import json
import subprocess
import base64
from io import BytesIO
from pptx import Presentation
from pptx.util import Inches, Pt, Emu
from pptx.dml.color import RGBColor
from pptx.enum.text import PP_ALIGN, MSO_ANCHOR
from pptx.util import Inches, Pt
from pptx.oxml.ns import qn
from lxml import etree

# ──────────────────── helpers ────────────────────
DARK_RED   = RGBColor(0x8B, 0x00, 0x00)   # deep maroon
DARK_BG    = RGBColor(0x1A, 0x1A, 0x2E)   # dark navy
ACCENT     = RGBColor(0xC0, 0x39, 0x2B)   # red accent
LIGHT_GRAY = RGBColor(0xF5, 0xF5, 0xF5)
WHITE      = RGBColor(0xFF, 0xFF, 0xFF)
DARK_GRAY  = RGBColor(0x2C, 0x2C, 0x54)
GOLD       = RGBColor(0xD4, 0xAC, 0x0D)
MID_RED    = RGBColor(0xA9, 0x3B, 0x26)
LIGHT_RED  = RGBColor(0xE8, 0x4C, 0x3C)
PALE_PINK  = RGBColor(0xFD, 0xED, 0xEC)

prs = Presentation()
prs.slide_width  = Inches(13.333)
prs.slide_height = Inches(7.5)
blank = prs.slide_layouts[6]

# ──────────────────── fetch images ────────────────────
URLS = [
    "https://upload.wikimedia.org/wikipedia/commons/2/21/Acute_Myeloid_Leukemia_%28M2_type%29.jpg",        # idx 0 – AML blood smear wiki
    "https://stjude.scene7.com/is/image/stjude/aml-leukemia-bm-m4?fit=crop,1&wid=600",                     # idx 1 – St Jude BM M4
    "https://d361swluvexzqs.cloudfront.net/chats-attachments/1000231836-1784477120666-bby7yr.jpg",          # idx 2 – book page (gum+BM)
    "https://imagebank.hematology.org/getimagebyid/62449?size=3",                                          # idx 3 – ASH image bank
    "https://media.istockphoto.com/id/2210327371/photo/acute-myeloid-leukemia-type-of-blood-cancer-in-which-the-bone-marrow-makes-abnormal-myeloblast.jpg?s=612x612&w=0&k=20&c=Q5z2EWrcOsy8ECK3pYx7IlqAJSzDwGsX7tXaT43C6eM=",   # idx 4 – istock AML
]

print("Fetching images...")
raw = subprocess.check_output(["python", "/tmp/skills/shared/scripts/fetch_images.py"] + URLS)
imgs_data = json.loads(raw)

def get_image(idx):
    d = imgs_data[idx]
    if d.get("base64"):
        mime, b64 = d["base64"].split(";base64,", 1)
        return BytesIO(base64.b64decode(b64))
    return None

# ──────────────────── utility functions ────────────────────
def add_rect(slide, x, y, w, h, fill_color=None, line_color=None, line_width=None, alpha=None):
    shape = slide.shapes.add_shape(1, Inches(x), Inches(y), Inches(w), Inches(h))
    if fill_color:
        shape.fill.solid()
        shape.fill.fore_color.rgb = fill_color
    else:
        shape.fill.background()
    if line_color:
        shape.line.color.rgb = line_color
        if line_width:
            shape.line.width = Pt(line_width)
    else:
        shape.line.fill.background()
    return shape

def add_text(slide, text, x, y, w, h, size=18, bold=False, color=WHITE,
             align=PP_ALIGN.LEFT, italic=False, wrap=True, v_anchor=None):
    tb = slide.shapes.add_textbox(Inches(x), Inches(y), Inches(w), Inches(h))
    tf = tb.text_frame
    tf.word_wrap = wrap
    if v_anchor:
        tf.vertical_anchor = v_anchor
    tf.margin_left  = Pt(4)
    tf.margin_right = Pt(4)
    tf.margin_top   = Pt(2)
    tf.margin_bottom= Pt(2)
    p = tf.paragraphs[0]
    p.alignment = align
    run = p.add_run()
    run.text = text
    run.font.size   = Pt(size)
    run.font.bold   = bold
    run.font.italic = italic
    run.font.color.rgb = color
    run.font.name   = "Calibri"
    return tb

def add_para(tf, text, size=13, bold=False, color=WHITE,
             align=PP_ALIGN.LEFT, space_before=0, bullet=False, italic=False):
    p = tf.add_paragraph()
    p.alignment = align
    if space_before:
        p.space_before = Pt(space_before)
    run = p.add_run()
    run.text = text
    run.font.size  = Pt(size)
    run.font.bold  = bold
    run.font.italic = italic
    run.font.color.rgb = color
    run.font.name  = "Calibri"
    if bullet:
        pPr = p._p.get_or_add_pPr()
        buChar = etree.SubElement(pPr, qn("a:buChar"))
        buChar.set("char", "•")
    return p

def add_image_safe(slide, img_io, x, y, w, h):
    if img_io is None:
        return None
    img_io.seek(0)
    try:
        pic = slide.shapes.add_picture(img_io, Inches(x), Inches(y), Inches(w), Inches(h))
        return pic
    except Exception as e:
        print(f"  Image add failed: {e}")
        return None

def add_header_bar(slide, title, subtitle=None):
    """Dark header banner across top."""
    add_rect(slide, 0, 0, 13.333, 1.3, fill_color=DARK_BG)
    add_rect(slide, 0, 1.3, 13.333, 0.07, fill_color=ACCENT)
    add_text(slide, title, 0.3, 0.05, 10, 0.75, size=30, bold=True, color=WHITE, v_anchor=MSO_ANCHOR.MIDDLE)
    if subtitle:
        add_text(slide, subtitle, 0.3, 0.8, 10, 0.45, size=14, color=GOLD, italic=True)
    # Red corner accent
    add_rect(slide, 12.5, 0, 0.833, 1.3, fill_color=ACCENT)

def slide_bg(slide):
    add_rect(slide, 0, 0, 13.333, 7.5, fill_color=LIGHT_GRAY)

# ═══════════════════════════════════════════════════════════
# SLIDE 1 – TITLE SLIDE
# ═══════════════════════════════════════════════════════════
s1 = prs.slides.add_slide(blank)
add_rect(s1, 0, 0, 13.333, 7.5, fill_color=DARK_BG)
# diagonal accent
add_rect(s1, 0, 5.8, 13.333, 0.12, fill_color=ACCENT)
add_rect(s1, 0, 5.92, 13.333, 1.58, fill_color=DARK_GRAY)

# Left image strip
img0 = get_image(0)
add_image_safe(s1, img0, 0.3, 1.0, 3.6, 4.5)

# Red overlay band
add_rect(s1, 3.9, 1.0, 0.15, 4.5, fill_color=ACCENT)

# Title text
add_text(s1, "ACUTE LEUKEMIA", 4.3, 1.4, 8.5, 1.3, size=44, bold=True, color=WHITE)
add_text(s1, "A Comprehensive Overview", 4.3, 2.75, 8.5, 0.6, size=22, italic=True, color=GOLD)
add_rect(s1, 4.3, 3.45, 7.5, 0.07, fill_color=ACCENT)
add_text(s1, "Based on AK Tripathi's Medicine – Chapter 4: Hematological System",
         4.3, 3.6, 8.5, 0.5, size=14, color=RGBColor(0xBB, 0xBB, 0xCC), italic=True)

add_text(s1, "Topics Covered:", 4.3, 4.2, 8.5, 0.45, size=15, bold=True, color=GOLD)
topics_tf_box = s1.shapes.add_textbox(Inches(4.3), Inches(4.65), Inches(8.5), Inches(1.0))
ttf = topics_tf_box.text_frame
ttf.word_wrap = True
for t in ["Definition & Classification  |  Pathophysiology  |  AML Clinical Features",
          "Diagnosis & Risk Stratification  |  Treatment of AML & ALL"]:
    add_para(ttf, t, size=12, color=RGBColor(0xCC, 0xCC, 0xEE))

add_text(s1, "Hematology  |  Internal Medicine", 4.3, 6.1, 8.5, 0.4, size=12,
         color=RGBColor(0x99, 0x99, 0xBB), italic=True)

print("Slide 1 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 2 – DEFINITION & OVERVIEW
# ═══════════════════════════════════════════════════════════
s2 = prs.slides.add_slide(blank)
slide_bg(s2)
add_header_bar(s2, "Definition & Overview", "What is Acute Leukemia?")

# Main content box
add_rect(s2, 0.3, 1.5, 7.8, 5.6, fill_color=WHITE)
add_rect(s2, 0.3, 1.5, 7.8, 0.05, fill_color=ACCENT)

tb = s2.shapes.add_textbox(Inches(0.5), Inches(1.6), Inches(7.5), Inches(5.0))
tf = tb.text_frame
tf.word_wrap = True

add_para(tf, "Definition", size=16, bold=True, color=DARK_RED, space_before=4)
add_para(tf, "Acute leukemia is a life-threatening hematological malignancy characterized by >20% blasts "
             "in either peripheral blood or bone marrow.", size=13, color=DARK_GRAY, bullet=False)
add_para(tf, "", size=6)
add_para(tf, "Classification", size=16, bold=True, color=DARK_RED, space_before=4)
add_para(tf, "Acute leukemias are broadly classified into two categories:", size=13, color=DARK_GRAY)
add_para(tf, "• Acute Lymphoblastic Leukemia (ALL)", size=13, color=DARK_GRAY, bold=True)
add_para(tf, "• Acute Myeloblastic Leukemia (AML)", size=13, color=DARK_GRAY, bold=True)
add_para(tf, "", size=6)
add_para(tf, "Epidemiology", size=16, bold=True, color=DARK_RED, space_before=4)
add_para(tf, "• 80% of pediatric leukemias are ALL (in contrast to adult preponderance of AML)", size=13, color=DARK_GRAY)
add_para(tf, "• AML median age of onset: 70 years", size=13, color=DARK_GRAY)
add_para(tf, "• Classification based on morphology: WHO 2016 revision (Table 4.13)", size=13, color=DARK_GRAY)

# Right side image
img4 = get_image(4)
add_image_safe(s2, img4, 8.4, 1.5, 4.5, 3.5)

# Caption
add_rect(s2, 8.4, 5.05, 4.5, 0.9, fill_color=DARK_GRAY)
add_text(s2, "AML – Abnormal myeloblasts in bone marrow (microscopy)",
         8.5, 5.1, 4.3, 0.8, size=11, color=WHITE, italic=True, wrap=True)

# Quote box at bottom right
add_rect(s2, 8.4, 6.05, 4.5, 0.95, fill_color=PALE_PINK)
add_rect(s2, 8.4, 6.05, 0.08, 0.95, fill_color=ACCENT)
add_text(s2, "Recently AML and ALL have been further subclassified based on WHO 2016 revision.",
         8.55, 6.1, 4.25, 0.85, size=10.5, color=DARK_GRAY, italic=True, wrap=True)

print("Slide 2 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 3 – CLASSIFICATION TABLE
# ═══════════════════════════════════════════════════════════
s3 = prs.slides.add_slide(blank)
slide_bg(s3)
add_header_bar(s3, "Classification of Acute Leukemia", "WHO & FAB Classification (Table 4.13)")

# Two column boxes
def classification_box(slide, x, title, items, col_color):
    add_rect(slide, x, 1.45, 4.0, 5.7, fill_color=WHITE)
    add_rect(slide, x, 1.45, 4.0, 0.55, fill_color=col_color)
    add_text(slide, title, x+0.15, 1.48, 3.7, 0.5, size=15, bold=True, color=WHITE,
             align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE)
    tb = slide.shapes.add_textbox(Inches(x+0.1), Inches(2.1), Inches(3.8), Inches(4.8))
    tf = tb.text_frame
    tf.word_wrap = True
    for item in items:
        add_para(tf, item, size=12.5, color=DARK_GRAY, bullet=("•" in item))
    return tf

aml_items = [
    "FAB Classification:",
    "• M0 – Undifferentiated",
    "• M1 – Myeloblastic",
    "• M2 – Myeloblastic with differentiation",
    "• M3 – Promyelocytic",
    "• M4 – Myelomonocytic",
    "• M5 – Monoblastic",
    "• M6 – Erythroleukemia",
    "• M7 – Megakaryoblastic",
    "",
    "WHO Types:",
    "• AML with recurrent genetic abnormalities",
    "• AML with myelodysplasia-related changes",
    "• Therapy-related AML",
    "• AML not otherwise specified",
    "• Myeloid sarcoma",
    "• Myeloid proliferations related to Down syndrome",
]

all_items = [
    "FAB Classification:",
    "• ALL-L1: small uniform cells",
    "• ALL-L2: large varied cells",
    "• ALL-L3: mature medium size cells",
    "",
    "WHO Types:",
    "• B lymphoblastic leukemia/lymphoma",
    "• T-lymphoblastic leukemia/lymphoma",
    "• Mature B cell leukemia",
    "• Early T-cell precursor ALL",
    "",
    "Key Facts:",
    "• B-ALL: 80% of all ALLs",
    "• Pre-B ALL: most common type (80%)",
    "• >80% long-term survival in pediatric ALL",
    "• Adults: only ~40% survival",
]

classification_box(s3, 0.3, "ACUTE MYELOID LEUKEMIA (AML)", aml_items, ACCENT)
classification_box(s3, 4.7, "ACUTE LYMPHOBLASTIC LEUKEMIA (ALL)", all_items, RGBColor(0x14, 0x6E, 0xBE))

# Middle divider
add_rect(s3, 4.5, 1.45, 0.06, 5.7, fill_color=ACCENT)

# Bottom note
add_rect(s3, 0.3, 7.1, 12.73, 0.32, fill_color=DARK_GRAY)
add_text(s3, "Reference: Table 4.13 – AK Tripathi's Medicine | Chapter 4: Hematological System",
         0.5, 7.12, 12.5, 0.28, size=10, color=WHITE, italic=True)

print("Slide 3 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 4 – PATHOPHYSIOLOGY
# ═══════════════════════════════════════════════════════════
s4 = prs.slides.add_slide(blank)
slide_bg(s4)
add_header_bar(s4, "Pathophysiology", "Mechanism of Leukemogenesis")

# Left panel
add_rect(s4, 0.3, 1.45, 7.3, 5.75, fill_color=WHITE)
add_rect(s4, 0.3, 1.45, 7.3, 0.05, fill_color=ACCENT)

tb = s4.shapes.add_textbox(Inches(0.45), Inches(1.55), Inches(7.0), Inches(5.5))
tf = tb.text_frame
tf.word_wrap = True

add_para(tf, "Core Mechanism", size=15, bold=True, color=DARK_RED, space_before=2)
add_para(tf, "Various cytogenetic and molecular abnormalities lead to uncontrolled proliferation "
             "of immature precursors and their defective maturation and differentiation.", size=12.5, color=DARK_GRAY)
add_para(tf, "", size=5)
add_para(tf, "Key Cellular Events", size=15, bold=True, color=DARK_RED, space_before=2)
add_para(tf, "• Immature cells (Blasts) fail to function normally", size=12.5, color=DARK_GRAY)
add_para(tf, "• Blasts replace the normal hematopoietic system in bone marrow", size=12.5, color=DARK_GRAY)
add_para(tf, "• Result: Cytopenias (low blood counts) and bone pains", size=12.5, color=DARK_GRAY)
add_para(tf, "", size=5)
add_para(tf, "Clinical Consequences of Cytopenias", size=15, bold=True, color=DARK_RED, space_before=2)

cytopenias = [
    ("Anemia (↓ RBCs)", "Weakness, pallor, fatigue, breathlessness"),
    ("Neutropenia (↓ WBCs)", "Infections – bacterial and fungal"),
    ("Thrombocytopenia (↓ Platelets)", "Bleeding manifestations, bruising"),
]
for cell, effect in cytopenias:
    add_para(tf, f"• {cell}: {effect}", size=12.5, color=DARK_GRAY)

add_para(tf, "", size=5)
add_para(tf, "• Immunocompromised state further increases risk of infections", size=12, color=DARK_GRAY, italic=True)

# Right panel – image + info boxes
img1 = get_image(1)
add_image_safe(s4, img1, 7.8, 1.45, 5.2, 3.3)
add_rect(s4, 7.8, 4.75, 5.2, 0.55, fill_color=DARK_GRAY)
add_text(s4, "Bone marrow: sheets of leukemic blasts replacing normal cells (AML-M4)",
         7.9, 4.78, 5.0, 0.5, size=10.5, color=WHITE, italic=True)

# Info box
add_rect(s4, 7.8, 5.45, 5.2, 1.7, fill_color=PALE_PINK)
add_rect(s4, 7.8, 5.45, 0.1, 1.7, fill_color=ACCENT)
tb2 = s4.shapes.add_textbox(Inches(8.0), Inches(5.5), Inches(4.9), Inches(1.6))
tf2 = tb2.text_frame
tf2.word_wrap = True
add_para(tf2, "Blast Cell Characteristics in AML:", size=13, bold=True, color=DARK_RED)
add_para(tf2, "• 3-5x larger than mature lymphocyte", size=12, color=DARK_GRAY)
add_para(tf2, "• Scant to moderate eosinophilic cytoplasm", size=12, color=DARK_GRAY)
add_para(tf2, "• Multiple prominent nucleoli", size=12, color=DARK_GRAY)
add_para(tf2, "• Auer rods present in ~45% of AML cases", size=12, color=DARK_GRAY, bold=True)

print("Slide 4 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 5 – AML CLINICAL FEATURES
# ═══════════════════════════════════════════════════════════
s5 = prs.slides.add_slide(blank)
slide_bg(s5)
add_header_bar(s5, "Acute Myeloid Leukemia – Clinical Features", "Median Age: 70 years | Acute Onset")

# 3-column card layout
def feature_card(slide, x, y, w, h, icon, heading, text, header_col=ACCENT):
    add_rect(slide, x, y, w, h, fill_color=WHITE)
    add_rect(slide, x, y, w, 0.5, fill_color=header_col)
    add_text(slide, f"{icon}  {heading}", x+0.08, y+0.04, w-0.15, 0.42, size=13, bold=True,
             color=WHITE, v_anchor=MSO_ANCHOR.MIDDLE)
    tb = slide.shapes.add_textbox(Inches(x+0.1), Inches(y+0.56), Inches(w-0.2), Inches(h-0.65))
    tf = tb.text_frame
    tf.word_wrap = True
    for line in text:
        add_para(tf, line, size=11.5, color=DARK_GRAY)
    return tf

cards = [
    ("🌡", "Fever", [
        "Very common in acute leukemia.",
        "Manifestation of disease itself",
        "OR due to opportunistic infection",
        "from functional neutropenia and",
        "compromised immune status.",
        "Bacterial & fungal infections",
        "are common in AML.",
    ], ACCENT),
    ("💪", "Weakness / Lethargy", [
        "Due to anemia and disease itself.",
        "Rapid onset weakness,",
        "exertional breathlessness,",
        "and loss of stamina.",
    ], RGBColor(0x6C, 0x35, 0x82)),
    ("🩸", "Bleeding Symptoms", [
        "Due to thrombocytopenia.",
        "Severe thrombocytopenia",
        "not rare in AML.",
        "APML – diffuse bleeding due",
        "to DIC (disseminated intravascular",
        "coagulopathy).",
    ], RGBColor(0x17, 0x6B, 0x87)),
    ("🦴", "Bone Pains", [
        "Due to expansion of bone",
        "marrow by rapidly proliferative",
        "leukemic cells.",
        "Rib pain, joint pain & pain in",
        "extremities is quite common.",
    ], RGBColor(0x0D, 0x7A, 0x5F)),
    ("🔬", "Hyperviscosity", [
        "Blast count >1,00,000/cmm OR",
        "myelocytic variant >50,000.",
        "Visual symptoms, giddiness,",
        "breathlessness, confusion &",
        "altered mentation.",
    ], RGBColor(0xC0, 0x7B, 0x1E)),
    ("🫀", "Other Features", [
        "Hepatosplenomegaly",
        "Lymphadenopathy",
        "Mass lesions & proptosis",
        "Myeloid sarcoma",
        "Gum hyperplasia (AML M4, M5)",
        "due to monocytic infiltration.",
    ], RGBColor(0x7B, 0x24, 0x1C)),
]

cols = [0.3, 4.55, 8.8]
rows = [1.45, 4.35]
for i, (icon, heading, text, hcol) in enumerate(cards):
    cx = cols[i % 3]
    cy = rows[i // 3]
    feature_card(s5, cx, cy, 4.0, 2.78, icon, heading, text, header_col=hcol)

print("Slide 5 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 6 – AML IMAGES (GUM HYPERPLASIA + BLAST CELLS)
# ═══════════════════════════════════════════════════════════
s6 = prs.slides.add_slide(blank)
slide_bg(s6)
add_header_bar(s6, "AML – Morphological Features & Images", "Fig. 4.12 & 4.13 from AK Tripathi")

# Left: textbook page image (gum + AML microscopy)
img2 = get_image(2)   # book page with gum hyperplasia + AML blast image
add_image_safe(s6, img2, 0.3, 1.45, 5.2, 5.75)

# Right content
add_rect(s6, 5.75, 1.45, 7.28, 2.7, fill_color=WHITE)
add_rect(s6, 5.75, 1.45, 7.28, 0.06, fill_color=ACCENT)
tb = s6.shapes.add_textbox(Inches(5.9), Inches(1.55), Inches(7.0), Inches(2.55))
tf = tb.text_frame
tf.word_wrap = True
add_para(tf, "Fig 4.12: Gum Hyperplasia (AML-M5)", size=14, bold=True, color=DARK_RED)
add_para(tf, "• Feature of monocytic leukemia (AML M4 & M5)", size=12, color=DARK_GRAY)
add_para(tf, "• Occurs due to gum infiltration by monocytic cells", size=12, color=DARK_GRAY)
add_para(tf, "• Tender, swollen, red, hypertrophied gingiva", size=12, color=DARK_GRAY)
add_para(tf, "", size=6)
add_para(tf, "Fig 4.13: Acute Myeloid Leukemia (BM)", size=14, bold=True, color=DARK_RED)
add_para(tf, "• Blasts are 3-5x larger than mature lymphocytes", size=12, color=DARK_GRAY)
add_para(tf, "• Scant to moderate eosinophilic cytoplasm", size=12, color=DARK_GRAY)
add_para(tf, "• Multiple prominent nucleoli", size=12, color=DARK_GRAY)
add_para(tf, "• Auer rods present in ~45% AML cases (PATHOGNOMONIC)", size=12, bold=True, color=ACCENT)
add_para(tf, "• Flowcytometry using acute leukemia panel confirms AML", size=12, color=DARK_GRAY)

# Right bottom – AML blood smear image
img0 = get_image(0)
add_image_safe(s6, img0, 5.75, 4.25, 3.8, 2.85)
add_rect(s6, 5.75, 7.1, 3.8, 0.35, fill_color=DARK_GRAY)
add_text(s6, "AML (M2 type) – peripheral blood smear (Wikimedia Commons)",
         5.8, 7.12, 3.7, 0.3, size=9.5, color=WHITE, italic=True)

# ASH image bank
img3 = get_image(3)
add_image_safe(s6, img3, 9.75, 4.25, 3.28, 2.85)
add_rect(s6, 9.75, 7.1, 3.28, 0.35, fill_color=DARK_GRAY)
add_text(s6, "AML blast cells – ASH Image Bank",
         9.8, 7.12, 3.2, 0.3, size=9.5, color=WHITE, italic=True)

print("Slide 6 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 7 – DIAGNOSIS & WORKUP (Table 4.14)
# ═══════════════════════════════════════════════════════════
s7 = prs.slides.add_slide(blank)
slide_bg(s7)
add_header_bar(s7, "Diagnostic Workup in Acute Leukemia", "Table 4.14 – AK Tripathi")

def col_box(slide, x, title, items, col=ACCENT):
    add_rect(slide, x, 1.45, 4.15, 5.85, fill_color=WHITE)
    add_rect(slide, x, 1.45, 4.15, 0.5, fill_color=col)
    add_text(slide, title, x+0.1, 1.47, 3.95, 0.46, size=13, bold=True, color=WHITE,
             align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE)
    tb = slide.shapes.add_textbox(Inches(x+0.1), Inches(2.02), Inches(3.95), Inches(5.2))
    tf = tb.text_frame
    tf.word_wrap = True
    for item in items:
        add_para(tf, item, size=12, color=DARK_GRAY)
    return tf

diag_items = [
    "Diagnostic & Prognostic:",
    "• Complete blood counts + peripheral smear",
    "• Bone marrow aspiration and biopsy",
    "• Flowcytometry (acute leukemia panel)",
    "• Karyotyping",
    "• Molecular studies",
    "• CSF examination",
    "",
    "Biochemical Parameters:",
    "• Serum LDH",
    "• Serum uric acid",
    "• Serum electrolytes: Na, K, Ca, PO4",
    "• Serum urea/creatinine",
    "• Liver function tests",
]

coag_items = [
    "Coagulation Parameters:",
    "• Prothrombin time (PT)",
    "• Activated partial thromboplastin time (aPTT)",
    "• FDP, D-Dimer",
    "",
    "Microbiology:",
    "• HbsAg, HCV, HIV",
    "",
    "Key Investigations:",
    "• Flowcytometry is INVESTIGATION OF CHOICE",
    "  to confirm AML diagnosis",
    "• Baseline CSF evaluation important – 5%",
    "  patients have CNS involvement",
    "• TLC >1,00,000/cmm – high risk for",
    "  Tumor Lysis Syndrome (TLS)",
]

col_box(s7, 0.3, "DIAGNOSTIC WORKUP", diag_items, ACCENT)
col_box(s7, 4.6, "ADDITIONAL TESTS & KEY POINTS", coag_items, RGBColor(0x14, 0x6E, 0xBE))

# Right info box
add_rect(s7, 9.1, 1.45, 4.0, 2.5, fill_color=RGBColor(0x2C, 0x3E, 0x50))
add_rect(s7, 9.1, 1.45, 4.0, 0.5, fill_color=RGBColor(0x0D, 0x7A, 0x5F))
add_text(s7, "Why Flowcytometry?", 9.2, 1.47, 3.8, 0.46, size=13, bold=True, color=WHITE,
         align=PP_ALIGN.CENTER)
tb7 = s7.shapes.add_textbox(Inches(9.2), Inches(2.02), Inches(3.8), Inches(1.85))
tf7 = tb7.text_frame
tf7.word_wrap = True
for txt in [
    "Identifies surface markers on",
    "blast cells (CD markers)",
    "Differentiates AML from ALL",
    "Determines lineage & subtype",
    "Essential for treatment planning",
]:
    add_para(tf7, f"• {txt}", size=12, color=WHITE)

# CSF note
add_rect(s7, 9.1, 4.1, 4.0, 3.2, fill_color=PALE_PINK)
add_rect(s7, 9.1, 4.1, 4.0, 0.5, fill_color=DARK_RED)
add_text(s7, "CSF & TLS Notes", 9.2, 4.12, 3.8, 0.46, size=13, bold=True, color=WHITE,
         align=PP_ALIGN.CENTER)
tb7b = s7.shapes.add_textbox(Inches(9.2), Inches(4.67), Inches(3.8), Inches(2.55))
tf7b = tb7b.text_frame
tf7b.word_wrap = True
for txt in [
    "Baseline CSF evaluation is important:",
    "5% patients have CNS involvement",
    "requiring CNS-directed therapy",
    "",
    "Tumor Lysis Syndrome (TLS):",
    "High risk if TLC >1,00,000/cmm",
    "or with Burkitt leukemia",
    "Baseline evaluation recommended",
    "for ALL patients",
]:
    add_para(tf7b, txt, size=11.5, color=DARK_GRAY)

print("Slide 7 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 8 – RISK STRATIFICATION (Tables 4.15 & 4.17)
# ═══════════════════════════════════════════════════════════
s8 = prs.slides.add_slide(blank)
slide_bg(s8)
add_header_bar(s8, "Risk Stratification", "Tables 4.15 & 4.17 – AML & ALL Cytogenetic Abnormalities")

# AML table
def draw_table_header(slide, x, y, headers, widths, col=ACCENT):
    curr_x = x
    for h, w in zip(headers, widths):
        add_rect(slide, curr_x, y, w, 0.38, fill_color=col)
        add_text(slide, h, curr_x+0.03, y+0.03, w-0.06, 0.32, size=10, bold=True, color=WHITE,
                 align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE)
        curr_x += w

def draw_table_row(slide, x, y, vals, widths, even=True):
    bg = RGBColor(0xF8, 0xF8, 0xF8) if even else WHITE
    curr_x = x
    for v, w in zip(vals, widths):
        add_rect(slide, curr_x, y, w, 0.32, fill_color=bg)
        col = ACCENT if v in ["Good", "Very Good"] else (DARK_RED if v in ["Poor", "Very Poor"] else DARK_GRAY)
        if v == "Intermediate Risk":
            col = RGBColor(0xD4, 0x7B, 0x0D)
        add_text(slide, v, curr_x+0.03, y+0.02, w-0.06, 0.28, size=10, color=col,
                 align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE,
                 bold=(v in ["Good", "Very Good", "Poor", "Very Poor", "Intermediate Risk"]))
        curr_x += w

# AML risk section
add_rect(s8, 0.3, 1.45, 6.0, 0.45, fill_color=ACCENT)
add_text(s8, "Table 4.15: Risk Stratification – Acute Myeloid Leukemia",
         0.35, 1.47, 5.9, 0.41, size=12, bold=True, color=WHITE, v_anchor=MSO_ANCHOR.MIDDLE)

hdrs = ["Cytogenetics", "Incidence", "Prognosis"]
ws   = [2.6, 1.5, 1.7]
draw_table_header(s8, 0.3, 1.9, hdrs, ws, col=DARK_GRAY)

aml_rows = [
    ("t(8;21)", "8-12%", "Good"),
    ("t(15;17)", "6-13%", "Very Good"),
    ("t(16;16)", "-", "Good"),
    ("Inv 16", "5-12%", "Good"),
    ("-5, del 5q", "7-10%", "Poor"),
    ("-7, del 7q", "10-12%", "Very Poor"),
    ("Normal cytogenetics", "50%", "Intermediate Risk"),
    ("Complex karyotype", "10-20%", "Very Poor"),
]
for i, row in enumerate(aml_rows):
    draw_table_row(s8, 0.3, 2.22 + i*0.32, row, ws, even=(i%2==0))

# Molecular
add_rect(s8, 0.3, 4.82, 6.0, 0.35, fill_color=DARK_GRAY)
add_text(s8, "Molecular Abnormalities", 0.35, 4.84, 5.9, 0.31, size=11, bold=True, color=WHITE)
mol_rows = [
    ("FLT-3 Mutation", "20-30%", "Poor"),
    ("NPM-1 Mutation", "20-40%", "Good"),
    ("CEBPA Biallelic", "5-10%", "Good"),
    ("C-KIT", "3-5%", "Poor"),
]
for i, row in enumerate(mol_rows):
    draw_table_row(s8, 0.3, 5.17 + i*0.32, row, ws, even=(i%2==0))

# ALL risk section
add_rect(s8, 6.6, 1.45, 6.43, 0.45, fill_color=RGBColor(0x14, 0x6E, 0xBE))
add_text(s8, "Table 4.17: Cytogenetic Abnormalities – Acute Lymphoblastic Leukemia",
         6.65, 1.47, 6.33, 0.41, size=12, bold=True, color=WHITE, v_anchor=MSO_ANCHOR.MIDDLE)

all_hdrs = ["Cytogenetic", "Mol. Transcript", "Incidence (Ped.)", "Prognosis"]
all_ws = [1.8, 1.6, 1.5, 1.33]
draw_table_header(s8, 6.6, 1.9, all_hdrs, all_ws, col=DARK_GRAY)

all_rows = [
    ("t(12;21)", "TEL-AML1", "20-25%", "Good"),
    ("t(9;22)", "BCR-ABL", "4%", "Very poor"),
    ("t(4;11)", "MLL-AF4", "8%", "Very poor"),
    ("t(8;14)", "IgH/MYC", "2%", "Good"),
    ("Hyperdiploidy", "-", "20-25%", "Good"),
    ("Hypodiploidy", "-", "6%", "Poor"),
]
for i, row in enumerate(all_rows):
    draw_table_row(s8, 6.6, 2.22 + i*0.32, row, all_ws, even=(i%2==0))

# Prognostic note
add_rect(s8, 6.6, 4.3, 6.43, 2.9, fill_color=PALE_PINK)
add_rect(s8, 6.6, 4.3, 0.1, 2.9, fill_color=RGBColor(0x14, 0x6E, 0xBE))
tb8 = s8.shapes.add_textbox(Inches(6.8), Inches(4.36), Inches(6.1), Inches(2.75))
tf8 = tb8.text_frame
tf8.word_wrap = True
add_para(tf8, "Overall Survival (OS) in AML:", size=12, bold=True, color=DARK_RED)
add_para(tf8, "• Overall OS ranges from 30-40%", size=11.5, color=DARK_GRAY)
add_para(tf8, "• Good risk patients: OS 50-60%", size=11.5, color=DARK_GRAY)
add_para(tf8, "• Poor risk patients: survival 10-20%", size=11.5, color=DARK_GRAY)
add_para(tf8, "• Age, performance status & comorbidities also impact prognosis", size=11.5, color=DARK_GRAY)
add_para(tf8, "", size=5)
add_para(tf8, "Philadelphia Chromosome (Ph+) in ALL:", size=12, bold=True, color=DARK_RED)
add_para(tf8, "• t(9;22) BCR-ABL – very poor prognosis (4%)", size=11.5, color=DARK_GRAY)
add_para(tf8, "• Benefits from TKI addition (Imatinib, Nilotinib, Dasatinib)", size=11.5, color=DARK_GRAY)

print("Slide 8 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 9 – TREATMENT OF AML
# ═══════════════════════════════════════════════════════════
s9 = prs.slides.add_slide(blank)
slide_bg(s9)
add_header_bar(s9, "Treatment of Acute Myeloid Leukemia", "Counseling → Supportive Care → Specific Treatment")

# Supportive care box
add_rect(s9, 0.3, 1.45, 6.0, 5.85, fill_color=WHITE)
add_rect(s9, 0.3, 1.45, 6.0, 0.5, fill_color=DARK_GRAY)
add_text(s9, "SUPPORTIVE TREATMENT", 0.4, 1.47, 5.8, 0.46, size=14, bold=True, color=WHITE,
         align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE)

tb9a = s9.shapes.add_textbox(Inches(0.45), Inches(2.02), Inches(5.75), Inches(5.2))
tf9a = tb9a.text_frame
tf9a.word_wrap = True

add_para(tf9a, "Anemia Management:", size=13, bold=True, color=DARK_RED)
add_para(tf9a, "• Transfusion of packed RBCs – target Hb ≥8 g/dL", size=12, color=DARK_GRAY)
add_para(tf9a, "", size=4)
add_para(tf9a, "Thrombocytopenia:", size=13, bold=True, color=DARK_RED)
add_para(tf9a, "• Platelet transfusion if count <10,000/cmm", size=12, color=DARK_GRAY)
add_para(tf9a, "  OR <20,000 with fever/bleeding", size=12, color=DARK_GRAY)
add_para(tf9a, "• Use SDP (1 unit) or RDP (4-6 units)", size=12, color=DARK_GRAY)
add_para(tf9a, "", size=4)
add_para(tf9a, "Infection Management:", size=13, bold=True, color=DARK_RED)
add_para(tf9a, "• Blood cultures before starting antibiotics", size=12, color=DARK_GRAY)
add_para(tf9a, "• Empirical broad-spectrum antibiotics immediately", size=12, color=DARK_GRAY)
add_para(tf9a, "• Prophylaxis: Allopurinol/Febuxostat, Rasburicase", size=12, color=DARK_GRAY)
add_para(tf9a, "• Antibiotic + Antiviral prophylaxis to be started", size=12, color=DARK_GRAY)
add_para(tf9a, "", size=4)
add_para(tf9a, "Tumor Lysis Prophylaxis:", size=13, bold=True, color=DARK_RED)
add_para(tf9a, "• Hydration, Allopurinol/Rasburicase", size=12, color=DARK_GRAY)
add_para(tf9a, "• Blood component support as indicated", size=12, color=DARK_GRAY)

# Specific treatment box
add_rect(s9, 6.6, 1.45, 6.43, 5.85, fill_color=WHITE)
add_rect(s9, 6.6, 1.45, 6.43, 0.5, fill_color=ACCENT)
add_text(s9, "SPECIFIC TREATMENT", 6.7, 1.47, 6.23, 0.46, size=14, bold=True, color=WHITE,
         align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE)

tb9b = s9.shapes.add_textbox(Inches(6.75), Inches(2.02), Inches(6.1), Inches(5.2))
tf9b = tb9b.text_frame
tf9b.word_wrap = True

add_para(tf9b, "Treatment depends on: Age, Performance Status,", size=12, color=DARK_GRAY, italic=True)
add_para(tf9b, "Cytogenetics & Molecular Abnormalities", size=12, color=DARK_GRAY, italic=True)
add_para(tf9b, "", size=5)
add_para(tf9b, "Induction Chemotherapy:", size=13, bold=True, color=DARK_RED)
add_para(tf9b, "• Standard: 3+7 Protocol", size=12, color=DARK_GRAY, bold=True)
add_para(tf9b, "• Daunorubicin + Cytarabine (7 days)", size=12, color=DARK_GRAY)
add_para(tf9b, "", size=4)
add_para(tf9b, "Consolidation:", size=13, bold=True, color=DARK_RED)
add_para(tf9b, "• 3-4 cycles with high-dose Cytosine Arabinoside", size=12, color=DARK_GRAY)
add_para(tf9b, "", size=4)
add_para(tf9b, "High-risk Patients:", size=13, bold=True, color=DARK_RED)
add_para(tf9b, "• Allogeneic stem cell transplant after induction", size=12, color=DARK_GRAY)
add_para(tf9b, "", size=4)
add_para(tf9b, "Targeted Therapies:", size=13, bold=True, color=DARK_RED)
add_para(tf9b, "• FLT-3 inhibitors, C-Kit inhibitors", size=12, color=DARK_GRAY)
add_para(tf9b, "• Demethylating agents: Azacitidine, Decitabine", size=12, color=DARK_GRAY)
add_para(tf9b, "• Low-dose Cytarabine (for elderly/comorbidities)", size=12, color=DARK_GRAY)
add_para(tf9b, "", size=4)
add_para(tf9b, "Drugs Used (Table 4.16):", size=13, bold=True, color=DARK_RED)
for d in ["Daunorubicin", "Cytosine arabinoside", "Etoposide", "All-trans retinoic acid (AML-M3)"]:
    add_para(tf9b, f"• {d}", size=12, color=DARK_GRAY)

print("Slide 9 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 10 – ALL CLINICAL FEATURES & DIAGNOSIS
# ═══════════════════════════════════════════════════════════
s10 = prs.slides.add_slide(blank)
slide_bg(s10)
add_header_bar(s10, "Acute Lymphoblastic Leukemia (ALL)", "Clinical Presentation & Diagnosis")

# Left col: clinical features
add_rect(s10, 0.3, 1.45, 6.0, 5.85, fill_color=WHITE)
add_rect(s10, 0.3, 1.45, 6.0, 0.5, fill_color=RGBColor(0x14, 0x6E, 0xBE))
add_text(s10, "CLINICAL PRESENTATION", 0.4, 1.47, 5.8, 0.46, size=14, bold=True, color=WHITE,
         align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE)

tb10a = s10.shapes.add_textbox(Inches(0.45), Inches(2.02), Inches(5.75), Inches(5.2))
tf10a = tb10a.text_frame
tf10a.word_wrap = True

add_para(tf10a, "Most Common Pediatric Leukemia", size=13, bold=True, color=DARK_RED)
add_para(tf10a, "Two types: B-ALL (80%) and T-ALL", size=12, color=DARK_GRAY)
add_para(tf10a, "", size=5)
add_para(tf10a, "Symptoms:", size=13, bold=True, color=DARK_RED)
for sym in [
    "Weakness & lethargy",
    "Fever",
    "Bleeding manifestations",
    "Swellings in neck and armpits",
    "Bone and joint pain (common in pediatric patients)",
]:
    add_para(tf10a, f"• {sym}", size=12, color=DARK_GRAY)
add_para(tf10a, "", size=5)
add_para(tf10a, "Clinical Examination Findings:", size=13, bold=True, color=DARK_RED)
for finding in [
    "Pallor",
    "Lymphadenopathy",
    "Variable hepatosplenomegaly",
    "Bone tenderness",
]:
    add_para(tf10a, f"• {finding}", size=12, color=DARK_GRAY)
add_para(tf10a, "", size=5)
add_para(tf10a, "Lymphoblast Characteristics:", size=13, bold=True, color=DARK_RED)
add_para(tf10a, "• 2-3x larger than mature lymphocytes", size=12, color=DARK_GRAY)
add_para(tf10a, "• Very high N:C ratio", size=12, color=DARK_GRAY)
add_para(tf10a, "• Scant basophilic agranular cytoplasm", size=12, color=DARK_GRAY)
add_para(tf10a, "• Inconspicuous nucleoli", size=12, color=DARK_GRAY)

# Right col: diagnosis
add_rect(s10, 6.6, 1.45, 6.43, 5.85, fill_color=WHITE)
add_rect(s10, 6.6, 1.45, 6.43, 0.5, fill_color=DARK_GRAY)
add_text(s10, "DIAGNOSIS & RISK STRATIFICATION", 6.7, 1.47, 6.23, 0.46, size=13, bold=True, color=WHITE,
         align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE)

tb10b = s10.shapes.add_textbox(Inches(6.75), Inches(2.02), Inches(6.1), Inches(5.2))
tf10b = tb10b.text_frame
tf10b.word_wrap = True

add_para(tf10b, "Diagnostic Workup:", size=13, bold=True, color=DARK_RED)
add_para(tf10b, "Similar to AML including:", size=12, color=DARK_GRAY, italic=True)
for d in ["CBC & peripheral smear", "Bone marrow evaluation", "Flowcytometry",
          "CSF analysis", "Cytogenetics & molecular studies"]:
    add_para(tf10b, f"• {d}", size=12, color=DARK_GRAY)
add_para(tf10b, "", size=5)
add_para(tf10b, "Key Investigation Points:", size=13, bold=True, color=DARK_RED)
add_para(tf10b, "• Flowcytometry helps diagnose ALL and subtype it", size=12, color=DARK_GRAY)
add_para(tf10b, "• Baseline TLC evaluation – risk of TLS", size=12, color=DARK_GRAY)
add_para(tf10b, "  (High TLC >1,00,000/cmm)", size=12, color=DARK_GRAY)
add_para(tf10b, "• Burkitt leukemia: high TLS risk", size=12, color=DARK_GRAY)
add_para(tf10b, "• Baseline CSF: 5% have CNS involvement", size=12, color=DARK_GRAY)
add_para(tf10b, "", size=5)
add_para(tf10b, "Prognosis:", size=13, bold=True, color=DARK_RED)
add_para(tf10b, "• Pediatric ALL: >80% long-term survival (cure)", size=12, bold=True, color=RGBColor(0x0D, 0x7A, 0x5F))
add_para(tf10b, "• Adults: poor – only ~40% survival", size=12, bold=True, color=DARK_RED)
add_para(tf10b, "", size=5)
add_para(tf10b, "High-Risk Features:", size=13, bold=True, color=DARK_RED)
for hr in [
    "Age <1 yr or >10 yrs",
    "WBC >50,000/cmm at presentation",
    "CNS or testicular involvement",
    "Philadelphia chromosome t(9;22)",
    "Hypodiploidy",
    "Poor response to induction",
]:
    add_para(tf10b, f"• {hr}", size=12, color=DARK_GRAY)

print("Slide 10 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 11 – TREATMENT OF ALL
# ═══════════════════════════════════════════════════════════
s11 = prs.slides.add_slide(blank)
slide_bg(s11)
add_header_bar(s11, "Treatment of Acute Lymphoblastic Leukemia", "Pediatric & Adult Protocols")

# Three phase boxes
def phase_box(slide, x, title, items, col):
    add_rect(slide, x, 1.45, 3.85, 5.85, fill_color=WHITE)
    add_rect(slide, x, 1.45, 3.85, 0.5, fill_color=col)
    add_text(slide, title, x+0.1, 1.47, 3.65, 0.46, size=13, bold=True, color=WHITE,
             align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE)
    tb = slide.shapes.add_textbox(Inches(x+0.1), Inches(2.02), Inches(3.65), Inches(5.2))
    tf = tb.text_frame
    tf.word_wrap = True
    for item in items:
        is_heading = item.endswith(":")
        add_para(tf, item, size=12 if not is_heading else 13,
                 bold=is_heading, color=DARK_RED if is_heading else DARK_GRAY)
    return tf

phase_box(s11, 0.3, "INDUCTION", [
    "Protocols:",
    "MCP-841, BFM-95, BFM 2002, UKALL",
    "",
    "Duration: ~2.5 years total",
    "",
    "Drugs include:",
    "• Dexamethasone/Prednisolone",
    "• Anthracycline (Daunorubicin)",
    "• Vincristine",
    "• L-Asparaginase",
    "",
    "Goal:",
    "Reduce disease burden to minimum",
    "Achieve complete remission",
], RGBColor(0x14, 0x6E, 0xBE))

phase_box(s11, 4.45, "CONSOLIDATION", [
    "Purpose:",
    "Further boost response achieved",
    "by induction chemotherapy",
    "Eradicate resistant clones",
    "",
    "Drugs:",
    "• High-dose Methotrexate",
    "• High-dose Cytarabine",
    "",
    "High-risk patients:",
    "Allogeneic stem cell transplant",
    "(2nd complete remission)",
    "",
    "Philadelphia+ patients:",
    "Add TKIs (Imatinib/Nilotinib/",
    "Dasatinib)",
], RGBColor(0x0D, 0x7A, 0x5F))

phase_box(s11, 8.6, "MAINTENANCE &\nCNS THERAPY", [
    "Long-term Maintenance:",
    "• 6-Mercaptopurine (6-MP)",
    "• Oral Methotrexate",
    "Prevents relapse at sanctuary sites",
    "",
    "CNS-Directed Therapy:",
    "Intrathecal therapy to prevent",
    "CNS relapse",
    "",
    "Options:",
    "• Single agent: Methotrexate",
    "• Triple agent: Methotrexate +",
    "  Cytarabine + Hydrocortisone",
    "",
    "Cranial Radiotherapy:",
    "12-18 Gy – planned per protocol",
    "to prevent CNS relapse",
], RGBColor(0x6C, 0x35, 0x82))

print("Slide 11 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 12 – DRUGS TABLE (Table 4.16)
# ═══════════════════════════════════════════════════════════
s12 = prs.slides.add_slide(blank)
slide_bg(s12)
add_header_bar(s12, "Drugs Commonly Used to Treat Acute Leukemias", "Table 4.16 – AK Tripathi")

# AML drugs box
add_rect(s12, 0.3, 1.45, 5.9, 5.85, fill_color=WHITE)
add_rect(s12, 0.3, 1.45, 5.9, 0.5, fill_color=ACCENT)
add_text(s12, "ACUTE MYELOID LEUKEMIA (AML)", 0.4, 1.47, 5.7, 0.46, size=14, bold=True, color=WHITE,
         align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE)

aml_drugs = [
    ("Daunorubicin", "Anthracycline antibiotic – DNA intercalator", "Induction (3+7 protocol)"),
    ("Cytosine Arabinoside\n(Cytarabine, Ara-C)", "Pyrimidine antimetabolite – inhibits DNA synthesis", "Induction & Consolidation"),
    ("Etoposide", "Topoisomerase II inhibitor", "Salvage therapy"),
    ("All-trans Retinoic Acid\n(ATRA)*", "Vitamin A analog – induces differentiation of promyelocytes", "AML-M3 (APML) specific"),
]

y_pos = 2.05
for drug, mech, use in aml_drugs:
    add_rect(s12, 0.35, y_pos, 5.8, 0.38, fill_color=RGBColor(0xFD, 0xED, 0xEC))
    add_text(s12, drug, 0.45, y_pos+0.02, 1.6, 0.34, size=11.5, bold=True, color=DARK_RED,
             v_anchor=MSO_ANCHOR.MIDDLE)
    add_text(s12, mech, 2.1, y_pos+0.02, 2.5, 0.34, size=10, color=DARK_GRAY,
             v_anchor=MSO_ANCHOR.MIDDLE, wrap=True)
    add_text(s12, use, 4.65, y_pos+0.02, 1.45, 0.34, size=10, color=RGBColor(0x14, 0x6E, 0xBE),
             v_anchor=MSO_ANCHOR.MIDDLE, wrap=True)
    y_pos += 0.42

add_text(s12, "*ATRA is a Vitamin A analog used specifically in treatment of AML-M3 (APML)",
         0.45, 3.8, 5.7, 0.45, size=10, color=DARK_GRAY, italic=True, wrap=True)

# ALL drugs box
add_rect(s12, 6.5, 1.45, 6.53, 5.85, fill_color=WHITE)
add_rect(s12, 6.5, 1.45, 6.53, 0.5, fill_color=RGBColor(0x14, 0x6E, 0xBE))
add_text(s12, "ACUTE LYMPHOBLASTIC LEUKEMIA (ALL)", 6.6, 1.47, 6.33, 0.46, size=14, bold=True, color=WHITE,
         align=PP_ALIGN.CENTER, v_anchor=MSO_ANCHOR.MIDDLE)

all_drugs = [
    ("Vincristine", "Vinca alkaloid – inhibits microtubule formation", "Induction backbone"),
    ("Prednisolone", "Corticosteroid – lympholytic", "Induction backbone"),
    ("Daunorubicin", "Anthracycline antibiotic", "Induction"),
    ("L-Asparaginase", "Enzyme – depletes asparagine (lymphoblasts cannot synthesize it)", "Induction (specific to ALL)"),
    ("Methotrexate", "DHFR inhibitor – antifolate", "Induction + CNS + Maintenance"),
    ("Etoposide", "Topoisomerase II inhibitor", "Intensification"),
    ("Cytosine Arabinoside", "Pyrimidine antimetabolite", "Consolidation + CNS"),
    ("6-Mercaptopurine\n(6-MP)", "Purine analog – antimetabolite", "Maintenance (long-term)"),
]

y_pos = 2.05
for drug, mech, use in all_drugs:
    add_rect(s12, 6.55, y_pos, 6.43, 0.38, fill_color=RGBColor(0xEB, 0xF5, 0xFB))
    add_text(s12, drug, 6.65, y_pos+0.02, 1.8, 0.34, size=11, bold=True, color=RGBColor(0x14, 0x6E, 0xBE),
             v_anchor=MSO_ANCHOR.MIDDLE)
    add_text(s12, mech, 8.5, y_pos+0.02, 2.9, 0.34, size=9.5, color=DARK_GRAY,
             v_anchor=MSO_ANCHOR.MIDDLE, wrap=True)
    add_text(s12, use, 11.45, y_pos+0.02, 1.45, 0.34, size=9.5, color=RGBColor(0x0D, 0x7A, 0x5F),
             v_anchor=MSO_ANCHOR.MIDDLE, wrap=True)
    y_pos += 0.42

print("Slide 12 done")

# ═══════════════════════════════════════════════════════════
# SLIDE 13 – SUMMARY / KEY POINTS
# ═══════════════════════════════════════════════════════════
s13 = prs.slides.add_slide(blank)
add_rect(s13, 0, 0, 13.333, 7.5, fill_color=DARK_BG)
add_rect(s13, 0, 0, 13.333, 1.35, fill_color=DARK_GRAY)
add_rect(s13, 0, 1.35, 13.333, 0.07, fill_color=ACCENT)

add_text(s13, "KEY TAKEAWAYS – ACUTE LEUKEMIA", 0.3, 0.1, 12.0, 0.8, size=30, bold=True, color=WHITE)
add_text(s13, "AK Tripathi's Medicine Summary", 0.3, 0.85, 12.0, 0.45, size=14, italic=True, color=GOLD)

key_points = [
    ("Definition", "Acute leukemia = >20% blasts in blood/bone marrow. AML commonest in adults (median age 70); ALL in children (80% of pediatric leukemias)."),
    ("Pathophysiology", "Cytogenetic/molecular abnormalities → uncontrolled blast proliferation → cytopenias (anemia, infections, bleeding) + bone pain."),
    ("AML Diagnosis", "Flowcytometry (investigation of choice). Auer rods in ~45% AML. Baseline CBC, BMA, karyotyping, molecular studies essential."),
    ("AML Treatment", "Induction: 3+7 (Daunorubicin + Cytarabine). Consolidation: High-dose AraC. High-risk: Allogeneic SCT. Ph+: TKIs."),
    ("ALL Features", "Weakness, fever, lymphadenopathy, hepatosplenomegaly, bone tenderness. B-ALL 80%; T-ALL 20%. Lymphoblasts 2-3x lymphocyte size."),
    ("ALL Treatment", "Protocols: MCP-841, BFM-95/2002, UKALL. Three phases: Induction → Consolidation → Maintenance (~2.5 years). CNS: IT Methotrexate ± RT 12-18 Gy."),
]

col_positions = [0.3, 6.8]
for i, (heading, content) in enumerate(key_points):
    col = i % 2
    row = i // 2
    x = col_positions[col]
    y = 1.55 + row * 1.85
    add_rect(s13, x, y, 6.1, 1.7, fill_color=RGBColor(0x2C, 0x2C, 0x54))
    add_rect(s13, x, y, 6.1, 0.42, fill_color=ACCENT if col == 0 else RGBColor(0x14, 0x6E, 0xBE))
    add_text(s13, heading, x+0.1, y+0.04, 5.9, 0.34, size=13, bold=True, color=WHITE, v_anchor=MSO_ANCHOR.MIDDLE)
    tb = s13.shapes.add_textbox(Inches(x+0.1), Inches(y+0.48), Inches(5.9), Inches(1.18))
    tf = tb.text_frame
    tf.word_wrap = True
    add_para(tf, content, size=11.5, color=RGBColor(0xCC, 0xCC, 0xEE))

add_rect(s13, 0, 7.25, 13.333, 0.25, fill_color=RGBColor(0x11, 0x11, 0x22))
add_text(s13, "Source: AK Tripathi's Medicine – Chapter 4: Hematological System",
         0.3, 7.27, 12.0, 0.21, size=10, color=RGBColor(0x88, 0x88, 0xAA), italic=True)

print("Slide 13 done")

# ═══════════════════════════════════════════════════════════
# SAVE
# ═══════════════════════════════════════════════════════════
out_path = "/tmp/workspace/acute-leukemia-ppt/Acute_Leukemia_AK_Tripathi.pptx"
prs.save(out_path)
print(f"\nPresentation saved: {out_path}")
print(f"Total slides: {len(prs.slides)}")