannot coordinate MDI (no need to press + breathe simultaneously)",
        "Requires fast, deep inspiratory effort to aerosolise powder — NOT suitable during acute severe asthma (weak inspiratory flow).",
    ],
    [
        "Spacer\n(Valved Holding Chamber)",
        "Used with MDI — children, elderly, acute exacerbations, poor technique",
        "Reduces oropharyngeal deposition → less oral candidiasis. Equivalent to nebuliser in acute mild-moderate asthma.",
    ],
    [
        "Nebuliser",
        "Acute severe asthma/COPD exacerbation; patients unable to use any handheld device",
        "Driven by O2 (asthma) or air (COPD — avoid high FiO2). Slower to set up than MDI + spacer.",
    ],
    [
        "Soft Mist Inhaler\n(e.g. Respimat — tiotropium)",
        "COPD maintenance; elderly with low inspiratory flow",
        "Produces slow aerosol cloud — less effort needed than DPI. Better lung deposition than standard MDI.",
    ],
]
story.append(build_table(dev_headers, dev_rows, [32*mm, 55*mm, 88*mm]))
story.append(sp(2))
story.append(paper_box("I (device selection MCQs)  |  III (prescribing appropriate device for patient scenario)"))
story.append(sp(1))
story.append(trap_box(
    "Trap 1: DPI cannot be used during acute severe asthma — insufficient inspiratory flow.  "
    "Trap 2: Spacer with MDI is equivalent to nebuliser for mild-moderate exacerbations — no need to wait for nebuliser.  "
    "Trap 3: COPD + nebuliser → use air-driven, NOT oxygen-driven, to avoid hypercapnic drive suppression."
))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# PAGE BREAK → CHEAT SHEETS
# ══════════════════════════════════════════════════════════════════════════════
story.append(PageBreak())

# ══════════════════════════════════════════════════════════════════════════════
# QUICK MNEMONICS CHEAT SHEET
# ══════════════════════════════════════════════════════════════════════════════
mne_banner = Table([[ph("QUICK MNEMONICS CHEAT SHEET", TITLE)]], colWidths=[W])
mne_banner.setStyle(TableStyle([
    ("BACKGROUND",(0,0),(-1,-1), C_NAVY),
    ("TOPPADDING",(0,0),(-1,-1), 8),
    ("BOTTOMPADDING",(0,0),(-1,-1), 6),
    ("LEFTPADDING",(0,0),(-1,-1), 10),
]))
story.append(mne_banner)
story.append(sp(3))

mne_headers = ["Mnemonic", "Stands For", "What it Helps You Remember"]
mne_rows = [
    ["BALTICS",   "Beta-2 | Anticholinergics | Leukotriene | Theophylline | ICS | Chromones | Steroids+biologics", "Complete drug class list for respiratory pharmacology"],
    ["I'm SAMA, Tio's LAMA", "Ipratropium = SAMA; Tiotropium = LAMA", "Duration classification of anticholinergics"],
    ["Rinse or you'll get Thrush", "Rinse mouth after ICS", "Prevents oral candidiasis from ICS"],
    ["TANS",      "Tachycardia | Arrhythmia | Nausea | Seizures", "Theophylline toxicity features (>20 mg/L)"],
    ["Montelukast for Aspirin Asthma & Allergic Athletes", "LTRA = first choice for AERD + exercise-induced", "Key indications of leukotriene modifiers"],
    ["O-M-D targets IgE, IL-5, IL-4", "Omalizumab | Mepolizumab | Dupilumab", "Biologic targets — matched to drug names"],
    ["RIP PE",    "Rifampicin (orange) | INH (neuropathy) | Pyrazinamide (urate) | Pyridoxine for INH | Ethambutol (Eyes)", "TB drug unique toxicities"],
]
story.append(build_table(mne_headers, mne_rows, [38*mm, 72*mm, 65*mm]))
story.append(sp(4))

# ══════════════════════════════════════════════════════════════════════════════
# HKMLE PAPER DISTRIBUTION SUMMARY
# ══════════════════════════════════════════════════════════════════════════════
dist_banner = Table([[ph("HKMLE PAPER DISTRIBUTION SUMMARY", TITLE)]], colWidths=[W])
dist_banner.setStyle(TableStyle([
    ("BACKGROUND",(0,0),(-1,-1), C_NAVY),
    ("TOPPADDING",(0,0),(-1,-1), 8),
    ("BOTTOMPADDING",(0,0),(-1,-1), 6),
    ("LEFTPADDING",(0,0),(-1,-1), 10),
]))
story.append(dist_banner)
story.append(sp(3))

dist_headers = ["Topic", "Paper I\n(Basic Sciences / Pharmacology MCQ)", "Paper II\n(Clinical Sciences / Prescribing)", "Paper III\n(Clinical Management / SAQ)"]
dist_rows = [
    ["Beta-2 Agonists (SABA/LABA)",    "Mechanism, SE, hypokalaemia",          "Overdose, pregnancy use",                    "Asthma step therapy, acute management"],
    ["Anticholinergics (SAMA/LAMA)",   "Mechanism, receptor subtypes",         "—",                                          "COPD maintenance, acute severe asthma ER"],
    ["Inhaled Corticosteroids",        "Mechanism, local/systemic SE",         "Paediatric growth, pregnancy",               "Step-up therapy, paediatric asthma"],
    ["Theophylline",                   "Mechanism, drug interactions (HIGH YIELD)", "Toxicity management, drug interactions", "3rd-line role, monitoring"],
    ["Leukotriene Modifiers",          "Mechanism, receptor type",             "Psychiatric SE (black box)",                 "Aspirin asthma, add-on therapy"],
    ["Mast Cell Stabilisers",          "Mechanism type MCQ",                   "—",                                          "Exercise-induced prophylaxis"],
    ["Biologics",                      "Target (IgE, IL-5, IL-4/13)",          "Anaphylaxis risk (omalizumab)",              "Severe asthma patient selection"],
    ["TB Drugs (RIPE)",                "Mechanism, interactions (rifampicin)", "Hepatotoxicity, optic neuritis emergencies", "TB treatment initiation, monitoring"],
    ["Pneumonia Antibiotics",          "Antibiotic spectrum/mechanism",        "CAP prescribing, atypical cover",            "CAP/HAP management, MRSA scenarios"],
    ["Inhaler Devices",                "Device selection MCQs",                "Prescribing appropriate device",             "Acute asthma — spacer vs nebuliser"],
]
story.append(build_table(dist_headers, dist_rows, [38*mm, 48*mm, 45*mm, 44*mm]))
story.append(sp(3))

# ── final note ─────────────────────────────────────────────────────────────────
story.append(box(
    "These notes are compiled from Katzung's Basic & Clinical Pharmacology (16e), Lippincott Illustrated Reviews Pharmacology, "
    "Goodman & Gilman's Pharmacological Basis of Therapeutics, and Murray & Nadel's Textbook of Respiratory Medicine. "
    "Content is curated for HKMLE relevance. Always cross-reference with current HKMLE guidelines.",
    bg=C_MUTED, style=SMALL
))

# ── BUILD ──────────────────────────────────────────────────────────────────────
doc = SimpleDocTemplate(
    OUTPUT,
    pagesize=A4,
    topMargin=14*mm,
    bottomMargin=14*mm,
    leftMargin=14*mm,
    rightMargin=14*mm,
)
doc.build(story)
print(f"PDF written: {OUTPUT}")