#!/usr/bin/env python3
"""
Premium Atypical Cardiomyopathy Pediatrics PDF
Author: Raghul Balaji | 4th Year MBBS | Group 8 | Jalalabad State University
"""

from reportlab.lib.pagesizes import A4
from reportlab.lib import colors
from reportlab.lib.units import mm, cm
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.enums import TA_LEFT, TA_CENTER, TA_RIGHT, TA_JUSTIFY
from reportlab.platypus import (
    SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle,
    HRFlowable, Image, KeepTogether, PageBreak
)
from reportlab.platypus.flowables import Flowable
from reportlab.lib.colors import HexColor, white, black
import os

# ─── Colour palette ──────────────────────────────────────────────────────────
NAVY       = HexColor('#0D2B55')   # deep navy – headers / rule lines
TEAL       = HexColor('#1A7A8A')   # teal – section titles
ACCENT     = HexColor('#E8F4F8')   # very light blue – shaded rows / callout bg
GOLD       = HexColor('#C8860A')   # gold – bullet icon colour
LIGHT_GREY = HexColor('#F5F5F5')   # table alt row
MID_GREY   = HexColor('#CCCCCC')   # dividers
DARK_GREY  = HexColor('#333333')   # body text
RED_LIGHT  = HexColor('#FFF0F0')   # key-points box bg
RED_BORDER = HexColor('#CC2222')   # key-points box border

W, H = A4
MARGIN = 18 * mm

# ─── Custom flowables ─────────────────────────────────────────────────────────

class ColorBar(Flowable):
    """Full-width colour bar used as section dividers."""
    def __init__(self, w, h, color):
        super().__init__()
        self.bar_w = w
        self.bar_h = h
        self.color = color

    def draw(self):
        self.canv.setFillColor(self.color)
        self.canv.rect(0, 0, self.bar_w, self.bar_h, fill=1, stroke=0)

    def wrap(self, aW, aH):
        return self.bar_w, self.bar_h


class RoundedBox(Flowable):
    """Rounded-corner coloured box wrapping a list of text lines."""
    def __init__(self, lines, bg, border, width, font='Helvetica', size=8.5):
        super().__init__()
        self.lines   = lines
        self.bg      = bg
        self.border  = border
        self.bw      = width
        self.font    = font
        self.size    = size
        self.padding = 8

    def wrap(self, aW, aH):
        self.bw = min(self.bw, aW)
        lh = self.size * 1.35
        self.bh = self.padding * 2 + len(self.lines) * lh
        return self.bw, self.bh

    def draw(self):
        c = self.canv
        c.setFillColor(self.bg)
        c.setStrokeColor(self.border)
        c.setLineWidth(1.2)
        c.roundRect(0, 0, self.bw, self.bh, 6, fill=1, stroke=1)
        c.setFillColor(DARK_GREY)
        c.setFont(self.font, self.size)
        lh = self.size * 1.35
        y = self.bh - self.padding - self.size
        for line in self.lines:
            c.drawString(self.padding, y, line)
            y -= lh


# ─── Style sheet ─────────────────────────────────────────────────────────────

def make_styles():
    base = getSampleStyleSheet()
    s = {}

    # Cover-page title
    s['cover_univ'] = ParagraphStyle('cover_univ', fontName='Helvetica-Bold',
        fontSize=13, leading=16, textColor=NAVY, alignment=TA_CENTER, spaceAfter=2)
    s['cover_faculty'] = ParagraphStyle('cover_faculty', fontName='Helvetica',
        fontSize=10, leading=13, textColor=NAVY, alignment=TA_CENTER, spaceAfter=4)
    s['cover_main'] = ParagraphStyle('cover_main', fontName='Helvetica-Bold',
        fontSize=28, leading=33, textColor=white, alignment=TA_CENTER, spaceAfter=2)
    s['cover_sub'] = ParagraphStyle('cover_sub', fontName='Helvetica',
        fontSize=13, leading=17, textColor=white, alignment=TA_CENTER, spaceAfter=6)
    s['cover_meta'] = ParagraphStyle('cover_meta', fontName='Helvetica',
        fontSize=10.5, leading=15, textColor=ACCENT, alignment=TA_CENTER, spaceAfter=3)

    # Section headers
    s['page_header'] = ParagraphStyle('page_header', fontName='Helvetica-Bold',
        fontSize=14, leading=18, textColor=white, alignment=TA_LEFT,
        leftIndent=8, spaceAfter=6)
    s['page_subhdr'] = ParagraphStyle('page_subhdr', fontName='Helvetica',
        fontSize=9.5, leading=13, textColor=white, alignment=TA_LEFT,
        leftIndent=8, spaceAfter=4)
    s['section_title'] = ParagraphStyle('section_title', fontName='Helvetica-Bold',
        fontSize=11.5, leading=15, textColor=TEAL, spaceBefore=8, spaceAfter=4)

    # Body
    s['body'] = ParagraphStyle('body', fontName='Helvetica',
        fontSize=8.8, leading=13, textColor=DARK_GREY, alignment=TA_JUSTIFY,
        spaceAfter=4)
    s['bullet'] = ParagraphStyle('bullet', fontName='Helvetica',
        fontSize=8.5, leading=12.5, textColor=DARK_GREY, leftIndent=14,
        firstLineIndent=-10, spaceAfter=2)
    s['bullet2'] = ParagraphStyle('bullet2', fontName='Helvetica',
        fontSize=8.2, leading=12, textColor=DARK_GREY, leftIndent=26,
        firstLineIndent=-10, spaceAfter=1.5)

    # Caption
    s['caption'] = ParagraphStyle('caption', fontName='Helvetica-Oblique',
        fontSize=7.8, leading=10, textColor=TEAL, alignment=TA_CENTER, spaceAfter=6)
    s['fig_label'] = ParagraphStyle('fig_label', fontName='Helvetica-Bold',
        fontSize=7.8, leading=10, textColor=TEAL, alignment=TA_CENTER)

    # Table
    s['tbl_hdr'] = ParagraphStyle('tbl_hdr', fontName='Helvetica-Bold',
        fontSize=8, leading=10, textColor=white, alignment=TA_CENTER)
    s['tbl_cell'] = ParagraphStyle('tbl_cell', fontName='Helvetica',
        fontSize=7.8, leading=10.5, textColor=DARK_GREY, alignment=TA_LEFT)
    s['tbl_cell_c'] = ParagraphStyle('tbl_cell_c', fontName='Helvetica',
        fontSize=7.8, leading=10.5, textColor=DARK_GREY, alignment=TA_CENTER)

    # Footer / misc
    s['footer'] = ParagraphStyle('footer', fontName='Helvetica',
        fontSize=7.5, textColor=MID_GREY, alignment=TA_CENTER)
    s['topics'] = ParagraphStyle('topics', fontName='Helvetica',
        fontSize=10, leading=15, textColor=NAVY, leftIndent=12, spaceAfter=3)
    s['conclusion'] = ParagraphStyle('conclusion', fontName='Helvetica',
        fontSize=8.8, leading=13.5, textColor=DARK_GREY, alignment=TA_JUSTIFY,
        spaceAfter=4)
    s['thank_you'] = ParagraphStyle('thank_you', fontName='Helvetica-Bold',
        fontSize=26, leading=32, textColor=NAVY, alignment=TA_CENTER, spaceBefore=20)
    s['thank_sub'] = ParagraphStyle('thank_sub', fontName='Helvetica',
        fontSize=11, leading=15, textColor=TEAL, alignment=TA_CENTER, spaceAfter=4)

    return s


# ─── Helper builders ─────────────────────────────────────────────────────────

def hline(color=MID_GREY, thickness=0.5):
    return HRFlowable(width='100%', thickness=thickness, color=color, spaceAfter=4, spaceBefore=2)

def sp(pts=6):
    return Spacer(1, pts)

def section_header_block(title, subtitle, s, width):
    """Navy bar with white title + subtitle."""
    bar_h = 36
    items = [
        (ColorBar(width, bar_h, NAVY), 0, 0, bar_h),
    ]
    # We'll use a Table with a coloured background instead
    data = [[Paragraph(title, s['page_header'])],
            [Paragraph(subtitle, s['page_subhdr'])]]
    tbl = Table(data, colWidths=[width])
    tbl.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), NAVY),
        ('TOPPADDING',    (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
        ('LEFTPADDING',   (0,0), (-1,-1), 10),
        ('RIGHTPADDING',  (0,0), (-1,-1), 10),
        ('ROWBACKGROUNDS',(0,0), (-1,-1), [NAVY]),
    ]))
    return tbl

def key_points_box(title, points, s, width):
    """Red-bordered key-points box."""
    content = [Paragraph(f'<b>{title}</b>', ParagraphStyle('kp_title',
        fontName='Helvetica-Bold', fontSize=9, leading=12,
        textColor=RED_BORDER, spaceAfter=3))]
    for pt in points:
        content.append(Paragraph(f'• {pt}', ParagraphStyle('kp_pt',
            fontName='Helvetica', fontSize=8.2, leading=12,
            textColor=DARK_GREY, leftIndent=8, spaceAfter=1)))
    data = [[content]]
    tbl = Table([[content]], colWidths=[width])
    tbl.setStyle(TableStyle([
        ('BACKGROUND',    (0,0), (-1,-1), RED_LIGHT),
        ('BOX',           (0,0), (-1,-1), 1.2, RED_BORDER),
        ('ROUNDEDCORNERS',[4]),
        ('TOPPADDING',    (0,0), (-1,-1), 8),
        ('BOTTOMPADDING', (0,0), (-1,-1), 8),
        ('LEFTPADDING',   (0,0), (-1,-1), 10),
        ('RIGHTPADDING',  (0,0), (-1,-1), 10),
    ]))
    return tbl

def img_with_caption(path, caption, s, img_w, img_h, label=''):
    """Return [Image, caption Paragraph] as a list."""
    elements = []
    if os.path.exists(path):
        im = Image(path, width=img_w, height=img_h)
        im.hAlign = 'CENTER'
        elements.append(im)
    if label:
        elements.append(Paragraph(label, s['fig_label']))
    elements.append(Paragraph(caption, s['caption']))
    return elements


# ─── Page callback for headers/footers ───────────────────────────────────────

PAGE_TITLES = {
    1: '',  # cover
    2: 'Atypical Cardiomyopathies in Children & Adolescents',
    3: 'Atypical Cardiomyopathies in Children & Adolescents',
    4: 'Atypical Cardiomyopathies in Children & Adolescents',
    5: 'Atypical Cardiomyopathies in Children & Adolescents',
}

def on_page(canvas, doc):
    pg = doc.page
    if pg == 1:
        return
    canvas.saveState()
    # Top rule
    canvas.setStrokeColor(NAVY)
    canvas.setLineWidth(1.5)
    canvas.line(MARGIN, H - 14*mm, W - MARGIN, H - 14*mm)
    # Running head
    canvas.setFont('Helvetica', 7.5)
    canvas.setFillColor(NAVY)
    canvas.drawString(MARGIN, H - 11*mm, PAGE_TITLES.get(pg, ''))
    canvas.drawRightString(W - MARGIN, H - 11*mm, 'Raghul Balaji | 4th MBBS | Gr 8')
    # Bottom rule
    canvas.setStrokeColor(MID_GREY)
    canvas.setLineWidth(0.8)
    canvas.line(MARGIN, 14*mm, W - MARGIN, 14*mm)
    canvas.setFont('Helvetica', 7.5)
    canvas.setFillColor(MID_GREY)
    canvas.drawCentredString(W/2, 10*mm,
        f'Atypical Cardiomyopathies in Children & Adolescents   |   Page {pg} of 5')
    canvas.restoreState()


# ─── Content builders ─────────────────────────────────────────────────────────

def build_cover(s, cw):
    story = []
    story.append(sp(28))

    # University badge area
    uni_data = [
        [Paragraph('JALALABAD STATE UNIVERSITY', s['cover_univ'])],
        [Paragraph('Faculty of Medicine — Named after B. Osmonova', s['cover_faculty'])],
    ]
    uni_tbl = Table(uni_data, colWidths=[cw])
    uni_tbl.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), ACCENT),
        ('BOX',        (0,0), (-1,-1), 1.5, NAVY),
        ('TOPPADDING',    (0,0), (-1,-1), 10),
        ('BOTTOMPADDING', (0,0), (-1,-1), 10),
    ]))
    story.append(uni_tbl)
    story.append(sp(30))

    # Hero banner
    hero_data = [
        [Paragraph('ATYPICAL FORMS OF', s['cover_main'])],
        [Paragraph('CARDIOMYOPATHY', s['cover_main'])],
        [Paragraph('in Children and Adolescents', s['cover_sub'])],
    ]
    hero_tbl = Table(hero_data, colWidths=[cw])
    hero_tbl.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), NAVY),
        ('TOPPADDING',    (0,0), (-1,-1), 14),
        ('BOTTOMPADDING', (0,0), (-1,-1), 14),
        ('ROWBACKGROUNDS',(0,0), (-1,-1), [NAVY]),
    ]))
    story.append(hero_tbl)
    story.append(sp(20))

    # Topic block
    topic_title = Paragraph('<b>Topics Covered</b>', ParagraphStyle('tp', fontName='Helvetica-Bold',
        fontSize=11, textColor=TEAL, alignment=TA_CENTER, spaceAfter=8))
    topics = [
        '● Left Ventricular Non-Compaction (LVNC)',
        '● Arrhythmogenic Cardiomyopathy (ACM / ARVC)',
        '● Restrictive Cardiomyopathy (RCM)',
        '● Takotsubo & Myocarditis-related Cardiomyopathy',
        '● Metabolic / Storage Cardiomyopathies',
    ]
    topic_rows = [[topic_title]]
    for t in topics:
        topic_rows.append([Paragraph(t, s['topics'])])
    topic_tbl = Table(topic_rows, colWidths=[cw])
    topic_tbl.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), ACCENT),
        ('BOX',        (0,0), (-1,-1), 1, TEAL),
        ('TOPPADDING',    (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
        ('LEFTPADDING',   (0,0), (-1,-1), 16),
    ]))
    story.append(topic_tbl)
    story.append(sp(30))

    # Author info table
    meta_rows = [
        ['Topic :-', 'Long-term monitoring and atypical forms of cardiomyopathy'],
        ['Done by :-', 'Raghul Balaji'],
        ['Year :-', '4th MBBS'],
        ['Group :-', '8th'],
    ]
    meta_style = ParagraphStyle('meta_l', fontName='Helvetica-Bold',
        fontSize=10, textColor=NAVY)
    meta_style_r = ParagraphStyle('meta_r', fontName='Helvetica',
        fontSize=10, textColor=DARK_GREY)
    meta_data = [[Paragraph(r[0], meta_style), Paragraph(r[1], meta_style_r)] for r in meta_rows]
    meta_tbl = Table(meta_data, colWidths=[cw*0.28, cw*0.72])
    meta_tbl.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), white),
        ('BOX',        (0,0), (-1,-1), 1.2, NAVY),
        ('INNERGRID',  (0,0), (-1,-1), 0.4, MID_GREY),
        ('TOPPADDING',    (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
        ('LEFTPADDING',   (0,0), (-1,-1), 12),
        ('ROWBACKGROUNDS',(0,0), (-1,-1), [ACCENT, white, ACCENT, white]),
        # Highlight "Done by" row
        ('BACKGROUND', (0,1), (-1,1), HexColor('#D0EAF5')),
        ('FONTNAME',   (1,1), (1,1), 'Helvetica-Bold'),
    ]))
    story.append(meta_tbl)
    return story


def build_page2(s, cw, img_path):
    """LVNC page"""
    story = []
    story.append(sp(8))

    # Header bar
    story.append(section_header_block(
        'Introduction &amp; LVNC',
        'Overview of atypical cardiomyopathies · Left Ventricular Non-Compaction',
        s, cw))
    story.append(sp(10))

    # Intro paragraph
    story.append(Paragraph('<b>Introduction :-</b>', s['section_title']))
    story.append(Paragraph(
        'Cardiomyopathies are myocardial diseases with structural and functional abnormality in the '
        'absence of coronary artery disease, hypertension, or valvular disease. While dilated (DCM) and '
        'hypertrophic (HCM) forms are well-known, a significant subset in children falls into atypical forms — '
        'rare, heterogeneous, and often under-recognised. These represent a major cause of heart failure, '
        'sudden cardiac death (SCD), and cardiac transplantation in the young. Modern tools — cardiac MRI '
        '(CMR), genetic panels, and advanced echocardiography — allow precise phenotyping and guide '
        'individualised management.', s['body']))

    story.append(hline())
    story.append(Paragraph('<b>1. Left Ventricular Non-Compaction (LVNC) :-</b>', s['section_title']))

    # Two-column: text left, image right
    lvnc_bullets = [
        '<b>Pathophysiology:</b> Arrest of normal myocardial compaction at 5–8 weeks gestation → '
        'prominent trabeculations + deep intertrabecular recesses communicating with LV cavity',
        '<b>Genetics:</b> TAZ (Barth syndrome, X-linked), MYH7, MYBPC3, LDB3, ACTC1; 30–50% have an '
        'affected first-degree relative',
        '<b>Associations:</b> Barth syndrome (DCM+LVNC+neutropenia), Danon disease, Noonan, '
        'mitochondrial disorders',
        '<b>Diagnosis:</b> Echo NC:C ratio &gt;2.0 (adult), &gt;1.4 (paediatric); CMR = gold standard — '
        'confirms NC extent + late gadolinium enhancement (LGE)',
        '<b>Classic triad:</b> Heart failure · Ventricular arrhythmias · Thromboembolism',
        '<b>Management:</b> ACEi + beta-blockers + diuretics; anticoagulation if EF &lt;35% or AF; '
        'ICD for high-risk VT/syncope; transplant for end-stage disease',
    ]
    text_content = [[Paragraph(b, s['bullet'])] for b in lvnc_bullets]
    text_tbl = Table(text_content, colWidths=[cw * 0.55])
    text_tbl.setStyle(TableStyle([
        ('TOPPADDING', (0,0),(-1,-1), 2),
        ('BOTTOMPADDING',(0,0),(-1,-1), 2),
        ('LEFTPADDING',  (0,0),(-1,-1), 0),
        ('RIGHTPADDING', (0,0),(-1,-1), 0),
    ]))

    # Image + caption
    img_w = cw * 0.40
    img_h = img_w * 0.72
    img_cap_content = []
    if os.path.exists(img_path):
        im = Image(img_path, width=img_w, height=img_h)
        im.hAlign = 'CENTER'
        img_cap_content.append(im)
    img_cap_content.append(Paragraph(
        '<i>LVNC Echo: NC:C &gt;2, apical trabeculations</i>', s['caption']))
    img_cap_content.append(Paragraph(
        'Fig 1 – LVNC echocardiogram: prominent trabeculations, NC:C &gt;2', s['fig_label']))

    from reportlab.platypus import KeepInFrame
    img_tbl = Table([[img_cap_content]], colWidths=[cw * 0.43])
    img_tbl.setStyle(TableStyle([
        ('ALIGN',        (0,0),(-1,-1), 'CENTER'),
        ('VALIGN',       (0,0),(-1,-1), 'TOP'),
        ('TOPPADDING',   (0,0),(-1,-1), 0),
        ('BOTTOMPADDING',(0,0),(-1,-1), 0),
        ('LEFTPADDING',  (0,0),(-1,-1), 0),
        ('RIGHTPADDING', (0,0),(-1,-1), 0),
        ('BOX',          (0,0),(-1,-1), 0.8, TEAL),
        ('BACKGROUND',   (0,0),(-1,-1), ACCENT),
    ]))

    two_col = Table([[text_tbl, img_tbl]], colWidths=[cw*0.57, cw*0.43])
    two_col.setStyle(TableStyle([
        ('VALIGN',       (0,0),(-1,-1), 'TOP'),
        ('LEFTPADDING',  (0,0),(-1,-1), 0),
        ('RIGHTPADDING', (0,0),(-1,-1), 4),
        ('TOPPADDING',   (0,0),(-1,-1), 0),
        ('BOTTOMPADDING',(0,0),(-1,-1), 0),
    ]))
    story.append(two_col)
    story.append(sp(8))

    # Key points box
    story.append(key_points_box('✦  LVNC Key Points', [
        '1–7% of all paediatric cardiomyopathies; most common in infancy',
        'Barth syndrome = LVNC + DCM + neutropenia + 3-methylglutaconic aciduria (TAZ mutation)',
        'CMR gold standard; differentiates from HCM by absence of marked LV hypertrophy',
    ], s, cw))
    return story


def build_page3(s, cw, img_path):
    """ARVC page"""
    story = []
    story.append(sp(8))
    story.append(section_header_block(
        'Arrhythmogenic Cardiomyopathy (ACM / ARVC)',
        'Leading cause of SCD in young athletes — desmosomal disease',
        s, cw))
    story.append(sp(10))

    story.append(Paragraph('<b>2. Arrhythmogenic Cardiomyopathy (ACM / ARVC) :-</b>', s['section_title']))
    story.append(Paragraph(
        'ACM is a heritable cardiomyopathy characterised by fibrofatty replacement of the myocardium, '
        'predominantly the right ventricle (though biventricular and LV-dominant forms exist). It is the leading '
        'cause of SCD in young competitive athletes, accounting for up to 20% of sport-related deaths. '
        'Physical exercise accelerates disease progression by stressing defective desmosomes.', s['body']))

    # Two-column: text + image
    arvc_bullets = [
        '<b>Genetics:</b> PKP2 (~40%), DSP, DSG2, DSC2, JUP mutations → impaired desmosomal adhesion '
        '→ apoptosis → fibrofatty remodelling',
        '<b>Classic triangle of dysplasia:</b> RVOT · RV apex · Subtricuspid area',
        '<b>Paediatric ACM:</b> LV-dominant or biventricular forms more common than adults; worse prognosis',
    ]
    text_content = [[Paragraph(b, s['bullet'])] for b in arvc_bullets]
    text_tbl = Table(text_content, colWidths=[cw * 0.55])
    text_tbl.setStyle(TableStyle([
        ('TOPPADDING', (0,0),(-1,-1), 2),
        ('BOTTOMPADDING',(0,0),(-1,-1), 2),
        ('LEFTPADDING',  (0,0),(-1,-1), 0),
        ('RIGHTPADDING', (0,0),(-1,-1), 0),
    ]))

    img_w = cw * 0.40
    img_h = img_w * 0.68
    img_cap_content = []
    if os.path.exists(img_path):
        im = Image(img_path, width=img_w, height=img_h)
        im.hAlign = 'CENTER'
        img_cap_content.append(im)
    img_cap_content.append(Paragraph(
        '<i>ARVC CMR: Fatty RV replacement, RV dilatation</i>', s['caption']))
    img_cap_content.append(Paragraph(
        'Fig 2 – CMR in ARVC: fatty RV free wall replacement and RV dilatation', s['fig_label']))

    img_tbl = Table([[img_cap_content]], colWidths=[cw * 0.43])
    img_tbl.setStyle(TableStyle([
        ('ALIGN',        (0,0),(-1,-1), 'CENTER'),
        ('VALIGN',       (0,0),(-1,-1), 'TOP'),
        ('TOPPADDING',   (0,0),(-1,-1), 0),
        ('BOTTOMPADDING',(0,0),(-1,-1), 0),
        ('LEFTPADDING',  (0,0),(-1,-1), 0),
        ('RIGHTPADDING', (0,0),(-1,-1), 0),
        ('BOX',          (0,0),(-1,-1), 0.8, TEAL),
        ('BACKGROUND',   (0,0),(-1,-1), ACCENT),
    ]))

    two_col = Table([[text_tbl, img_tbl]], colWidths=[cw*0.57, cw*0.43])
    two_col.setStyle(TableStyle([
        ('VALIGN',       (0,0),(-1,-1), 'TOP'),
        ('LEFTPADDING',  (0,0),(-1,-1), 0),
        ('RIGHTPADDING', (0,0),(-1,-1), 4),
        ('TOPPADDING',   (0,0),(-1,-1), 0),
        ('BOTTOMPADDING',(0,0),(-1,-1), 0),
    ]))
    story.append(two_col)
    story.append(sp(6))

    # Diagnosis criteria box
    story.append(Paragraph('<b>Diagnosis — 2010 Revised Task Force Criteria</b>', s['section_title']))
    diag_note = Paragraph(
        '<i>Definite: 2 major | 1 major + 2 minor | 4 minor criteria from different categories</i>',
        ParagraphStyle('diag_n', fontName='Helvetica-Oblique', fontSize=8, textColor=TEAL,
                       spaceAfter=4))
    story.append(diag_note)

    c1 = [
        Paragraph('<b>Structural (Major):</b> RV regional akinesia/dyskinesia + RVEDV/BSA ≥110 (M)/100 (F) mL/m² on CMR/echo', s['bullet']),
        Paragraph('<b>Tissue (Major):</b> Fibrofatty replacement on biopsy (residual myocytes &lt;60%)', s['bullet']),
        Paragraph('<b>Repolarisation (Major):</b> T-wave inversions V1–V4 in &gt;14 yr without complete RBBB', s['bullet']),
    ]
    c2 = [
        Paragraph('<b>Depolarisation (Major):</b> Epsilon wave in V1–V3', s['bullet']),
        Paragraph('<b>Arrhythmia (Major):</b> Sustained/non-sustained VT with LBBB morphology, superior axis', s['bullet']),
        Paragraph('<b>Family (Major):</b> First-degree relative with confirmed ACM or identified pathogenic mutation', s['bullet']),
    ]
    diag_tbl = Table([[c1, c2]], colWidths=[cw*0.50, cw*0.50])
    diag_tbl.setStyle(TableStyle([
        ('VALIGN',       (0,0),(-1,-1), 'TOP'),
        ('TOPPADDING',   (0,0),(-1,-1), 0),
        ('BOTTOMPADDING',(0,0),(-1,-1), 0),
        ('LEFTPADDING',  (0,0),(-1,-1), 2),
        ('RIGHTPADDING', (0,0),(-1,-1), 2),
        ('LINEBEFORE',   (1,0),(1,-1), 0.5, MID_GREY),
    ]))
    story.append(diag_tbl)
    story.append(sp(6))

    # Management
    story.append(Paragraph('<b>Management</b>', s['section_title']))
    mgmt = [
        '<b>Mandatory sport restriction</b> — exercise is the most important modifiable trigger for disease progression',
        '<b>Beta-blockers</b> (sotalol / amiodarone) for arrhythmia suppression; ICD mandatory in high-risk patients (SCD survivors, sustained VT, syncope, severe RV dysfunction)',
        '<b>Catheter ablation</b> for recurrent VT storms; cardiac transplantation for end-stage disease',
    ]
    for m in mgmt:
        story.append(Paragraph(f'• {m}', s['bullet']))
    story.append(sp(6))

    story.append(key_points_box('✦  ARVC Key Points', [
        'Epsilon wave (low-amp signal after QRS in V1–V3) = pathognomonic ECG sign of ARVC',
        'LBBB-morphology VT in a young athlete = suspect ARVC; screen all first-degree relatives',
        'PKP2 most common mutation (~40%); exercise restriction is life-saving even pre-symptomatically',
    ], s, cw))
    return story


def build_page4(s, cw, img_path):
    """RCM + Takotsubo + Myocarditis page"""
    story = []
    story.append(sp(8))
    story.append(section_header_block(
        'RCM · Takotsubo · Myocarditis-related CMP',
        'Restrictive · Stress · Inflammatory cardiomyopathies in children',
        s, cw))
    story.append(sp(10))

    story.append(Paragraph('<b>3. Restrictive Cardiomyopathy (RCM) :-</b>', s['section_title']))

    rcm_bullets = [
        '<b>Etiology:</b> Idiopathic (most common in children; TNNI3, MYH7, ACTC1 mutations); '
        'infiltrative (amyloid, Gaucher, Fabry); fibrotic (post-myocarditis, scleroderma)',
        '<b>Pathophysiology:</b> Non-compliant stiff ventricles → elevated filling pressures → '
        'biatrial enlargement → pulmonary venous/arterial hypertension',
        '<b>Clinical:</b> Dyspnoea, exercise intolerance, hepatomegaly, ascites, AF, thromboembolism',
        '<b>Diagnosis:</b> Echo — biatrial enlargement + diastolic dysfunction Grade III/IV (E/A &gt;2, '
        'DT &lt;150 ms, E/e\' &gt;15); CMR ± LGE; endomyocardial biopsy',
        '<b>Mx:</b> Diuretics, anticoagulation; NO disease-modifying therapy; early cardiac transplant '
        'listing — worst prognosis of all paediatric CMPs; 5-yr survival ~50% without Tx',
    ]
    text_content = [[Paragraph(b, s['bullet'])] for b in rcm_bullets]
    text_tbl = Table(text_content, colWidths=[cw * 0.55])
    text_tbl.setStyle(TableStyle([
        ('TOPPADDING', (0,0),(-1,-1), 2),
        ('BOTTOMPADDING',(0,0),(-1,-1), 2),
        ('LEFTPADDING',  (0,0),(-1,-1), 0),
        ('RIGHTPADDING', (0,0),(-1,-1), 0),
    ]))

    img_w = cw * 0.40
    img_h = img_w * 0.72
    img_cap_content = []
    if os.path.exists(img_path):
        im = Image(img_path, width=img_w, height=img_h)
        im.hAlign = 'CENTER'
        img_cap_content.append(im)
    img_cap_content.append(Paragraph(
        '<i>RCM CMR: Biatrial enlargement, normal LV</i>', s['caption']))
    img_cap_content.append(Paragraph(
        'Fig 3 – CMR in RCM: biatrial enlargement, normal ventricular dimensions, preserved LVEF',
        s['fig_label']))

    img_tbl = Table([[img_cap_content]], colWidths=[cw * 0.43])
    img_tbl.setStyle(TableStyle([
        ('ALIGN',        (0,0),(-1,-1), 'CENTER'),
        ('VALIGN',       (0,0),(-1,-1), 'TOP'),
        ('TOPPADDING',   (0,0),(-1,-1), 0),
        ('BOTTOMPADDING',(0,0),(-1,-1), 0),
        ('LEFTPADDING',  (0,0),(-1,-1), 0),
        ('RIGHTPADDING', (0,0),(-1,-1), 0),
        ('BOX',          (0,0),(-1,-1), 0.8, TEAL),
        ('BACKGROUND',   (0,0),(-1,-1), ACCENT),
    ]))

    two_col = Table([[text_tbl, img_tbl]], colWidths=[cw*0.57, cw*0.43])
    two_col.setStyle(TableStyle([
        ('VALIGN',       (0,0),(-1,-1), 'TOP'),
        ('LEFTPADDING',  (0,0),(-1,-1), 0),
        ('RIGHTPADDING', (0,0),(-1,-1), 4),
        ('TOPPADDING',   (0,0),(-1,-1), 0),
        ('BOTTOMPADDING',(0,0),(-1,-1), 0),
    ]))
    story.append(two_col)
    story.append(sp(8))

    # Takotsubo + Myocarditis side-by-side
    story.append(Paragraph('<b>4. Takotsubo (Stress) CMP &amp; 5. Myocarditis-related CMP :-</b>', s['section_title']))
    tako_rows = [
        [Paragraph('<b>Takotsubo CMP</b>', ParagraphStyle('t_h', fontName='Helvetica-Bold',
            fontSize=9, textColor=white)),
         Paragraph('<b>Myocarditis-related CMP</b>', ParagraphStyle('t_h2', fontName='Helvetica-Bold',
            fontSize=9, textColor=white))],
        [Paragraph('• Rare in children; stress-induced catecholamine surge → transient apical LV ballooning', s['bullet']),
         Paragraph('• Viral triggers: Coxsackie B, adenovirus, parvovirus B19, SARS-CoV-2/MIS-C', s['bullet'])],
        [Paragraph('• Triggers: emotional stress, seizures, SAH, pheochromocytoma', s['bullet']),
         Paragraph('• Acute: DCM-like systolic dysfunction; Chronic: fibrosis → ACM phenocopy', s['bullet'])],
        [Paragraph('• ECG: ST elevation / deep T inversions; normal coronaries', s['bullet']),
         Paragraph('• CMR: T2↑ (oedema) + mid-wall LGE (fibrosis); Biopsy: Dallas criteria', s['bullet'])],
        [Paragraph('• Usually reversible in 4–8 weeks; Rx = supportive (beta-blockers, ACEi)', s['bullet']),
         Paragraph('• Rx: IVIG (fulminant); immunosuppression (chronic); standard HF therapy', s['bullet'])],
    ]
    tako_tbl = Table(tako_rows, colWidths=[cw*0.50, cw*0.50])
    tako_tbl.setStyle(TableStyle([
        ('BACKGROUND',    (0,0), (-1,0), TEAL),
        ('ROWBACKGROUNDS',(0,1), (-1,-1), [white, ACCENT]),
        ('BOX',           (0,0), (-1,-1), 1, TEAL),
        ('INNERGRID',     (0,0), (-1,-1), 0.4, MID_GREY),
        ('LINEBEFORE',    (1,0), (1,-1), 0.8, TEAL),
        ('TOPPADDING',    (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
        ('LEFTPADDING',   (0,0), (-1,-1), 8),
        ('VALIGN',        (0,0), (-1,-1), 'TOP'),
    ]))
    story.append(tako_tbl)
    story.append(sp(8))

    story.append(key_points_box('✦  RCM Key Points', [
        'Worst prognosis of all paediatric CMPs — early transplant listing is life-saving',
        'Key differentiator: constrictive pericarditis (septal bounce, pericardial calcification on CT) vs RCM (E/e\' >15, tissue Doppler)',
        'Any child with unexplained biatrial enlargement + pulmonary hypertension → suspect RCM',
    ], s, cw))
    return story


def build_page5(s, cw):
    """Metabolic + Summary + Conclusion page"""
    story = []
    story.append(sp(8))
    story.append(section_header_block(
        'Metabolic CMPs · Summary · Conclusion',
        'Storage disorders · Comparative table · Key takeaways',
        s, cw))
    story.append(sp(10))

    story.append(Paragraph('<b>6. Metabolic &amp; Storage Cardiomyopathies :-</b>', s['section_title']))
    story.append(Paragraph(
        'Metabolic cardiomyopathies arise from inherited enzyme deficiencies, lysosomal storage disorders, '
        'or mitochondrial dysfunction. Multi-system involvement is the clue — cardiac findings alongside '
        'neurological, skeletal, renal, or haematological features should prompt targeted enzyme assays and genetics.',
        s['body']))

    # Metabolic table
    h = lambda t: Paragraph(t, s['tbl_hdr'])
    c = lambda t: Paragraph(t, s['tbl_cell'])
    cc = lambda t: Paragraph(t, s['tbl_cell_c'])

    met_data = [
        [h('Disorder'), h('Gene/Defect'), h('CMP Phenotype'), h('Key Feature'), h('Treatment')],
        [c('Pompe (GSD II)'), cc('GAA'), cc('HCM-like'),
         c('Hypotonia, absent acid α-glucosidase'), c('ERT (alglucosidase alfa)')],
        [c('Fabry disease'), cc('GLA (XL)'), cc('HCM'),
         c('Renal, neuro, skin, corneal whorls'), c('ERT (agalsidase)')],
        [c('Barth syndrome'), cc('TAZ (XL)'), cc('DCM+LVNC'),
         c('Neutropenia, 3-MGA, myopathy'), c('Supportive; ERT trials')],
        [c('Danon disease'), cc('LAMP2 (XL)'), cc('HCM'),
         c('Cognitive impairment, WPW, retinopathy'), c('Transplant; gene therapy')],
        [c('Mitochondrial'), cc('mtDNA/nuclear'), cc('HCM or DCM'),
         c('Multi-system, lactic acidosis'), c('Supportive + cofactors')],
    ]
    col_w = [cw*0.19, cw*0.12, cw*0.14, cw*0.31, cw*0.24]
    met_tbl = Table(met_data, colWidths=col_w)
    met_tbl.setStyle(TableStyle([
        ('BACKGROUND',    (0,0), (-1,0), NAVY),
        ('ROWBACKGROUNDS',(0,1), (-1,-1), [white, LIGHT_GREY]),
        ('BOX',           (0,0), (-1,-1), 1, NAVY),
        ('INNERGRID',     (0,0), (-1,-1), 0.4, MID_GREY),
        ('TOPPADDING',    (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
        ('LEFTPADDING',   (0,0), (-1,-1), 5),
        ('RIGHTPADDING',  (0,0), (-1,-1), 5),
        ('VALIGN',        (0,0), (-1,-1), 'MIDDLE'),
        ('ALIGN',         (0,0), (-1,0), 'CENTER'),
    ]))
    story.append(met_tbl)
    story.append(sp(8))

    # Comparative summary table
    story.append(Paragraph('<b>Comparative Summary :-</b>', s['section_title']))
    sum_data = [
        [h('Type'), h('Key Genetics'), h('Hallmark Imaging'), h('ECG Sign'), h('Prognosis')],
        [c('LVNC'), c('TAZ, MYH7'), c('Echo NC:C&gt;2 / CMR'), c('LVH, WPW'), c('Variable')],
        [c('ACM/ARVC'), c('PKP2, DSP'), c('CMR fatty RV wall'), c('Epsilon wave, LBBB-VT'), c('SCD risk ↑')],
        [c('RCM'), c('TNNI3, MYH7'), c('Biatrial enlargement'), c('AF, CHB'), c('Worst')],
        [c('Takotsubo'), c('None'), c('Apical ballooning'), c('ST elevation'), c('Good')],
        [c('Metabolic'), c('Various'), c('HCM or DCM pattern'), c('Variable/WPW'), c('Disease-dep.')],
    ]
    col_w2 = [cw*0.14, cw*0.16, cw*0.25, cw*0.25, cw*0.20]
    sum_tbl = Table(sum_data, colWidths=col_w2)
    sum_tbl.setStyle(TableStyle([
        ('BACKGROUND',    (0,0), (-1,0), TEAL),
        ('ROWBACKGROUNDS',(0,1), (-1,-1), [white, ACCENT]),
        ('BOX',           (0,0), (-1,-1), 1, TEAL),
        ('INNERGRID',     (0,0), (-1,-1), 0.4, MID_GREY),
        ('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), 'MIDDLE'),
    ]))
    story.append(sum_tbl)
    story.append(sp(8))

    # Conclusion
    story.append(Paragraph('<b>Conclusion :-</b>', s['section_title']))
    story.append(Paragraph(
        'Atypical cardiomyopathies in children are clinically heterogeneous but share a need for early '
        'diagnosis, genetic workup, and family screening. LVNC and ARVC demand vigilance for SCD risk; RCM '
        'requires prompt transplant listing; Takotsubo is generally reversible; and metabolic CMPs benefit '
        'from targeted enzyme replacement. CMR, genetic panels, and multidisciplinary care are the '
        'cornerstones of modern paediatric cardiomyopathy management.', s['conclusion']))

    # Final key-points exam box
    story.append(key_points_box('✦  Final Key Points for Exams', [
        'LVNC: NC:C >2 on echo | Barth syndrome (TAZ) = LVNC+DCM+neutropenia',
        'ARVC: Epsilon wave + LBBB-VT in young athlete | PKP2 most common | restrict sport',
        'RCM: Worst prognosis | biatrial enlargement + preserved LVEF | early transplant list',
        'Takotsubo: Stress-triggered, apical ballooning, reversible — Rx supportive',
        'Metabolic: Pompe=GAA, Fabry=GLA, Barth=TAZ, Danon=LAMP2 — multisystem clues',
    ], s, cw))
    story.append(sp(16))

    # Thank you
    story.append(Paragraph('THANK YOU', s['thank_you']))
    story.append(sp(6))
    story.append(hline(TEAL, 1.5))
    story.append(Paragraph(
        'Raghul Balaji  |  4th Year MBBS  |  Group 8  |  Jalalabad State University',
        s['thank_sub']))
    return story


# ─── Main ─────────────────────────────────────────────────────────────────────

def main():
    out = '/home/daytona/workspace/cardiomyopathy-pdf/Atypical_Cardiomyopathy_Pediatrics_RaghulBalaji.pdf'
    base = '/home/daytona/workspace/cardiomyopathy-pdf'

    doc = SimpleDocTemplate(
        out,
        pagesize=A4,
        leftMargin=MARGIN, rightMargin=MARGIN,
        topMargin=20*mm, bottomMargin=20*mm,
        title='Atypical Forms of Cardiomyopathy in Children and Adolescents',
        author='Raghul Balaji',
        subject='Atypical Cardiomyopathies in Pediatrics',
        creator='Jalalabad State University – Faculty of Medicine',
    )
    cw = W - 2 * MARGIN   # usable content width
    s  = make_styles()

    story = []

    # ── Cover (page 1) ────────────────────────────────────────────────────────
    story += build_cover(s, cw)
    story.append(PageBreak())

    # ── Page 2: LVNC ─────────────────────────────────────────────────────────
    story += build_page2(s, cw, os.path.join(base, 'lvnc_echo.png'))
    story.append(PageBreak())

    # ── Page 3: ARVC ─────────────────────────────────────────────────────────
    story += build_page3(s, cw, os.path.join(base, 'arvc_cmr.jpg'))
    story.append(PageBreak())

    # ── Page 4: RCM + Takotsubo + Myocarditis ────────────────────────────────
    story += build_page4(s, cw, os.path.join(base, 'rcm_cmr.jpg'))
    story.append(PageBreak())

    # ── Page 5: Metabolic + Summary + Conclusion ──────────────────────────────
    story += build_page5(s, cw)

    doc.build(story, onFirstPage=on_page, onLaterPages=on_page)
    print(f'PDF saved → {out}')


if __name__ == '__main__':
    main()