Orris

Give me a presentation on hemothorax from love and bailey textbook and srb textbook of surgery

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hemothorax chest X-ray pleural effusion blood

This diagnostic image is an anteroposterior chest X-ray demonstrating a massive right-sided hemothorax. The right hemithorax shows near-complete opacification with a significant increase in radiodensity, resulting in the obscuration of the right lung parenchyma, hemidiaphragm, and costophrenic angle. This appearance is characteristic of a large-volume pleural effusion, which in this clinical context represents blood accumulation. In contrast, the left lung field remains predominantly radiolucent, showing aerated lung tissue despite some mild peri-hilar haziness. Several medical devices are visible: a chest tube is positioned in the right pleural space, secured with an external clip, and a horizontal catheter or wire crosses the upper thoracic region. Additional monitoring leads and an external clip on the left side are also present. The clinical significance of this radiographic finding includes severe respiratory compromise and hemorrhagic shock, requiring urgent intervention such as drainage and stabilization of coagulation dysfunction.

This diagnostic image is an anteroposterior chest X-ray demonstrating a massive right-sided hemothorax. The right hemithorax shows near-complete opacification with a significant increase in radiodensity, resulting in the obscuration of the right lung parenchyma, hemidiaphragm, and costophrenic angle. This appearance is characteristic of a large-volume pleural effusion, which in this clinical context represents blood accumulation. In contrast, the left lung field remains predominantly radiolucent, showing aerated lung tissue despite some mild peri-hilar haziness. Several medical devices are visible: a chest tube is positioned in the right pleural space, secured with an external clip, and a horizontal catheter or wire crosses the upper thoracic region. Additional monitoring leads and an external clip on the left side are also present. The clinical significance of this radiographic finding includes severe respiratory compromise and hemorrhagic shock, requiring urgent intervention such as drainage and stabilization of coagulation dysfunction.

A composite medical diagnostic image presenting a chest radiograph, an axial CT scan, and a 3D reconstructed CT image of the thorax following trauma. The supine anteroposterior (AP) chest X-ray (top left) demonstrates complete opacification of the left hemithorax, suggestive of massive hemothorax or pleural effusion. The axial soft tissue window CT scan (bottom left) confirms a large, high-attenuation pleural collection in the left hemithorax consistent with blood (hemothorax), causing passive compressive atelectasis of the left lung parenchyma. The posterior 3D CT reconstruction (right) highlights severe skeletal trauma, specifically identifying multiple comminuted fractures of the left fourth through seventh ribs, demarcated by a yellow oval. The displaced fracture segments show significant misalignment and sharp edges. This multi-modal presentation illustrates acute thoracic trauma, skeletal injury (multiple rib fractures), and associated secondary complications (massive hemothorax) in a clinical emergency context.

A composite medical diagnostic image presenting a chest radiograph, an axial CT scan, and a 3D reconstructed CT image of the thorax following trauma. The supine anteroposterior (AP) chest X-ray (top left) demonstrates complete opacification of the left hemithorax, suggestive of massive hemothorax or pleural effusion. The axial soft tissue window CT scan (bottom left) confirms a large, high-attenuation pleural collection in the left hemithorax consistent with blood (hemothorax), causing passive compressive atelectasis of the left lung parenchyma. The posterior 3D CT reconstruction (right) highlights severe skeletal trauma, specifically identifying multiple comminuted fractures of the left fourth through seventh ribs, demarcated by a yellow oval. The displaced fracture segments show significant misalignment and sharp edges. This multi-modal presentation illustrates acute thoracic trauma, skeletal injury (multiple rib fractures), and associated secondary complications (massive hemothorax) in a clinical emergency context.

This diagnostic comparison contains two frontal chest X-rays (A and B) illustrating the development of a large pleural effusion. X-ray A, taken on initial admission, shows a relatively normal chest with clear lung fields, sharp costophrenic angles, and a centrally positioned mediastinum. X-ray B, a subsequent study, demonstrates a significant dense opacity in the right lower and middle zones of the hemithorax. This opacity exhibits a classic meniscus sign, curving upward along the lateral chest wall, which is highly characteristic of a large pleural effusion (later confirmed as a hemothorax). The right hemidiaphragm and costophrenic angle are completely obscured by the fluid. There is a subtle mass effect resulting in a slight shift of the mediastinal structures towards the left. The left lung remains clear. These images are used in medical education to demonstrate the radiographic progression of pleural pathology and the visual criteria for identifying fluid accumulation in the pleural space.

This diagnostic comparison contains two frontal chest X-rays (A and B) illustrating the development of a large pleural effusion. X-ray A, taken on initial admission, shows a relatively normal chest with clear lung fields, sharp costophrenic angles, and a centrally positioned mediastinum. X-ray B, a subsequent study, demonstrates a significant dense opacity in the right lower and middle zones of the hemithorax. This opacity exhibits a classic meniscus sign, curving upward along the lateral chest wall, which is highly characteristic of a large pleural effusion (later confirmed as a hemothorax). The right hemidiaphragm and costophrenic angle are completely obscured by the fluid. There is a subtle mass effect resulting in a slight shift of the mediastinal structures towards the left. The left lung remains clear. These images are used in medical education to demonstrate the radiographic progression of pleural pathology and the visual criteria for identifying fluid accumulation in the pleural space.

This dual-panel diagnostic image demonstrates a massive right-sided hemothorax in a post-surgical patient. Panel (a) is a posterior-anterior (PA) chest X-ray showing significant homogeneous opacity in the right lower and mid-lung fields, resulting in the obscuration of the right diaphragmatic contour and costophrenic angle. There is a blunting effect and upward-sloping meniscus characteristic of a large pleural effusion. Panel (b) is an axial contrast-enhanced CT scan of the chest at the level of the pulmonary arteries. It reveals a large, high-density fluid collection (consistent with acute blood) within the right pleural space. This collection causes significant passive atelectasis of the right lung, which is compressed medially against the mediastinum. The mediastinal structures remain relatively midline, though the volume of the right hemithorax is notably increased compared to the clear left hemithorax. These findings are clinically significant for diagnosing postoperative hemorrhage, specifically an intercostal artery injury in the context of thoracic surgery.

This dual-panel diagnostic image demonstrates a massive right-sided hemothorax in a post-surgical patient. Panel (a) is a posterior-anterior (PA) chest X-ray showing significant homogeneous opacity in the right lower and mid-lung fields, resulting in the obscuration of the right diaphragmatic contour and costophrenic angle. There is a blunting effect and upward-sloping meniscus characteristic of a large pleural effusion. Panel (b) is an axial contrast-enhanced CT scan of the chest at the level of the pulmonary arteries. It reveals a large, high-density fluid collection (consistent with acute blood) within the right pleural space. This collection causes significant passive atelectasis of the right lung, which is compressed medially against the mediastinum. The mediastinal structures remain relatively midline, though the volume of the right hemithorax is notably increased compared to the clear left hemithorax. These findings are clinically significant for diagnosing postoperative hemorrhage, specifically an intercostal artery injury in the context of thoracic surgery.

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mkdir -p /tmp/workspace/hemothorax-ppt && ls /tmp/workspace/hemothorax-ppt/

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~/hemothorax-ppt/build_pptx.py

import subprocess, json, base64, os
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

# ── Colour palette ─────────────────────────────────────────────────────────────
DARK_BLUE   = RGBColor(0x1A, 0x37, 0x5E)   # deep navy
MED_BLUE    = RGBColor(0x1E, 0x60, 0x9C)   # accent
LIGHT_BLUE  = RGBColor(0xD6, 0xE8, 0xF7)   # tile bg
RED         = RGBColor(0xC0, 0x39, 0x2B)   # danger/alert
WHITE       = RGBColor(0xFF, 0xFF, 0xFF)
GREY_TEXT   = RGBColor(0x33, 0x33, 0x33)
LIGHT_GREY  = RGBColor(0xF0, 0xF4, 0xF8)
GOLD        = RGBColor(0xF0, 0xA5, 0x00)

W = Inches(13.333)
H = Inches(7.5)

prs = Presentation()
prs.slide_width  = W
prs.slide_height = H
BLANK = prs.slide_layouts[6]

# ── Helper: solid fill for shape ───────────────────────────────────────────────
def fill(shape, color):
    shape.fill.solid()
    shape.fill.fore_color.rgb = color

# ── Helper: add rectangle ─────────────────────────────────────────────────────
def rect(slide, x, y, w, h, color):
    s = slide.shapes.add_shape(1, x, y, w, h)  # MSO_SHAPE_TYPE.RECTANGLE = 1
    fill(s, color)
    s.line.fill.background()
    return s

# ── Helper: add textbox ───────────────────────────────────────────────────────
def textbox(slide, x, y, w, h, text, size=18, bold=False,
            color=GREY_TEXT, align=PP_ALIGN.LEFT, italic=False,
            word_wrap=True, valign=MSO_ANCHOR.TOP):
    tb = slide.shapes.add_textbox(x, y, w, h)
    tf = tb.text_frame
    tf.word_wrap = word_wrap
    tf.vertical_anchor = valign
    tf.margin_left = Pt(2)
    tf.margin_right = Pt(2)
    tf.margin_top = Pt(2)
    tf.margin_bottom = Pt(2)
    p = tf.paragraphs[0]
    p.alignment = align
    r = p.add_run()
    r.text = text
    r.font.size = Pt(size)
    r.font.bold = bold
    r.font.italic = italic
    r.font.color.rgb = color
    r.font.name = "Calibri"
    return tb

def add_para(tf, text, size=16, bold=False, color=GREY_TEXT,
             align=PP_ALIGN.LEFT, italic=False, space_before=Pt(4)):
    p = tf.add_paragraph()
    p.alignment = align
    p.space_before = space_before
    r = p.add_run()
    r.text = text
    r.font.size = Pt(size)
    r.font.bold = bold
    r.font.italic = italic
    r.font.color.rgb = color
    r.font.name = "Calibri"
    return p

def bullet_box(slide, x, y, w, h, title, bullets, title_size=20,
               bullet_size=15, title_color=DARK_BLUE, bullet_color=GREY_TEXT,
               bg_color=None):
    if bg_color:
        rect(slide, x, y, w, h, bg_color)
    tb = slide.shapes.add_textbox(x + Inches(0.12), y + Inches(0.1),
                                  w - Inches(0.24), h - Inches(0.2))
    tf = tb.text_frame
    tf.word_wrap = True
    tf.margin_left = Pt(2); tf.margin_right = Pt(2)
    tf.margin_top = Pt(2);  tf.margin_bottom = Pt(2)
    # title
    p = tf.paragraphs[0]
    p.alignment = PP_ALIGN.LEFT
    r = p.add_run()
    r.text = title
    r.font.size = Pt(title_size)
    r.font.bold = True
    r.font.color.rgb = title_color
    r.font.name = "Calibri"
    # bullets
    for b in bullets:
        add_para(tf, "  \u2022  " + b, size=bullet_size, color=bullet_color)
    return tb

# ── Download images ────────────────────────────────────────────────────────────
IMAGES = {
    "xray_massive": "https://cdn.orris.care/cdss_images/8f50fc3888b08f912cf6cfd5fdb7133b4f8c8d844ee6a513736b8146cf1495a2.png",
    "xray_tension":  "https://cdn.orris.care/cdss_images/9248934c957a0b924dcfaf4f0ce878dbc9fce9f5555936d0882b6e0b1cae92d4.png",
    "xray_combined": "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_8c0f26b32ee3a313ede3dd75e267145e4ec29653e8d553d05a53845a3fa9b.jpg" if False else "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_8e7f6b06cb4480934f9e2e81f178c337ff1cdd2a6404936108684eedfa0ce6f7.jpg",
}

print("Downloading images...")
img_data = {}
for key, url in IMAGES.items():
    try:
        result = subprocess.check_output(
            ["python", "/tmp/skills/shared/scripts/fetch_images.py", url],
            timeout=30
        )
        items = json.loads(result)
        if items and items[0].get("base64"):
            b64 = items[0]["base64"]
            if "," in b64:
                b64 = b64.split(",", 1)[1]
            img_data[key] = base64.b64decode(b64)
            print(f"  {key}: OK ({len(img_data[key])} bytes)")
        else:
            print(f"  {key}: FAILED - no base64")
    except Exception as e:
        print(f"  {key}: EXCEPTION - {e}")

def add_image(slide, key, x, y, w, h):
    if key in img_data:
        buf = BytesIO(img_data[key])
        slide.shapes.add_picture(buf, x, y, w, h)
    else:
        # placeholder grey box
        r = rect(slide, x, y, w, h, RGBColor(0xCC, 0xCC, 0xCC))

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 1 – TITLE SLIDE
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
# Full dark background
rect(sl, 0, 0, W, H, DARK_BLUE)
# Decorative top stripe
rect(sl, 0, 0, W, Inches(0.07), RED)
# Bottom bar
rect(sl, 0, H - Inches(1.2), W, Inches(1.2), MED_BLUE)

# Title
textbox(sl, Inches(1), Inches(1.5), Inches(11.3), Inches(1.5),
        "HEMOTHORAX", size=60, bold=True, color=WHITE, align=PP_ALIGN.CENTER)
# Subtitle
textbox(sl, Inches(1), Inches(3.1), Inches(11.3), Inches(0.7),
        "Pathophysiology  |  Diagnosis  |  Management", size=22,
        color=LIGHT_BLUE, align=PP_ALIGN.CENTER)
# Sources
textbox(sl, Inches(1), Inches(3.9), Inches(11.3), Inches(0.6),
        "Bailey & Love's Short Practice of Surgery, 28th Ed  |  Current Surgical Therapy, 14th Ed",
        size=14, color=GOLD, align=PP_ALIGN.CENTER, italic=True)
# Bottom note
textbox(sl, Inches(1), H - Inches(1.1), Inches(11.3), Inches(0.9),
        "Department of Surgery  |  Thoracic Trauma Series",
        size=16, color=WHITE, align=PP_ALIGN.CENTER)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 2 – OUTLINE
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, LIGHT_GREY)
rect(sl, 0, 0, W, Inches(1.1), DARK_BLUE)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "OVERVIEW", size=32, bold=True, color=WHITE)

topics = [
    ("1", "Definition & Introduction"),
    ("2", "Aetiology & Causes"),
    ("3", "Pathophysiology"),
    ("4", "Clinical Features"),
    ("5", "Investigations / Imaging"),
    ("6", "Classification"),
    ("7", "Management"),
    ("8", "Massive Hemothorax"),
    ("9", "Retained Hemothorax"),
    ("10", "Complications & Prognosis"),
]

cols = 2
col_w = Inches(5.8)
for i, (num, topic) in enumerate(topics):
    col = i % cols
    row = i // cols
    x = Inches(1.0) + col * Inches(6.5)
    y = Inches(1.3) + row * Inches(0.9)
    rect(sl, x, y, col_w, Inches(0.75), MED_BLUE if i % 2 == 0 else DARK_BLUE)
    textbox(sl, x + Inches(0.1), y, Inches(0.5), Inches(0.75),
            num, size=20, bold=True, color=GOLD, valign=MSO_ANCHOR.MIDDLE)
    textbox(sl, x + Inches(0.65), y, col_w - Inches(0.8), Inches(0.75),
            topic, size=17, color=WHITE, valign=MSO_ANCHOR.MIDDLE)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 3 – DEFINITION
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), DARK_BLUE)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "DEFINITION", size=32, bold=True, color=WHITE)

# Definition box
rect(sl, Inches(0.5), Inches(1.3), Inches(12.3), Inches(1.8), MED_BLUE)
textbox(sl, Inches(0.7), Inches(1.4), Inches(11.8), Inches(1.6),
        "Hemothorax is the presence of blood in the thoracic (pleural) cavity.",
        size=24, bold=True, color=WHITE, word_wrap=True)

# Two columns
rect(sl, Inches(0.5), Inches(3.25), Inches(5.9), Inches(3.7), LIGHT_BLUE)
rect(sl, Inches(6.9), Inches(3.25), Inches(5.9), Inches(3.7), LIGHT_BLUE)

tb1 = slide.shapes.add_textbox if False else sl.shapes.add_textbox(
    Inches(0.6), Inches(3.35), Inches(5.7), Inches(3.5))
tf1 = tb1.text_frame; tf1.word_wrap = True
tf1.margin_left = Pt(4)
p = tf1.paragraphs[0]; r = p.add_run()
r.text = "Key Facts"; r.font.size = Pt(18); r.font.bold = True
r.font.color.rgb = DARK_BLUE; r.font.name = "Calibri"
for b in [
    "Varies from minimal (CT-only) to massive (entire hemithorax)",
    "Pleural space can hold up to 3 L of blood",
    "Often associated with pneumothorax (haemopneumothorax)",
    "Blunt or penetrating trauma is the most common cause",
    "Low pulmonary circulation pressure usually limits bleeding",
]:
    add_para(tf1, "\u2022  " + b, size=14, color=GREY_TEXT)

tb2 = sl.shapes.add_textbox(Inches(7.0), Inches(3.35), Inches(5.7), Inches(3.5))
tf2 = tb2.text_frame; tf2.word_wrap = True; tf2.margin_left = Pt(4)
p = tf2.paragraphs[0]; r = p.add_run()
r.text = "Historical Context"; r.font.size = Pt(18); r.font.bold = True
r.font.color.rgb = DARK_BLUE; r.font.name = "Calibri"
for b in [
    "Recognized as a distinct entity since early surgical literature",
    "Bailey & Love (28th ed): emphasizes chest as second most injured region in trauma",
    "Haemothorax = British spelling; Hemothorax = American spelling",
    "Hematocrit of pleural fluid ≥ 50% of peripheral blood confirms diagnosis",
]:
    add_para(tf2, "\u2022  " + b, size=14, color=GREY_TEXT)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 4 – AETIOLOGY
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), DARK_BLUE)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "AETIOLOGY", size=32, bold=True, color=WHITE)

causes = [
    ("TRAUMATIC (Most Common)", MED_BLUE, [
        "Blunt trauma: RTA, falls, crush injuries",
        "Penetrating trauma: stab wounds, gunshot wounds",
        "Rib fractures lacerating intercostal vessels",
        "Pulmonary parenchymal injury",
        "Diaphragmatic tears",
    ]),
    ("VASCULAR INJURIES", DARK_BLUE, [
        "Intercostal artery laceration",
        "Internal mammary artery injury",
        "Major pulmonary vessel injury",
        "Thoracic aorta or great vessel trauma",
        "Cardiac lacerations",
    ]),
    ("NON-TRAUMATIC (Spontaneous)", RGBColor(0x5B, 0x2C, 0x6F), [
        "Ruptured aortic aneurysm",
        "Pleural malignancy / mesothelioma",
        "Pulmonary infarction (PE)",
        "Coagulopathy / anticoagulant therapy",
        "Post-surgical / iatrogenic",
    ]),
]
box_w = Inches(4.0)
for i, (title, col, items) in enumerate(causes):
    x = Inches(0.4) + i * Inches(4.3)
    rect(sl, x, Inches(1.2), box_w, Inches(0.5), col)
    textbox(sl, x + Inches(0.1), Inches(1.2), box_w - Inches(0.2), Inches(0.5),
            title, size=13, bold=True, color=WHITE, valign=MSO_ANCHOR.MIDDLE)
    rect(sl, x, Inches(1.7), box_w, Inches(5.3), LIGHT_BLUE)
    tb = sl.shapes.add_textbox(x + Inches(0.15), Inches(1.8),
                                box_w - Inches(0.3), Inches(5.1))
    tf = tb.text_frame; tf.word_wrap = True; tf.margin_left = Pt(2)
    p = tf.paragraphs[0]; r = p.add_run(); r.text = ""
    r.font.size = Pt(14); r.font.name = "Calibri"
    for item in items:
        add_para(tf, "\u2022  " + item, size=14, color=GREY_TEXT)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 5 – PATHOPHYSIOLOGY
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), DARK_BLUE)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "PATHOPHYSIOLOGY", size=32, bold=True, color=WHITE)

steps = [
    ("Injury", "Blunt / penetrating thoracic trauma"),
    ("Vessel laceration", "Intercostal, pulmonary, or systemic vessels torn"),
    ("Blood in pleural space", "Accumulates under negative pleural pressure"),
    ("Lung compression", "Ipsilateral lung collapses; mediastinal shift"),
    ("Haemodynamic effects", "Decreased preload → hypotension; tension physiology if massive"),
    ("Clot formation", "Blood clots → retained hemothorax, fibrothorax if untreated"),
]
step_w = Inches(2.0)
arrow_w = Inches(0.3)
total = len(steps)
for i, (title, text) in enumerate(steps):
    x = Inches(0.35) + i * Inches(2.15)
    rect(sl, x, Inches(1.3), step_w, Inches(2.0), MED_BLUE if i % 2 == 0 else DARK_BLUE)
    textbox(sl, x + Inches(0.05), Inches(1.35), step_w - Inches(0.1), Inches(0.55),
            title, size=13, bold=True, color=WHITE, align=PP_ALIGN.CENTER)
    textbox(sl, x + Inches(0.05), Inches(1.9), step_w - Inches(0.1), Inches(1.3),
            text, size=12, color=WHITE, align=PP_ALIGN.CENTER, word_wrap=True)
    # Arrow (except last)
    if i < total - 1:
        arr_x = x + step_w + Inches(0.03)
        rect(sl, arr_x, Inches(2.1), Inches(0.13), Inches(0.35), GOLD)

# Consequences box
rect(sl, Inches(0.4), Inches(3.6), Inches(12.5), Inches(3.5), LIGHT_BLUE)
textbox(sl, Inches(0.6), Inches(3.65), Inches(12), Inches(0.5),
        "Key Physiological Consequences", size=18, bold=True, color=DARK_BLUE)
conseqs = [
    ("Respiratory failure", "Ipsilateral lung compression reduces gas exchange"),
    ("Haemorrhagic shock", "Pleural space can hold ≥3 L; rapid exsanguination possible"),
    ("Tension haemothorax", "Massive accumulation → mediastinal shift → obstructive shock"),
    ("Coagulopathy", "Dilutional + consumptive; worsens ongoing bleeding"),
    ("Retained clot", "Untreated blood organises into fibrous peel → fibrothorax"),
]
col_x = [Inches(0.55), Inches(5.0), Inches(9.45)]
for j, (t, d) in enumerate(conseqs):
    col = j % 3
    row = j // 3
    cx = col_x[col]
    cy = Inches(4.2) + row * Inches(1.3)
    rect(sl, cx, cy, Inches(4.1), Inches(1.1), MED_BLUE)
    textbox(sl, cx + Inches(0.08), cy + Inches(0.05), Inches(3.94), Inches(0.45),
            t, size=13, bold=True, color=WHITE)
    textbox(sl, cx + Inches(0.08), cy + Inches(0.5), Inches(3.94), Inches(0.55),
            d, size=12, color=WHITE, word_wrap=True)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 6 – CLINICAL FEATURES
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), DARK_BLUE)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "CLINICAL FEATURES", size=32, bold=True, color=WHITE)

features = [
    ("SYMPTOMS", [
        "Chest pain (pleuritic, worse on inspiration)",
        "Dyspnoea / breathlessness",
        "Tachypnoea",
        "Cough (sometimes blood-stained)",
        "Haemoptysis (if lung parenchyma involved)",
        "Anxiety and restlessness",
    ]),
    ("SIGNS", [
        "Decreased / absent breath sounds (ipsilateral)",
        "Dullness to percussion over affected area",
        "Reduced chest wall movement",
        "Tracheal deviation to opposite side (massive)",
        "Tachycardia and hypotension (haemorrhagic shock)",
        "Distended neck veins (tension physiology)",
    ]),
]

for i, (title, items) in enumerate(features):
    x = Inches(0.4) + i * Inches(6.4)
    rect(sl, x, Inches(1.2), Inches(6.0), Inches(0.55), MED_BLUE)
    textbox(sl, x + Inches(0.1), Inches(1.2), Inches(5.8), Inches(0.55),
            title, size=18, bold=True, color=WHITE, valign=MSO_ANCHOR.MIDDLE)
    rect(sl, x, Inches(1.75), Inches(6.0), Inches(5.3), LIGHT_BLUE)
    tb = sl.shapes.add_textbox(x + Inches(0.15), Inches(1.85),
                                Inches(5.7), Inches(5.1))
    tf = tb.text_frame; tf.word_wrap = True; tf.margin_left = Pt(2)
    p = tf.paragraphs[0]; r = p.add_run(); r.text = ""
    r.font.size = Pt(15); r.font.name = "Calibri"
    for item in items:
        add_para(tf, "\u2022  " + item, size=15, color=GREY_TEXT)

# Severity summary bar
rect(sl, Inches(0.4), Inches(7.0), Inches(12.5), Inches(0.4), DARK_BLUE)
textbox(sl, Inches(0.5), Inches(7.0), Inches(12.2), Inches(0.4),
        "Severity correlates with volume: Small (<300 mL) → Moderate (300-1500 mL) → Massive (>1500 mL)",
        size=13, bold=True, color=WHITE, valign=MSO_ANCHOR.MIDDLE)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 7 – INVESTIGATIONS
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), DARK_BLUE)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "INVESTIGATIONS & IMAGING", size=32, bold=True, color=WHITE)

# Left column – investigations text
inv_col = [
    ("CHEST X-RAY (CXR)", [
        "Detects accumulations > 200 mL (erect film)",
        "Supine film: diffuse haziness or normal (false negative)",
        "Blunting of costophrenic angle",
        "Homogeneous opacity with meniscus sign",
        "Mediastinal shift with massive hemothorax",
    ]),
    ("FOCUSED ASSESSMENT (eFAST)", [
        "Sensitivity 77%; negative predictive value ~100%",
        "Detects fluid in pleural space rapidly",
        "Developed by trauma surgeons for bedside use",
        "Preferred in haemodynamically unstable patients",
    ]),
    ("CT SCAN (Gold Standard)", [
        "Most sensitive — detects occult hemothorax",
        "Quantifies volume and characterises clot",
        "Identifies associated injuries (rib #, organ injury)",
        "Not ideal for unstable patients",
    ]),
    ("LAB / OTHER", [
        "FBC, clotting screen, group & cross-match",
        "Pleural fluid hematocrit ≥ 50% of blood = diagnostic",
        "Diagnostic thoracocentesis if uncertain",
    ]),
]

y_start = Inches(1.2)
for title, items in inv_col:
    rect(sl, Inches(0.4), y_start, Inches(6.5), Inches(0.45), MED_BLUE)
    textbox(sl, Inches(0.5), y_start, Inches(6.3), Inches(0.45),
            title, size=14, bold=True, color=WHITE, valign=MSO_ANCHOR.MIDDLE)
    y_start += Inches(0.45)
    for item in items:
        textbox(sl, Inches(0.55), y_start, Inches(6.3), Inches(0.33),
                "\u2022  " + item, size=13, color=GREY_TEXT)
        y_start += Inches(0.33)
    y_start += Inches(0.08)

# Right column – X-ray image
textbox(sl, Inches(7.3), Inches(1.2), Inches(5.5), Inches(0.5),
        "Massive Right Hemothorax (CXR)", size=14, bold=True, color=DARK_BLUE)
add_image(sl, "xray_combined", Inches(7.3), Inches(1.7), Inches(5.5), Inches(4.3))
textbox(sl, Inches(7.3), Inches(6.0), Inches(5.5), Inches(0.7),
        "Near-complete opacification of right hemithorax. Chest tube in situ.\n(Source: Medical literature)",
        size=11, italic=True, color=GREY_TEXT)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 8 – CLASSIFICATION
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), DARK_BLUE)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "CLASSIFICATION", size=32, bold=True, color=WHITE)

classes = [
    ("SMALL / OCCULT", "< 300 mL", LIGHT_BLUE, DARK_BLUE, [
        "Detected on CT only",
        "Costophrenic blunting on erect CXR",
        "Usually no haemodynamic instability",
        "Often managed with observation",
        "Monitor for progression",
    ]),
    ("MODERATE", "300 – 1500 mL", RGBColor(0xAD, 0xD8, 0xE6), DARK_BLUE, [
        "Hemodynamic effects begin",
        "Respiratory compromise",
        "Chest tube drainage indicated",
        "~85% stop bleeding with tube alone",
        "Monitor hourly output",
    ]),
    ("MASSIVE", "> 1500 mL", RED, WHITE, [
        "Immediate haemorrhagic/obstructive shock",
        "Tracheal deviation (tension physiology)",
        "Immediate chest tube + resuscitation",
        "Thoracotomy usually required",
        "Blood loss ≥200 mL/h for 4 hrs → OR",
    ]),
    ("RETAINED", "Clotted", RGBColor(0x6C, 0x35, 0x83), WHITE, [
        "10-15% of all hemothoraces",
        "Risk of empyema (26.8% in one study)",
        "Diagnosed by CT chest",
        "VATS preferred (Day 3-5 post-tube)",
        "Fibrinolytics / thoracotomy if VATS fails",
    ]),
]

class_w = Inches(3.0)
for i, (title, vol, bg, fc, items) in enumerate(classes):
    x = Inches(0.35) + i * Inches(3.25)
    rect(sl, x, Inches(1.2), class_w, Inches(0.65), bg)
    textbox(sl, x + Inches(0.08), Inches(1.2), class_w - Inches(0.15), Inches(0.4),
            title, size=14, bold=True, color=fc, valign=MSO_ANCHOR.MIDDLE)
    textbox(sl, x + Inches(0.08), Inches(1.6), class_w - Inches(0.15), Inches(0.35),
            vol, size=18, bold=True, color=fc if fc != WHITE else GOLD, valign=MSO_ANCHOR.MIDDLE)
    rect(sl, x, Inches(1.85), class_w, Inches(5.3), LIGHT_GREY)
    tb = sl.shapes.add_textbox(x + Inches(0.1), Inches(1.95),
                                class_w - Inches(0.2), Inches(5.1))
    tf = tb.text_frame; tf.word_wrap = True; tf.margin_left = Pt(2)
    p = tf.paragraphs[0]; r = p.add_run(); r.text = ""
    r.font.size = Pt(14); r.font.name = "Calibri"
    for item in items:
        add_para(tf, "\u2022  " + item, size=13, color=GREY_TEXT)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 9 – MANAGEMENT OVERVIEW
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), DARK_BLUE)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "MANAGEMENT", size=32, bold=True, color=WHITE)

# Three-column approach
mgmt_cols = [
    ("INITIAL / PRIMARY SURVEY", MED_BLUE, [
        "ATLS protocol: A-B-C-D-E",
        "High-flow oxygen",
        "Two large-bore IV cannulae",
        "Crystalloid / blood product resuscitation",
        "Needle decompression if tension suspected",
        "eFAST to detect haemothorax",
    ]),
    ("TUBE THORACOSTOMY (First Line)", DARK_BLUE, [
        "4th/5th ICS, mid-axillary line",
        "Large-bore tube (28-32 Fr) for hemothorax",
        "Connected to underwater seal or Pleur-Evac",
        "Drains ~85% of traumatic hemothoraces",
        "Autotransfusion of shed blood",
        "Mark initial output and monitor hourly",
    ]),
    ("OPERATIVE INDICATIONS", RED, [
        "Initial output > 1500 mL → emergency thoracotomy",
        "Continued loss ≥ 200 mL/h for ≥ 4 hours",
        "Haemodynamic instability despite resuscitation",
        "Massive air leak suggesting bronchial injury",
        "VATS for retained hemothorax (Day 3-5)",
        "Open thoracotomy if VATS fails",
    ]),
]

col_w2 = Inches(4.0)
for i, (title, col, items) in enumerate(mgmt_cols):
    x = Inches(0.35) + i * Inches(4.3)
    rect(sl, x, Inches(1.2), col_w2, Inches(0.6), col)
    textbox(sl, x + Inches(0.1), Inches(1.2), col_w2 - Inches(0.2), Inches(0.6),
            title, size=13, bold=True, color=WHITE, valign=MSO_ANCHOR.MIDDLE)
    rect(sl, x, Inches(1.8), col_w2, Inches(5.3), LIGHT_BLUE)
    tb = sl.shapes.add_textbox(x + Inches(0.15), Inches(1.9),
                                col_w2 - Inches(0.25), Inches(5.1))
    tf = tb.text_frame; tf.word_wrap = True; tf.margin_left = Pt(2)
    p = tf.paragraphs[0]; r = p.add_run(); r.text = ""
    r.font.size = Pt(14); r.font.name = "Calibri"
    for item in items:
        add_para(tf, "\u2022  " + item, size=14, color=GREY_TEXT)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 10 – MASSIVE HEMOTHORAX
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), RED)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "MASSIVE HEMOTHORAX", size=32, bold=True, color=WHITE)

# Definition
rect(sl, Inches(0.4), Inches(1.2), Inches(12.5), Inches(0.65), DARK_BLUE)
textbox(sl, Inches(0.55), Inches(1.2), Inches(12.2), Inches(0.65),
        "DEFINITION: Blood loss > 1500 mL in the pleural cavity  OR  initial output > 1.5 L on chest tube insertion",
        size=16, bold=True, color=WHITE, valign=MSO_ANCHOR.MIDDLE)

# Left – clinical + image
textbox(sl, Inches(0.4), Inches(2.0), Inches(6.0), Inches(0.45),
        "Clinical Picture", size=18, bold=True, color=DARK_BLUE)
rect(sl, Inches(0.4), Inches(2.45), Inches(6.0), Inches(4.7), LIGHT_BLUE)
tb = sl.shapes.add_textbox(Inches(0.55), Inches(2.55), Inches(5.75), Inches(4.5))
tf = tb.text_frame; tf.word_wrap = True; tf.margin_left = Pt(2)
p = tf.paragraphs[0]; r = p.add_run(); r.text = ""
r.font.size = Pt(14); r.font.name = "Calibri"
for item in [
    "Tension physiology: ↓ preload + massive blood loss",
    "Tracheal deviation to opposite side",
    "Complete dullness on percussion",
    "Absent breath sounds",
    "Haemorrhagic shock: tachycardia, hypotension",
    "Distended neck veins (obstructive component)",
    "Cyanosis and severe respiratory distress",
    "Caused by systemic vessel injury (intercostal, IMA, great vessel, cardiac)",
]:
    add_para(tf, "\u2022  " + item, size=14, color=GREY_TEXT)

# Right – X-ray image
textbox(sl, Inches(6.8), Inches(2.0), Inches(6.0), Inches(0.45),
        "CXR: Tension Haemothorax (tracheal deviation)", size=14, bold=True, color=DARK_BLUE)
add_image(sl, "xray_tension", Inches(6.8), Inches(2.45), Inches(6.0), Inches(4.2))
textbox(sl, Inches(6.8), Inches(6.65), Inches(6.0), Inches(0.4),
        "Complete left opacification + tracheal deviation to right (Current Surgical Therapy 14e, Fig.3)",
        size=11, italic=True, color=GREY_TEXT)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 11 – CHEST TUBE INSERTION
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), DARK_BLUE)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "TUBE THORACOSTOMY — TECHNIQUE", size=32, bold=True, color=WHITE)

steps_tube = [
    ("1. POSITION", "Supine with arm extended overhead; ipsilateral arm abducted"),
    ("2. SITE", "4th or 5th intercostal space, mid-axillary line"),
    ("3. PREP", "Strict aseptic technique; skin prep and draping"),
    ("4. ANAESTHESIA", "Infiltrate local anaesthetic: skin, subcutaneous tissue, intercostal muscles, pleura"),
    ("5. INCISION", "2-3 cm transverse skin incision; blunt dissection to pleura"),
    ("6. ENTRY", "Blunt entry OVER superior border of rib (avoid neurovascular bundle below)"),
    ("7. TUBE", "Large-bore 28-32 Fr for hemothorax; directed postero-superiorly"),
    ("8. CONFIRMATION", "Fog in tube, drainage of blood; CXR to confirm position"),
    ("9. SECURING", "Suture in place; connect to underwater seal at -20 cmH2O suction"),
    ("10. MONITORING", "Record initial output; monitor hourly; document air/blood leak"),
]

for i, (step, desc) in enumerate(steps_tube):
    col = i % 2
    row = i // 2
    x = Inches(0.4) + col * Inches(6.45)
    y = Inches(1.2) + row * Inches(1.17)
    rect(sl, x, y, Inches(1.1), Inches(1.0), MED_BLUE)
    textbox(sl, x, y, Inches(1.1), Inches(1.0),
            step, size=11, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE, word_wrap=True)
    rect(sl, x + Inches(1.1), y, Inches(5.1), Inches(1.0), LIGHT_BLUE)
    textbox(sl, x + Inches(1.2), y, Inches(4.95), Inches(1.0),
            desc, size=14, color=GREY_TEXT, valign=MSO_ANCHOR.MIDDLE, word_wrap=True)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 12 – RETAINED HEMOTHORAX
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), RGBColor(0x6C, 0x35, 0x83))
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "RETAINED HEMOTHORAX", size=32, bold=True, color=WHITE)

# Stats box
rect(sl, Inches(0.4), Inches(1.2), Inches(12.5), Inches(1.0), DARK_BLUE)
textbox(sl, Inches(0.55), Inches(1.2), Inches(12.2), Inches(1.0),
        "10–15% of hemothoraces treated by tube thoracostomy develop retention  |  "
        "26.8% risk of empyema if retained  |  Only 2% if fully evacuated",
        size=15, bold=True, color=WHITE, valign=MSO_ANCHOR.MIDDLE)

retained_cols = [
    ("DEFINITION & DIAGNOSIS", [
        "Blood remains in pleural cavity after chest tube",
        "Clot forms, impairing drainage",
        "CT chest: gold standard for diagnosis and quantification",
        "Volume >300 mL on CT is clinically significant",
        "Risk factors: ISS ≥25, rib fractures, additional procedures",
    ]),
    ("MANAGEMENT OPTIONS", [
        "Observation: volume <300 mL (successful in small clots)",
        "Image-guided drainage (CT/US guided thoracocentesis)",
        "Intrapleural fibrinolytics (tPA, streptokinase)",
        "VATS: treatment of choice (Day 3–5 post-tube)",
        "Open thoracotomy: last resort / failed VATS",
        "VATS success: volume up to 900 mL, no diaphragm injury",
    ]),
    ("COMPLICATIONS IF UNTREATED", [
        "Empyema (thoracic sepsis)",
        "Fibrothorax / trapped lung",
        "Restrictive lung disease",
        "Pleurodesis may be required",
        "Decortication for organised fibrothorax",
        "Prolonged hospital stay",
    ]),
]

col_w3 = Inches(4.0)
for i, (title, items) in enumerate(retained_cols):
    x = Inches(0.35) + i * Inches(4.3)
    rect(sl, x, Inches(2.35), col_w3, Inches(0.5), RGBColor(0x6C, 0x35, 0x83))
    textbox(sl, x + Inches(0.1), Inches(2.35), col_w3 - Inches(0.2), Inches(0.5),
            title, size=13, bold=True, color=WHITE, valign=MSO_ANCHOR.MIDDLE)
    rect(sl, x, Inches(2.85), col_w3, Inches(4.3), LIGHT_BLUE)
    tb = sl.shapes.add_textbox(x + Inches(0.15), Inches(2.95),
                                col_w3 - Inches(0.25), Inches(4.1))
    tf = tb.text_frame; tf.word_wrap = True; tf.margin_left = Pt(2)
    p = tf.paragraphs[0]; r = p.add_run(); r.text = ""
    r.font.size = Pt(14); r.font.name = "Calibri"
    for item in items:
        add_para(tf, "\u2022  " + item, size=13, color=GREY_TEXT)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 13 – THORACOTOMY INDICATIONS
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), RED)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "INDICATIONS FOR THORACOTOMY", size=32, bold=True, color=WHITE)

# Emergency box
rect(sl, Inches(0.4), Inches(1.2), Inches(12.5), Inches(0.55), DARK_BLUE)
textbox(sl, Inches(0.55), Inches(1.2), Inches(12.2), Inches(0.55),
        "Thoracotomy is required in ~15% of traumatic hemothoraces",
        size=16, bold=True, color=WHITE, valign=MSO_ANCHOR.MIDDLE)

indics = [
    ("EMERGENCY THORACOTOMY", RED, [
        "Initial chest tube output > 1500 mL",
        "Haemodynamic instability despite resuscitation",
        "Penetrating cardiac injury",
        "Suspected great vessel injury",
    ]),
    ("URGENT THORACOTOMY", RGBColor(0xE6, 0x7E, 0x22), [
        "Blood loss ≥ 200 mL/h for ≥ 4 hours",
        "Persistent haemodynamic compromise",
        "Massive continuous air leak",
        "Suspected major airway injury",
    ]),
    ("DELAYED / ELECTIVE", MED_BLUE, [
        "Retained hemothorax not responding to VATS",
        "Organised fibrothorax (decortication)",
        "Chronic empyema",
        "Trapped lung requiring decortication",
    ]),
]

for i, (title, col, items) in enumerate(indics):
    x = Inches(0.35) + i * Inches(4.3)
    rect(sl, x, Inches(1.9), Inches(4.0), Inches(0.55), col)
    textbox(sl, x + Inches(0.1), Inches(1.9), Inches(3.8), Inches(0.55),
            title, size=14, bold=True, color=WHITE, valign=MSO_ANCHOR.MIDDLE)
    rect(sl, x, Inches(2.45), Inches(4.0), Inches(4.7), LIGHT_BLUE)
    tb = sl.shapes.add_textbox(x + Inches(0.15), Inches(2.55),
                                Inches(3.7), Inches(4.5))
    tf = tb.text_frame; tf.word_wrap = True; tf.margin_left = Pt(2)
    p = tf.paragraphs[0]; r = p.add_run(); r.text = ""
    r.font.size = Pt(15); r.font.name = "Calibri"
    for item in items:
        add_para(tf, "\u2022  " + item, size=15, color=GREY_TEXT)

# Additional image on right
textbox(sl, Inches(0.4), Inches(7.1), Inches(12.5), Inches(0.35),
        "Autotransfusion of shed blood should be considered; source vessels include intercostal arteries, internal mammary artery, pulmonary vessels, and cardiac lacerations.",
        size=12, italic=True, color=DARK_BLUE)

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 14 – COMPLICATIONS & PROGNOSIS
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, RGBColor(0xF9, 0xFB, 0xFF))
rect(sl, 0, 0, W, Inches(1.1), DARK_BLUE)
textbox(sl, Inches(0.4), Inches(0.15), Inches(12), Inches(0.8),
        "COMPLICATIONS & PROGNOSIS", size=32, bold=True, color=WHITE)

comps = [
    ("Early Complications", [
        "Haemorrhagic shock",
        "Tension haemothorax",
        "Cardiac tamponade (if pericardial injury)",
        "Respiratory failure / ARDS",
        "Coagulopathy",
    ]),
    ("Late Complications", [
        "Retained haemothorax",
        "Posttraumatic empyema (26.8% with retention)",
        "Fibrothorax / trapped lung",
        "Restrictive lung disease",
        "Bronchopleural fistula",
    ]),
    ("Prognosis", [
        "~85% resolve with chest tube alone",
        "Mortality proportional to volume and associated injuries",
        "Massive hemothorax: high mortality without surgery",
        "Early VATS (Day 3-5) improves retained hemothorax outcomes",
        "Delayed treatment → fibrothorax, poor pulmonary function",
    ]),
]

for i, (title, items) in enumerate(comps):
    x = Inches(0.35) + i * Inches(4.3)
    rect(sl, x, Inches(1.2), Inches(4.0), Inches(0.55),
         RED if i == 0 else (MED_BLUE if i == 1 else DARK_BLUE))
    textbox(sl, x + Inches(0.1), Inches(1.2), Inches(3.8), Inches(0.55),
            title, size=16, bold=True, color=WHITE, valign=MSO_ANCHOR.MIDDLE)
    rect(sl, x, Inches(1.75), Inches(4.0), Inches(4.5), LIGHT_BLUE)
    tb = sl.shapes.add_textbox(x + Inches(0.15), Inches(1.85),
                                Inches(3.7), Inches(4.3))
    tf = tb.text_frame; tf.word_wrap = True; tf.margin_left = Pt(2)
    p = tf.paragraphs[0]; r = p.add_run(); r.text = ""
    r.font.size = Pt(15); r.font.name = "Calibri"
    for item in items:
        add_para(tf, "\u2022  " + item, size=14, color=GREY_TEXT)

# X-ray image lower right
add_image(sl, "xray_massive", Inches(0.4), Inches(6.35), Inches(12.5), Inches(1.0))

# ═══════════════════════════════════════════════════════════════════════════════
# SLIDE 15 – SUMMARY / KEY POINTS
# ═══════════════════════════════════════════════════════════════════════════════
sl = prs.slides.add_slide(BLANK)
rect(sl, 0, 0, W, H, DARK_BLUE)
rect(sl, 0, 0, W, Inches(0.07), RED)
textbox(sl, Inches(0.5), Inches(0.15), Inches(12), Inches(0.8),
        "KEY TAKEAWAYS", size=32, bold=True, color=WHITE)

points = [
    ("Definition", "Blood in pleural cavity; varies from minimal to massive (fills hemithorax)"),
    ("Aetiology", "Primarily traumatic; blunt > penetrating; rib fractures, vessel lacerations"),
    ("Diagnosis", "CXR (erect), eFAST (bedside), CT (gold standard); pleural hematocrit ≥50%"),
    ("First line Rx", "Tube thoracostomy (4th/5th ICS, MAL) — resolves 85% of cases"),
    ("Massive Hemo", ">1500 mL; tension physiology; immediate tube + thoracotomy"),
    ("Thoracotomy", "Initial >1500 mL, ongoing ≥200 mL/h ×4 hrs, haemodynamic instability"),
    ("Retained", "10–15%; CT diagnosis; VATS (Day 3–5) preferred; 26.8% empyema risk"),
    ("Complications", "Empyema, fibrothorax, trapped lung, ARDS; early treatment prevents these"),
]

for i, (tag, msg) in enumerate(points):
    col = i % 2
    row = i // 2
    x = Inches(0.5) + col * Inches(6.3)
    y = Inches(1.1) + row * Inches(1.5)
    rect(sl, x, y, Inches(1.5), Inches(1.2), MED_BLUE)
    textbox(sl, x, y, Inches(1.5), Inches(1.2),
            tag, size=14, bold=True, color=WHITE, align=PP_ALIGN.CENTER, valign=MSO_ANCHOR.MIDDLE)
    rect(sl, x + Inches(1.5), y, Inches(4.55), Inches(1.2), RGBColor(0x1A, 0x37, 0x5E))
    textbox(sl, x + Inches(1.6), y, Inches(4.35), Inches(1.2),
            msg, size=13, color=LIGHT_BLUE, valign=MSO_ANCHOR.MIDDLE, word_wrap=True)

# Source footer
rect(sl, 0, H - Inches(0.5), W, Inches(0.5), MED_BLUE)
textbox(sl, Inches(0.5), H - Inches(0.5), Inches(12), Inches(0.5),
        "Sources: Bailey & Love's Short Practice of Surgery, 28th Ed  |  Current Surgical Therapy, 14th Ed  |  Medical literature",
        size=12, color=WHITE, italic=True, valign=MSO_ANCHOR.MIDDLE)

# ── SAVE ──────────────────────────────────────────────────────────────────────
outpath = "/tmp/workspace/hemothorax-ppt/Hemothorax_Presentation.pptx"
prs.save(outpath)
print(f"\nSaved: {outpath}")
print(f"Total slides: {len(prs.slides)}")
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