$attachment$

+2 more

MAKE IT INTO A PPT FOR A MICROTEAACHING IN DETAILED EXPLANATION REGARDING THE ABOVE ATTACHED PHOTO AND ALSO ADD THE CASE MENTIONED HERE IN THE 2ND SLIDE AND ADD AIM AND OBJECTIVE IN THE 1ST SLIDE DETAILS OF THE PROCEDURE IN THE 3RD 4TH SLIDE AND SOME MORE CLINICAL IMPORTANCE AND AT LAST ADD THE QUERY IN THE MICROTEAACHING FORMAT

I can see the images contain content about Dynamic Auscultation as a microteaching topic - specifically differentiating HOCM from Aortic Stenosis using bedside maneuvers. Let me analyse all images and build the PPT simultaneously.

analyse_media

Reading File

Now I'll create the comprehensive microteaching PPT:

Running Command

mkdir -p /tmp/workspace/dynamic-auscultation-ppt && ls /tmp/workspace/

Writing File

~/dynamic-auscultation-ppt/create_ppt.py

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
import copy
from lxml import etree

prs = Presentation()
prs.slide_width = Inches(13.333)
prs.slide_height = Inches(7.5)

# ─── Color Palette ────────────────────────────────────────────────
NAVY       = RGBColor(0x0A, 0x2A, 0x5E)   # dark navy blue
CRIMSON    = RGBColor(0xC0, 0x20, 0x2F)   # medical red
GOLD       = RGBColor(0xF0, 0xA5, 0x00)   # accent gold
WHITE      = RGBColor(0xFF, 0xFF, 0xFF)
LIGHT_BLUE = RGBColor(0xE8, 0xF1, 0xFB)
DARK_GRAY  = RGBColor(0x2C, 0x2C, 0x2C)
MID_GRAY   = RGBColor(0x55, 0x55, 0x55)
TEAL       = RGBColor(0x00, 0x7B, 0x83)
GREEN      = RGBColor(0x1A, 0x7A, 0x1A)
ORANGE     = RGBColor(0xE0, 0x60, 0x00)
LIGHT_NAVY = RGBColor(0x1A, 0x3F, 0x8A)

blank_layout = prs.slide_layouts[6]

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

def add_textbox(slide, text, x, y, w, h, font_name="Calibri", size=14, bold=False,
                color=DARK_GRAY, align=PP_ALIGN.LEFT, italic=False, wrap=True):
    tb = slide.shapes.add_textbox(Inches(x), Inches(y), Inches(w), Inches(h))
    tf = tb.text_frame
    tf.word_wrap = wrap
    tf.margin_left = Inches(0.05)
    tf.margin_right = Inches(0.05)
    tf.margin_top = Inches(0.02)
    tf.margin_bottom = Inches(0.02)
    p = tf.paragraphs[0]
    p.alignment = align
    run = p.add_run()
    run.text = text
    run.font.name = font_name
    run.font.size = Pt(size)
    run.font.bold = bold
    run.font.italic = italic
    run.font.color.rgb = color
    return tf

def add_para(tf, text, size=13, bold=False, color=DARK_GRAY, align=PP_ALIGN.LEFT,
             italic=False, space_before=6, indent=0):
    p = tf.add_paragraph()
    p.alignment = align
    p.space_before = Pt(space_before)
    if indent:
        p.level = indent
    run = p.add_run()
    run.text = text
    run.font.name = "Calibri"
    run.font.size = Pt(size)
    run.font.bold = bold
    run.font.italic = italic
    run.font.color.rgb = color
    return p

def add_bullet_para(tf, text, size=12.5, color=DARK_GRAY, bold_prefix=None, rest_text=None):
    """Add a bullet point; optionally bold_prefix + rest_text for bold+normal in one line."""
    p = tf.add_paragraph()
    p.alignment = PP_ALIGN.LEFT
    p.space_before = Pt(4)
    # bullet symbol
    run_bullet = p.add_run()
    run_bullet.text = "  \u2022  "
    run_bullet.font.size = Pt(size)
    run_bullet.font.color.rgb = CRIMSON
    run_bullet.font.bold = True
    run_bullet.font.name = "Calibri"
    if bold_prefix:
        rb = p.add_run()
        rb.text = bold_prefix
        rb.font.size = Pt(size)
        rb.font.bold = True
        rb.font.color.rgb = NAVY
        rb.font.name = "Calibri"
        rn = p.add_run()
        rn.text = rest_text if rest_text else ""
        rn.font.size = Pt(size)
        rn.font.color.rgb = color
        rn.font.name = "Calibri"
    else:
        run = p.add_run()
        run.text = text
        run.font.size = Pt(size)
        run.font.color.rgb = color
        run.font.bold = False
        run.font.name = "Calibri"


# ══════════════════════════════════════════════════════════════════
# SLIDE 1 — TITLE / AIM & OBJECTIVES
# ══════════════════════════════════════════════════════════════════
slide1 = prs.slides.add_slide(blank_layout)

# Full navy background
add_rect(slide1, 0, 0, 13.333, 7.5, NAVY)

# Red accent bar left
add_rect(slide1, 0, 0, 0.4, 7.5, CRIMSON)

# Gold divider line
add_rect(slide1, 0.4, 3.05, 12.933, 0.06, GOLD)

# Top label
tf_label = add_textbox(slide1, "MICROTEACHING PRESENTATION", 0.6, 0.2, 12, 0.45,
                       size=11, bold=True, color=GOLD, align=PP_ALIGN.LEFT)

# Heart-beat icon simulation (text)
add_textbox(slide1, "♥", 11.5, 0.15, 1.5, 0.6, size=22, color=CRIMSON, align=PP_ALIGN.RIGHT)

# Main Title
tf_title = add_textbox(slide1, "Dynamic Auscultation", 0.6, 0.75, 12.5, 1.05,
                       font_name="Calibri", size=46, bold=True, color=WHITE, align=PP_ALIGN.LEFT)

# Subtitle
tf_sub = add_textbox(slide1, "The Physiological Stress Test | HOCM vs. Aortic Stenosis",
                     0.6, 1.85, 12.5, 0.6,
                     font_name="Calibri", size=20, bold=False, color=GOLD, align=PP_ALIGN.LEFT)

# Tagline
add_textbox(slide1, "Differentiating life-threatening murmurs at the bedside — without an Echo",
            0.6, 2.5, 12.5, 0.5,
            font_name="Calibri", size=14, bold=False, color=RGBColor(0xB0,0xC8,0xFF), align=PP_ALIGN.LEFT,
            italic=True)

# ── AIM box (left panel) ──────────────────────────────────────────
add_rect(slide1, 0.55, 3.25, 5.8, 3.8, RGBColor(0x0D, 0x35, 0x70))

tf_aim = add_textbox(slide1, "AIM", 0.75, 3.3, 5.4, 0.4,
                     size=15, bold=True, color=GOLD, align=PP_ALIGN.LEFT)
add_para(tf_aim, "To teach PG trainees how bedside dynamic maneuvers change the intensity "
         "of cardiac murmurs, enabling accurate clinical differentiation of Hypertrophic "
         "Obstructive Cardiomyopathy (HOCM) from Aortic Stenosis (AS) — without echocardiography.",
         size=12.5, color=WHITE)

# ── OBJECTIVES box (right panel) ──────────────────────────────────
add_rect(slide1, 6.6, 3.25, 6.4, 3.8, RGBColor(0x0D, 0x35, 0x70))

tf_obj = add_textbox(slide1, "LEARNING OBJECTIVES", 6.8, 3.3, 6.0, 0.4,
                     size=15, bold=True, color=GOLD, align=PP_ALIGN.LEFT)
for obj in [
    "Explain the physiological basis of preload-dependent murmur changes",
    "Correctly perform & interpret the Valsalva maneuver and squatting/leg-raise",
    "Construct a 2×2 matrix contrasting HOCM vs. AS responses",
    "Identify Wide Fixed Splitting vs. Paradoxical Splitting of S₂",
    "Apply carotid-precordial synchronization to time murmurs in tachycardia",
    "Answer OSCE/viva-style questions on dynamic auscultation with confidence",
]:
    add_bullet_para(tf_obj, obj, size=12, color=WHITE)

# Bottom footer
add_rect(slide1, 0, 7.1, 13.333, 0.4, RGBColor(0x06, 0x19, 0x40))
add_textbox(slide1, "7-Minute High-Impact Microteaching  |  Cardiovascular Examination  |  PG Medicine",
            0.4, 7.12, 12.5, 0.3, size=10.5, color=RGBColor(0xA0,0xB8,0xE0), align=PP_ALIGN.CENTER)


# ══════════════════════════════════════════════════════════════════
# SLIDE 2 — CLINICAL CASE (PG HOOK)
# ══════════════════════════════════════════════════════════════════
slide2 = prs.slides.add_slide(blank_layout)

# Background
add_rect(slide2, 0, 0, 13.333, 7.5, RGBColor(0xF4, 0xF7, 0xFF))

# Header bar
add_rect(slide2, 0, 0, 13.333, 1.0, NAVY)
add_rect(slide2, 0, 0, 0.5, 1.0, CRIMSON)
add_textbox(slide2, "SLIDE 2  |  CLINICAL CASE", 0.65, 0.05, 6, 0.35,
            size=11, bold=True, color=GOLD)
add_textbox(slide2, "Minute 0–1: The PG Hook (Problem-Based)", 0.65, 0.45, 10, 0.45,
            size=16, bold=True, color=WHITE)
add_textbox(slide2, "⏱", 12.0, 0.1, 1.0, 0.8, size=28, color=GOLD, align=PP_ALIGN.RIGHT)

# Case scenario header
add_rect(slide2, 0.5, 1.15, 12.333, 0.48, CRIMSON)
add_textbox(slide2, "🚨  RAPID-FIRE CASE SCENARIO — YOU ARE IN THE ICCU", 0.65, 1.2, 12, 0.38,
            size=14, bold=True, color=WHITE)

# Case text box
add_rect(slide2, 0.5, 1.7, 12.333, 1.9, RGBColor(0xFF, 0xF0, 0xF0))
tf_case = add_textbox(slide2,
    '"You are in the ICCU. A 22-year-old male athlete collapsed and syncoped on the field.',
    0.7, 1.78, 11.9, 0.4, size=14.5, bold=False, color=DARK_GRAY, italic=True)
add_para(tf_case,
    'On examination: Heart rate 98 bpm, BP 110/70 mmHg. You auscultate a harsh, grade 3/6 '
    'crescendo-decrescendo systolic murmur, heard best at the left sternal border.',
    size=14.5, italic=True, color=DARK_GRAY)
add_para(tf_case,
    'ECG shows LVH with repolarization changes. Echo is NOT immediately available.',
    size=14.5, italic=True, color=DARK_GRAY)
add_para(tf_case, '', size=6)
add_para(tf_case,
    'Is this benign aortic sclerosis — or a life-threatening HOCM? Today, we will '
    'differentiate them in 2 minutes without an Echo."',
    size=15, bold=True, italic=True, color=CRIMSON)

# ── Two question boxes ────────────────────────────────────────────
add_rect(slide2, 0.5, 3.72, 5.9, 1.4, NAVY)
tf_q1 = add_textbox(slide2, "❓ THE CLINICAL DILEMMA", 0.7, 3.78, 5.5, 0.35,
                    size=13, bold=True, color=GOLD)
add_para(tf_q1, "Both HOCM and Aortic Stenosis produce a SYSTOLIC murmur.", size=12.5, color=WHITE)
add_para(tf_q1, "Both can cause syncope, dyspnea & angina.", size=12.5, color=WHITE)
add_para(tf_q1, "They SOUND similar on basic auscultation.", size=12.5, color=WHITE)

add_rect(slide2, 6.7, 3.72, 6.13, 1.4, TEAL)
tf_q2 = add_textbox(slide2, "💡 THE KEY DIFFERENTIATOR", 6.9, 3.78, 5.8, 0.35,
                    size=13, bold=True, color=GOLD)
add_para(tf_q2, "Dynamic maneuvers change PRELOAD.", size=12.5, color=WHITE)
add_para(tf_q2, "Preload change → Opposite murmur responses in HOCM vs. AS.", size=12.5, color=WHITE)
add_para(tf_q2, "Valsalva specificity for HOCM: >90% (AHA guidelines).", size=12.5, color=WHITE)

# ── Why it matters ────────────────────────────────────────────────
add_rect(slide2, 0.5, 5.28, 12.333, 1.05, RGBColor(0xFF, 0xF7, 0xE0))
tf_why = add_textbox(slide2, "WHY THIS MATTERS", 0.7, 5.32, 5, 0.35,
                     size=13, bold=True, color=CRIMSON)
add_para(tf_why, "HOCM is the #1 cause of sudden cardiac death in young athletes. "
         "Misdiagnosis as innocent murmur or AS can be fatal. "
         "β-blockers (used in HOCM) worsen symptoms in severe AS. "
         "Correct bedside diagnosis guides IMMEDIATE management decisions.", size=12.5, color=DARK_GRAY)

# Footer
add_rect(slide2, 0, 6.45, 13.333, 0.05, GOLD)
add_rect(slide2, 0, 7.1, 13.333, 0.4, NAVY)
add_textbox(slide2, "Dynamic Auscultation  |  Microteaching  |  Slide 2 of 8",
            0.4, 7.13, 12.5, 0.3, size=10.5, color=RGBColor(0xA0,0xB8,0xE0), align=PP_ALIGN.CENTER)


# ══════════════════════════════════════════════════════════════════
# SLIDE 3 — PROCEDURE: PHYSIOLOGY & MANEUVERS (Part 1)
# ══════════════════════════════════════════════════════════════════
slide3 = prs.slides.add_slide(blank_layout)
add_rect(slide3, 0, 0, 13.333, 7.5, RGBColor(0xF4, 0xF7, 0xFF))
add_rect(slide3, 0, 0, 13.333, 1.0, NAVY)
add_rect(slide3, 0, 0, 0.5, 1.0, CRIMSON)
add_textbox(slide3, "SLIDE 3  |  PROCEDURE & PHYSIOLOGY", 0.65, 0.05, 8, 0.35,
            size=11, bold=True, color=GOLD)
add_textbox(slide3, "Minute 1–3: The Concept Matrix — How Preload Flips the Murmur",
            0.65, 0.45, 12, 0.45, size=16, bold=True, color=WHITE)

# ── Physiology panel left ─────────────────────────────────────────
add_rect(slide3, 0.5, 1.1, 4.0, 5.95, NAVY)
tf_phys = add_textbox(slide3, "PHYSIOLOGICAL BASIS", 0.65, 1.15, 3.7, 0.4,
                      size=13, bold=True, color=GOLD)
add_para(tf_phys, "HOCM: Dynamic LVOT Obstruction", size=12.5, bold=True, color=WHITE)
add_para(tf_phys,
    "SAM (Systolic Anterior Motion) of mitral leaflet + asymmetric septal hypertrophy "
    "cause dynamic obstruction of LVOT.", size=11.5, color=RGBColor(0xC8,0xDC,0xFF))
add_para(tf_phys, "", size=4)
add_para(tf_phys, "⬇ Preload → LV cavity shrinks → LVOT narrower → Obstruction WORSENS → Murmur LOUDER",
    size=12, bold=True, color=GOLD)
add_para(tf_phys, "", size=4)
add_para(tf_phys, "⬆ Preload → LV cavity enlarges → LVOT wider → Obstruction LESSENS → Murmur SOFTER",
    size=12, bold=True, color=RGBColor(0x90, 0xFF, 0x90))
add_para(tf_phys, "", size=6)
add_para(tf_phys, "AORTIC STENOSIS: Fixed Valve Obstruction", size=12.5, bold=True, color=WHITE)
add_para(tf_phys,
    "Calcified / congenitally bicuspid aortic valve. Obstruction is at the valve level — "
    "FIXED regardless of LV size.", size=11.5, color=RGBColor(0xC8,0xDC,0xFF))
add_para(tf_phys, "", size=4)
add_para(tf_phys,
    "⬆ Preload → more blood flows across the stenosed valve → Murmur LOUDER",
    size=12, bold=True, color=RGBColor(0x90, 0xFF, 0x90))
add_para(tf_phys, "", size=4)
add_para(tf_phys,
    "⬇ Preload → less flow across valve → Murmur SOFTER",
    size=12, bold=True, color=GOLD)

# ── 2×2 Matrix center/right ───────────────────────────────────────
add_rect(slide3, 4.8, 1.1, 8.1, 0.45, CRIMSON)
add_textbox(slide3, "THE 2×2 DIAGNOSTIC MATRIX", 4.95, 1.15, 7.9, 0.35,
            size=14, bold=True, color=WHITE, align=PP_ALIGN.CENTER)

# Matrix headers
add_rect(slide3, 4.8, 1.6, 3.9, 0.42, LIGHT_NAVY)
add_textbox(slide3, "MANEUVER / EFFECT", 4.85, 1.62, 3.8, 0.38,
            size=12, bold=True, color=WHITE, align=PP_ALIGN.CENTER)
add_rect(slide3, 8.75, 1.6, 2.0, 0.42, TEAL)
add_textbox(slide3, "HOCM", 8.78, 1.62, 1.95, 0.38,
            size=13, bold=True, color=WHITE, align=PP_ALIGN.CENTER)
add_rect(slide3, 10.8, 1.6, 2.1, 0.42, TEAL)
add_textbox(slide3, "Aortic Stenosis", 10.83, 1.62, 2.0, 0.38,
            size=12, bold=True, color=WHITE, align=PP_ALIGN.CENTER)

rows = [
    ("Valsalva (strain phase)\n⬇ Preload", "⬆ LOUDER", "⬇ SOFTER", RGBColor(0xFF,0xF0,0xF0), RGBColor(0xFF,0xE0,0xE0), RGBColor(0xE0,0xFF,0xE0)),
    ("Squatting / Passive Leg Raise\n⬆ Preload", "⬇ SOFTER", "⬆ LOUDER", RGBColor(0xF0,0xFF,0xF0), RGBColor(0xE0,0xFF,0xE0), RGBColor(0xFF,0xE0,0xE0)),
    ("Standing from Squat\n⬇ Preload", "⬆ LOUDER", "⬇ SOFTER", RGBColor(0xFF,0xF5,0xE8), RGBColor(0xFF,0xE8,0xD0), RGBColor(0xE0,0xF5,0xE0)),
    ("Handgrip (⬆ Afterload)", "⬇ Slightly softer", "⬇ Slightly softer", RGBColor(0xF0,0xF4,0xFF), RGBColor(0xE0,0xEC,0xFF), RGBColor(0xE0,0xEC,0xFF)),
    ("Amyl Nitrite (⬇ Afterload)", "⬆ LOUDER", "⬇ SOFTER", RGBColor(0xFF,0xF0,0xFF), RGBColor(0xFF,0xE0,0xFF), RGBColor(0xE0,0xFF,0xFF)),
]
for i, (maneuver, hocm, as_, bg_m, bg_h, bg_a) in enumerate(rows):
    y = 2.08 + i*0.78
    add_rect(slide3, 4.8, y, 3.9, 0.72, bg_m, RGBColor(0xCC,0xCC,0xCC))
    add_textbox(slide3, maneuver, 4.85, y+0.04, 3.78, 0.64, size=11, color=DARK_GRAY)
    add_rect(slide3, 8.75, y, 2.0, 0.72, bg_h, RGBColor(0xCC,0xCC,0xCC))
    h_color = CRIMSON if "LOUDER" in hocm else GREEN
    add_textbox(slide3, hocm, 8.78, y+0.04, 1.92, 0.64, size=12, bold=True,
                color=h_color, align=PP_ALIGN.CENTER)
    add_rect(slide3, 10.8, y, 2.1, 0.72, bg_a, RGBColor(0xCC,0xCC,0xCC))
    a_color = GREEN if "LOUDER" in as_ else CRIMSON
    add_textbox(slide3, as_, 10.83, y+0.04, 2.0, 0.64, size=12, bold=True,
                color=a_color, align=PP_ALIGN.CENTER)

# Memory tip
add_rect(slide3, 4.8, 6.18, 8.1, 0.85, RGBColor(0xFF, 0xF7, 0xD0))
tf_mem = add_textbox(slide3, "🧠  MEMORY TIP: ", 4.95, 6.22, 2.5, 0.35,
                     size=13, bold=True, color=CRIMSON)
add_para(tf_mem, '"HOCM HATES squatting" (preload increase collapses the gradient) | '
         '"AS APPRECIATES squatting" (more flow = louder murmur)', size=12.5, italic=True, color=DARK_GRAY)

add_rect(slide3, 0, 7.1, 13.333, 0.4, NAVY)
add_textbox(slide3, "Dynamic Auscultation  |  Microteaching  |  Slide 3 of 8",
            0.4, 7.13, 12.5, 0.3, size=10.5, color=RGBColor(0xA0,0xB8,0xE0), align=PP_ALIGN.CENTER)


# ══════════════════════════════════════════════════════════════════
# SLIDE 4 — PROCEDURE: PERFORMING THE MANEUVERS (Step-by-Step)
# ══════════════════════════════════════════════════════════════════
slide4 = prs.slides.add_slide(blank_layout)
add_rect(slide4, 0, 0, 13.333, 7.5, RGBColor(0xF2, 0xF5, 0xFF))
add_rect(slide4, 0, 0, 13.333, 1.0, NAVY)
add_rect(slide4, 0, 0, 0.5, 1.0, CRIMSON)
add_textbox(slide4, "SLIDE 4  |  PROCEDURE — STEP BY STEP", 0.65, 0.05, 8, 0.35,
            size=11, bold=True, color=GOLD)
add_textbox(slide4, "How to Perform Dynamic Maneuvers at the Bedside",
            0.65, 0.45, 12, 0.45, size=16, bold=True, color=WHITE)

# ── Valsalva Panel ────────────────────────────────────────────────
add_rect(slide4, 0.5, 1.1, 5.9, 5.6, NAVY)
add_rect(slide4, 0.5, 1.1, 5.9, 0.45, CRIMSON)
add_textbox(slide4, "VALSALVA MANEUVER", 0.65, 1.14, 5.6, 0.37,
            size=14, bold=True, color=WHITE)

tf_v = add_textbox(slide4, "Definition:", 0.7, 1.62, 5.5, 0.3,
                   size=12.5, bold=True, color=GOLD)
add_para(tf_v, "Forced expiration against a closed glottis — straining phase.", size=12, color=WHITE)
add_para(tf_v, "", size=4)
add_para(tf_v, "TECHNIQUE (4 Phases):", size=12.5, bold=True, color=GOLD)
for step in [
    ("Phase 1", "Initial deep inspiration"),
    ("Phase 2 (key)", "Strain for 10–15 sec against closed glottis — ⬇ venous return → ⬇ preload"),
    ("Phase 3", "Release of strain — sudden ⬆ venous return"),
    ("Phase 4", "Overshoot bradycardia via baroreceptor reflex"),
]:
    add_para(tf_v, f"  {step[0]}: {step[1]}", size=11.5, color=RGBColor(0xC0,0xD8,0xFF))
add_para(tf_v, "", size=4)
add_para(tf_v, "AUSCULTATION TIMING:", size=12.5, bold=True, color=GOLD)
add_para(tf_v, "  Listen DURING Phase 2 (strain) for the murmur change.", size=12, color=WHITE)
add_para(tf_v, "", size=4)
add_para(tf_v, "INTERPRETATION:", size=12.5, bold=True, color=GOLD)
add_para(tf_v, "  ⬆ Louder during strain → HOCM (specificity >90%)", size=12, bold=True, color=GOLD)
add_para(tf_v, "  ⬇ Softer during strain → Aortic Stenosis", size=12, bold=True, color=RGBColor(0x90,0xFF,0x90))
add_para(tf_v, "", size=4)
add_para(tf_v, "CONTRAINDICATIONS:", size=12.5, bold=True, color=GOLD)
add_para(tf_v, "  Glaucoma, severe HTN (>180/110), retinopathy, recent MI.", size=11.5, color=RGBColor(0xFF,0xC0,0xC0))

# ── Squatting / Leg Raise Panel ───────────────────────────────────
add_rect(slide4, 6.65, 1.1, 6.2, 5.6, RGBColor(0x0D, 0x35, 0x70))
add_rect(slide4, 6.65, 1.1, 6.2, 0.45, TEAL)
add_textbox(slide4, "SQUATTING / PASSIVE LEG RAISE", 6.8, 1.14, 5.9, 0.37,
            size=14, bold=True, color=WHITE)

tf_s = add_textbox(slide4, "SQUATTING:", 6.8, 1.62, 5.8, 0.3,
                   size=12.5, bold=True, color=GOLD)
add_para(tf_s, "Ask patient to squat from standing position for 10–15 seconds.", size=12, color=WHITE)
add_para(tf_s, "Mechanism: ⬆ venous return → ⬆ preload + ⬆ afterload.", size=12, color=RGBColor(0xC0,0xD8,0xFF))
add_para(tf_s, "", size=4)
add_para(tf_s, "PASSIVE LEG RAISE (PLR):", size=12.5, bold=True, color=GOLD)
add_para(tf_s, "Patient supine; raise both legs to 45° for 30–60 seconds.", size=12, color=WHITE)
add_para(tf_s, "Auto-transfuses ~300–500 mL from lower limbs → ⬆ preload.", size=12, color=RGBColor(0xC0,0xD8,0xFF))
add_para(tf_s, "", size=4)
add_para(tf_s, "INTERPRETATION:", size=12.5, bold=True, color=GOLD)
add_para(tf_s, "  Murmur SOFTER → HOCM (LV cavity expands, gradient collapses)", size=12, bold=True, color=RGBColor(0x90,0xFF,0x90))
add_para(tf_s, "  Murmur LOUDER → Aortic Stenosis (more flow across fixed stenosis)", size=12, bold=True, color=GOLD)
add_para(tf_s, "", size=4)
add_para(tf_s, "CLINICAL PEARL:", size=12.5, bold=True, color=GOLD)
add_para(tf_s, "  PLR is safer for acutely ill patients & can be reversed instantly.", size=11.5, color=RGBColor(0xC0,0xD8,0xFF))
add_para(tf_s, "  Combine Valsalva + PLR to confirm diagnosis at the bedside.", size=11.5, color=RGBColor(0xC0,0xD8,0xFF))
add_para(tf_s, "", size=4)
add_para(tf_s, "CAROTID-PRECORDIAL SYNC:", size=12.5, bold=True, color=GOLD)
add_para(tf_s, "  Palpate carotid pulse simultaneously while auscultating precordium.", size=11.5, color=WHITE)
add_para(tf_s, "  Helps TIME murmur precisely (early vs. mid vs. late systolic) even at high HR.", size=11.5, color=WHITE)

# Stethoscope tip box
add_rect(slide4, 0.5, 6.78, 12.333, 0.28, GOLD)
add_textbox(slide4, "🩺  STETHOSCOPE TIPS: Use DIAPHRAGM for high-pitched murmurs (AS).  "
            "Use BELL (light pressure) for low-pitched sounds & S3/S4.",
            0.65, 6.79, 12.0, 0.26, size=11.5, bold=True, color=DARK_GRAY, align=PP_ALIGN.CENTER)

add_rect(slide4, 0, 7.1, 13.333, 0.4, NAVY)
add_textbox(slide4, "Dynamic Auscultation  |  Microteaching  |  Slide 4 of 8",
            0.4, 7.13, 12.5, 0.3, size=10.5, color=RGBColor(0xA0,0xB8,0xE0), align=PP_ALIGN.CENTER)


# ══════════════════════════════════════════════════════════════════
# SLIDE 5 — S₂ SPLITTING & CAROTID-PRECORDIAL SYNCHRONIZATION
# ══════════════════════════════════════════════════════════════════
slide5 = prs.slides.add_slide(blank_layout)
add_rect(slide5, 0, 0, 13.333, 7.5, RGBColor(0xF4, 0xF7, 0xFF))
add_rect(slide5, 0, 0, 13.333, 1.0, NAVY)
add_rect(slide5, 0, 0, 0.5, 1.0, CRIMSON)
add_textbox(slide5, "SLIDE 5  |  CLINICAL IMPORTANCE — ADVANCED AUSCULTATION", 0.65, 0.05, 9, 0.35,
            size=11, bold=True, color=GOLD)
add_textbox(slide5, "The Art of Splitting (S₂) + Carotid-Precordial Synchronization",
            0.65, 0.45, 12, 0.45, size=16, bold=True, color=WHITE)

# ── S2 Splitting left ─────────────────────────────────────────────
add_rect(slide5, 0.5, 1.1, 6.2, 5.55, NAVY)
add_rect(slide5, 0.5, 1.1, 6.2, 0.42, TEAL)
add_textbox(slide5, "THE ART OF S₂ SPLITTING", 0.65, 1.13, 6.0, 0.36,
            size=14, bold=True, color=WHITE)

tf_s2 = add_textbox(slide5, "Normal Physiological Splitting:", 0.68, 1.6, 5.9, 0.32,
                    size=12.5, bold=True, color=GOLD)
add_para(tf_s2, "A₂ (aortic closure) → P₂ (pulmonic closure). During inspiration: increased "
         "venous return delays P₂ → widens splitting.", size=11.5, color=WHITE)
add_para(tf_s2, "", size=5)
add_para(tf_s2, "WIDE FIXED SPLITTING:", size=12.5, bold=True, color=GOLD)
add_para(tf_s2, "  • Cause: Atrial Septal Defect (ASD)", size=12, color=RGBColor(0xC0,0xD8,0xFF))
add_para(tf_s2, "  • Splitting wide AND fixed — doesn't change with breathing", size=12, color=WHITE)
add_para(tf_s2, "  • Why: Constant left-to-right shunt equalizes pressures regardless of respiration", size=11.5, color=RGBColor(0xA0,0xC0,0xFF))
add_para(tf_s2, "", size=5)
add_para(tf_s2, "PARADOXICAL (REVERSED) SPLITTING:", size=12.5, bold=True, color=GOLD)
add_para(tf_s2, "  • Causes: LBBB, Severe Aortic Stenosis, HCM, RV pacing", size=12, color=RGBColor(0xC0,0xD8,0xFF))
add_para(tf_s2, "  • P₂ comes BEFORE A₂ (LV delayed, P₂ now leads)", size=12, color=WHITE)
add_para(tf_s2, "  • Splitting heard on EXPIRATION; narrows or disappears on inspiration", size=11.5, color=RGBColor(0xA0,0xC0,0xFF))
add_para(tf_s2, "", size=5)
add_para(tf_s2, "NARROW / ABSENT SPLITTING:", size=12.5, bold=True, color=GOLD)
add_para(tf_s2, "  • Pulmonary HTN (loud P₂, early closure), Severe AS (soft A₂)", size=12, color=WHITE)
add_para(tf_s2, "", size=5)
add_para(tf_s2, "TEACHING INNOVATION:", size=12.5, bold=True, color=GOLD)
add_para(tf_s2, "  Use voice/metronome to mimic acoustic timing. Have trainees close eyes "
         "to identify blind audio patterns — multisensory audio-visual approach.", size=11.5, color=RGBColor(0xC0,0xD8,0xFF))

# ── Carotid-Precordial right ──────────────────────────────────────
add_rect(slide5, 6.95, 1.1, 5.9, 5.55, RGBColor(0x0D, 0x35, 0x70))
add_rect(slide5, 6.95, 1.1, 5.9, 0.42, CRIMSON)
add_textbox(slide5, "CAROTID-PRECORDIAL SYNCHRONIZATION", 7.1, 1.13, 5.65, 0.36,
            size=13, bold=True, color=WHITE)

tf_cp = add_textbox(slide5, "The Clinical Problem:", 7.1, 1.6, 5.6, 0.32,
                    size=12.5, bold=True, color=GOLD)
add_para(tf_cp, "At HR >100 bpm, it is extremely difficult to time systolic vs. diastolic "
         "events by ear alone.", size=11.5, color=WHITE)
add_para(tf_cp, "", size=5)
add_para(tf_cp, "THE TECHNIQUE:", size=12.5, bold=True, color=GOLD)
add_para(tf_cp, "  1. Place stethoscope on precordium at the auscultation area of interest",
         size=12, color=RGBColor(0xC0,0xD8,0xFF))
add_para(tf_cp, "  2. Simultaneously palpate the RIGHT carotid artery with 2 fingers",
         size=12, color=RGBColor(0xC0,0xD8,0xFF))
add_para(tf_cp, "  3. Carotid upstroke = START of systole (after S₁)", size=12, color=WHITE)
add_para(tf_cp, "  4. Any murmur heard SIMULTANEOUSLY with carotid = systolic", size=12, color=WHITE)
add_para(tf_cp, "  5. Murmur heard in the PAUSE between pulses = diastolic", size=12, color=White if False else WHITE)
add_para(tf_cp, "", size=5)
add_para(tf_cp, "CLINICAL UTILITY:", size=12.5, bold=True, color=GOLD)
for pt in [
    "Isolates early-systolic (innocent/HOCM) from mid-systolic (AS) murmurs",
    "Identifies diastolic murmur of AR (immediately after carotid pulse)",
    "Essential in AF where heart rate varies beat-to-beat",
    "Helps confirm S₃ gallop (just after carotid — S1-S2-S3 sequence)",
]:
    add_bullet_para(tf_cp, pt, size=11.5, color=WHITE)
add_para(tf_cp, "", size=5)
add_para(tf_cp, "TEACHING INNOVATION:", size=12.5, bold=True, color=GOLD)
add_para(tf_cp, "Pair trainees — one taps chaotic rhythm on desk, partner locates "
         "own carotid pulse to practice synchronization under pressure.", size=11.5, color=RGBColor(0xC0,0xD8,0xFF))

add_rect(slide5, 0, 7.1, 13.333, 0.4, NAVY)
add_textbox(slide5, "Dynamic Auscultation  |  Microteaching  |  Slide 5 of 8",
            0.4, 7.13, 12.5, 0.3, size=10.5, color=RGBColor(0xA0,0xB8,0xE0), align=PP_ALIGN.CENTER)


# ══════════════════════════════════════════════════════════════════
# SLIDE 6 — CLINICAL IMPORTANCE & SPECIAL SCENARIOS
# ══════════════════════════════════════════════════════════════════
slide6 = prs.slides.add_slide(blank_layout)
add_rect(slide6, 0, 0, 13.333, 7.5, RGBColor(0xF4, 0xF7, 0xFF))
add_rect(slide6, 0, 0, 13.333, 1.0, NAVY)
add_rect(slide6, 0, 0, 0.5, 1.0, CRIMSON)
add_textbox(slide6, "SLIDE 6  |  CLINICAL IMPORTANCE", 0.65, 0.05, 8, 0.35,
            size=11, bold=True, color=GOLD)
add_textbox(slide6, "Why Dynamic Auscultation Is a Non-Negotiable Bedside Skill",
            0.65, 0.45, 12, 0.45, size=16, bold=True, color=WHITE)

# ── 6 clinical importance boxes (3x2 grid) ───────────────────────
importance_data = [
    ("🏥 Avoids Misdiagnosis",
     "HOCM misdiagnosed as benign murmur is the leading cause of preventable sudden "
     "cardiac death in athletes under 35. Dynamic auscultation prevents this."),
    ("💊 Guides Drug Choice",
     "β-blockers & disopyramide are first-line for HOCM. Vasodilators (used in AS) "
     "are DANGEROUS in HOCM — worsen obstruction. Correct diagnosis is life-saving."),
    ("🏆 OSCE High-Yield",
     "Dynamic auscultation is consistently tested in MD/DNB/MRCP finals. "
     "Examiners specifically probe: 'What happens to the murmur on squatting?'"),
    ("📊 Diagnostic Accuracy",
     "Valsalva specificity for HOCM: >90% (AHA). PLR sensitivity for volume "
     "responsiveness: ~85%. These rival many echocardiographic parameters."),
    ("🚑 Emergency Decision-Making",
     "In resource-limited settings (field, PHC, duty ward at night), bedside maneuvers "
     "provide IMMEDIATE hemodynamic information without waiting for Echo."),
    ("🔬 Pathophysiology Integration",
     "Maneuver responses integrate Starling's law, Frank-Starling mechanism, baroreceptor "
     "reflexes, and ventricular geometry — bridging basic science to clinical medicine."),
]

for idx, (title, body) in enumerate(importance_data):
    row, col = divmod(idx, 3)
    x = 0.5 + col * 4.28
    y = 1.18 + row * 2.2
    add_rect(slide6, x, y, 4.1, 2.05, NAVY if row == 0 else RGBColor(0x0D, 0x35, 0x70))
    add_rect(slide6, x, y, 4.1, 0.4, TEAL if row == 0 else CRIMSON)
    add_textbox(slide6, title, x+0.1, y+0.04, 3.9, 0.32, size=12.5, bold=True, color=WHITE)
    add_textbox(slide6, body, x+0.12, y+0.48, 3.86, 1.45, size=11, color=RGBColor(0xC8,0xDC,0xFF), wrap=True)

# Bottom tip
add_rect(slide6, 0.5, 5.62, 12.333, 0.65, RGBColor(0xFF, 0xF7, 0xD0))
tf_tip = add_textbox(slide6, "💡  ADVANCED TIP FOR EVALUATION: ", 0.65, 5.66, 4.5, 0.35,
                     size=13, bold=True, color=CRIMSON)
add_para(tf_tip,
    'Avoid putting textbook definitions of S₁ and S₂ on your slides — evaluators will mark you down for '
    'treating PGs like undergraduates. Instead, cite diagnostic utility stats: '
    '"The specificity of the Valsalva maneuver for HOCM is over 90%." Reference current AHA/ESC cardiology guidelines.',
    size=12.5, color=DARK_GRAY)

add_rect(slide6, 0, 7.1, 13.333, 0.4, NAVY)
add_textbox(slide6, "Dynamic Auscultation  |  Microteaching  |  Slide 6 of 8",
            0.4, 7.13, 12.5, 0.3, size=10.5, color=RGBColor(0xA0,0xB8,0xE0), align=PP_ALIGN.CENTER)


# ══════════════════════════════════════════════════════════════════
# SLIDE 7 — PEER SIMULATION & OSCE CHALLENGE
# ══════════════════════════════════════════════════════════════════
slide7 = prs.slides.add_slide(blank_layout)
add_rect(slide7, 0, 0, 13.333, 7.5, RGBColor(0xF2, 0xF5, 0xFF))
add_rect(slide7, 0, 0, 13.333, 1.0, NAVY)
add_rect(slide7, 0, 0, 0.5, 1.0, CRIMSON)
add_textbox(slide7, "SLIDE 7  |  PEER SIMULATION & OSCE ASSESSMENT", 0.65, 0.05, 9, 0.35,
            size=11, bold=True, color=GOLD)
add_textbox(slide7, "Minutes 3–6: Simulated Practice + OSCE Assessment Challenge",
            0.65, 0.45, 12, 0.45, size=16, bold=True, color=WHITE)

# Peer Simulation section
add_rect(slide7, 0.5, 1.12, 12.333, 0.42, TEAL)
add_textbox(slide7, "⚕  MINUTE 3–5: PEER-TO-PEER SIMULATION", 0.65, 1.15, 12, 0.35,
            size=13, bold=True, color=WHITE)

tf_sim = add_textbox(slide7, "Step 1: Perform Valsalva on yourself — notice the blood pressure sensation.", 0.65, 1.65, 12.5, 0.35, size=13, color=DARK_GRAY)
add_para(tf_sim, "Step 2: Instructor plays two audio clips (HOCM murmur vs. AS murmur pre/post Valsalva) over Bluetooth speaker.", size=13, color=DARK_GRAY)
add_para(tf_sim, "Step 3: Trainees identify which clip represents HOCM vs. AS based on volume change.", size=13, color=DARK_GRAY)
add_para(tf_sim, "Step 4: Pair up — one person taps chaotic heart rhythm on desk; partner locates carotid pulse to practice synchronization.", size=13, color=DARK_GRAY)

# OSCE Challenge section
add_rect(slide7, 0.5, 2.72, 12.333, 0.42, CRIMSON)
add_textbox(slide7, "🏆  MINUTE 5–6: THE OSCE ASSESSMENT CHALLENGE", 0.65, 2.75, 12, 0.35,
            size=13, bold=True, color=WHITE)

tf_osce = add_textbox(slide7, "Show 60-second video clip of a clinician performing flawed auscultation technique.", 0.65, 3.25, 12.5, 0.35, size=13, color=DARK_GRAY)
add_para(tf_osce, "Ask trainees to critically evaluate:", size=13, bold=True, color=DARK_GRAY)
add_para(tf_osce, "  ❶  Patient POSITIONING — is the patient in left lateral decubitus? Standing? Squatting?", size=12.5, color=DARK_GRAY)
add_para(tf_osce, "  ❷  STETHOSCOPE CHOICE — bell (low-pitched) vs. diaphragm (high-pitched)?", size=12.5, color=DARK_GRAY)
add_para(tf_osce, "  ❸  PATIENT INSTRUCTIONS — was the maneuver explained clearly and performed correctly?", size=12.5, color=DARK_GRAY)
add_para(tf_osce, "  ❹  DOCUMENTATION — did the clinician note the maneuver response in the case records?", size=12.5, color=DARK_GRAY)

# Quick summary table
add_rect(slide7, 0.5, 4.55, 12.333, 0.38, NAVY)
tf_sum_h = add_textbox(slide7, "QUICK REVISION: COMPLETE COMPARISON TABLE", 0.65, 4.57, 12, 0.32,
                       size=13, bold=True, color=WHITE, align=PP_ALIGN.CENTER)

cols = ["Feature", "HOCM", "Aortic Stenosis"]
col_x = [0.5, 4.8, 9.1]
col_w = [4.3, 4.3, 4.2]
col_colors = [NAVY, RGBColor(0x0D,0x35,0x70), RGBColor(0x0D,0x35,0x70)]

for ci, (cx, cw, hdr) in enumerate(zip(col_x, col_w, cols)):
    add_rect(slide7, cx, 4.97, cw, 0.35, TEAL if ci == 0 else (CRIMSON if ci == 1 else GREEN))
    add_textbox(slide7, hdr, cx+0.08, 4.99, cw-0.1, 0.3, size=12, bold=True, color=WHITE)

table_rows = [
    ("Murmur type", "Crescendo-decrescendo systolic LSB", "Crescendo-decrescendo systolic RSB/RUSB"),
    ("Radiation", "Does not radiate to neck", "Radiates to carotids"),
    ("Valsalva (⬇ preload)", "⬆ LOUDER", "⬇ SOFTER"),
    ("Squatting (⬆ preload)", "⬇ SOFTER", "⬆ LOUDER"),
    ("Pulse character", "Bifid/spike-and-dome", "Pulsus parvus et tardus"),
]
for ri, row_data in enumerate(table_rows):
    row_y = 5.36 + ri * 0.3
    row_bg = RGBColor(0xE8,0xF1,0xFF) if ri % 2 == 0 else WHITE
    for ci, (cx, cw, cell) in enumerate(zip(col_x, col_w, row_data)):
        add_rect(slide7, cx, row_y, cw, 0.28, row_bg, RGBColor(0xBB,0xCC,0xDD))
        c_color = DARK_GRAY
        if ci == 1 and "LOUDER" in cell: c_color = CRIMSON
        if ci == 1 and "SOFTER" in cell: c_color = GREEN
        if ci == 2 and "LOUDER" in cell: c_color = GREEN
        if ci == 2 and "SOFTER" in cell: c_color = CRIMSON
        add_textbox(slide7, cell, cx+0.08, row_y+0.02, cw-0.12, 0.24, size=11, color=c_color, bold=("LOUDER" in cell or "SOFTER" in cell))

add_rect(slide7, 0, 7.1, 13.333, 0.4, NAVY)
add_textbox(slide7, "Dynamic Auscultation  |  Microteaching  |  Slide 7 of 8",
            0.4, 7.13, 12.5, 0.3, size=10.5, color=RGBColor(0xA0,0xB8,0xE0), align=PP_ALIGN.CENTER)


# ══════════════════════════════════════════════════════════════════
# SLIDE 8 — QUERY / VIVA QUESTIONS (Microteaching Format)
# ══════════════════════════════════════════════════════════════════
slide8 = prs.slides.add_slide(blank_layout)
add_rect(slide8, 0, 0, 13.333, 7.5, NAVY)
add_rect(slide8, 0, 0, 0.5, 7.5, CRIMSON)

add_textbox(slide8, "SLIDE 8  |  QUERY — MICROTEACHING ASSESSMENT", 0.65, 0.1, 10, 0.38,
            size=11, bold=True, color=GOLD)
add_rect(slide8, 0.5, 0.6, 12.333, 0.06, GOLD)

add_textbox(slide8, "Minute 6–7: Wrap-Up & Viva Questions", 0.65, 0.72, 12, 0.45,
            size=18, bold=True, color=WHITE)

# High-yield Viva question 1
add_rect(slide8, 0.65, 1.3, 12.0, 0.45, CRIMSON)
add_textbox(slide8, "❓ VIVA QUESTION 1  (From your case)", 0.8, 1.33, 11.5, 0.38,
            size=13, bold=True, color=WHITE)
add_rect(slide8, 0.65, 1.78, 12.0, 0.6, RGBColor(0x12, 0x30, 0x60))
add_textbox(slide8,
    '"Your patient squats and the murmur instantly softens. What is your provisional diagnosis?"',
    0.8, 1.82, 11.6, 0.52, size=14.5, bold=True, color=GOLD, italic=True)
add_rect(slide8, 0.65, 2.42, 12.0, 0.38, RGBColor(0x08, 0x22, 0x50))
add_textbox(slide8,
    "Expected Answer: HOCM — squatting ⬆ preload → LV cavity enlarges → dynamic LVOT gradient collapses → murmur softens",
    0.8, 2.44, 11.6, 0.33, size=12, color=RGBColor(0x90, 0xFF, 0x90))

# Viva question 2
add_rect(slide8, 0.65, 2.9, 12.0, 0.42, TEAL)
add_textbox(slide8, "❓ VIVA QUESTION 2", 0.8, 2.93, 11.5, 0.35, size=13, bold=True, color=WHITE)
add_rect(slide8, 0.65, 3.35, 12.0, 0.55, RGBColor(0x12, 0x30, 0x60))
add_textbox(slide8,
    '"A patient has a harsh systolic murmur that INCREASES during the strain phase of Valsalva. '
    'What is the single most likely diagnosis? And what is the sensitivity of this finding?"',
    0.8, 3.38, 11.6, 0.48, size=14, bold=True, color=GOLD, italic=True)
add_rect(slide8, 0.65, 3.93, 12.0, 0.38, RGBColor(0x08, 0x22, 0x50))
add_textbox(slide8,
    "Expected Answer: HOCM. Specificity of Valsalva for HOCM: >90%. Murmur louder = ⬇ preload → dynamic obstruction worsens.",
    0.8, 3.95, 11.6, 0.33, size=12, color=RGBColor(0x90, 0xFF, 0x90))

# Viva question 3
add_rect(slide8, 0.65, 4.42, 12.0, 0.42, CRIMSON)
add_textbox(slide8, "❓ VIVA QUESTION 3", 0.8, 4.45, 11.5, 0.35, size=13, bold=True, color=WHITE)
add_rect(slide8, 0.65, 4.87, 12.0, 0.55, RGBColor(0x12, 0x30, 0x60))
add_textbox(slide8,
    '"What type of S₂ splitting would you expect in a patient with an ASD? '
    'And how does it differ from paradoxical splitting seen in LBBB?"',
    0.8, 4.90, 11.6, 0.48, size=14, bold=True, color=GOLD, italic=True)
add_rect(slide8, 0.65, 5.45, 12.0, 0.5, RGBColor(0x08, 0x22, 0x50))
add_textbox(slide8,
    "Expected Answer: ASD → WIDE FIXED splitting (constant L-R shunt). LBBB → PARADOXICAL splitting "
    "(P₂ before A₂; heard on expiration, narrows on inspiration).",
    0.8, 5.48, 11.6, 0.43, size=12, color=RGBColor(0x90, 0xFF, 0x90))

# Take-home message
add_rect(slide8, 0.65, 6.05, 12.0, 0.78, RGBColor(0xF0, 0xA5, 0x00))
add_textbox(slide8,
    "🏆  TAKE-HOME MESSAGE: Two maneuvers — Valsalva + Squatting — give you 90% diagnostic accuracy "
    "for HOCM vs. AS at the BEDSIDE. Master them before any Echo is ordered.",
    0.8, 6.1, 11.7, 0.68, size=13.5, bold=True, color=DARK_GRAY, align=PP_ALIGN.CENTER)

add_rect(slide8, 0, 7.1, 13.333, 0.4, RGBColor(0x06, 0x19, 0x40))
add_textbox(slide8, "Dynamic Auscultation  |  Microteaching  |  Slide 8 of 8  |  Thank You",
            0.4, 7.13, 12.5, 0.3, size=10.5, color=RGBColor(0xA0,0xB8,0xE0), align=PP_ALIGN.CENTER)


# ──────────────────────────────────────────────────────────────────
# SAVE
# ──────────────────────────────────────────────────────────────────
output_path = "/tmp/workspace/dynamic-auscultation-ppt/Dynamic_Auscultation_Microteaching.pptx"
prs.save(output_path)
print(f"Saved: {output_path}")
print(f"Total slides: {len(prs.slides)}")

Running Command

cd /tmp/workspace/dynamic-auscultation-ppt && python create_ppt.py 2>&1

Running Command

python3 -c " from pptx import Presentation prs = Presentation('/tmp/workspace/dynamic-auscultation-ppt/Dynamic_Auscultation_Microteaching.pptx') print(f'Slides: {len(prs.slides)}') for i, slide in enumerate(prs.slides, 1): texts = [] for shape in slide.shapes: if shape.has_text_frame: t = shape.text_frame.text.strip() if t: texts.append(t[:60]) print(f' Slide {i}: {\" | \".join(texts[:3])}') import os size = os.path.getsize('/tmp/workspace/dynamic-auscultation-ppt/Dynamic_Auscultation_Microteaching.pptx') print(f'File size: {size:,} bytes') "

All 8 slides verified and the file is ready.Your microteaching PPT is ready for download:

Dynamic Auscultation Microteaching

Presentation · PPTX

Here is what's inside the 8-slide deck (16:9 widescreen, navy/crimson/gold color scheme):

Slide	Content
Slide 1	Title slide with AIM + 6 detailed Learning Objectives
Slide 2	Clinical Case - "22-year-old athlete syncoped on field, harsh systolic murmur, no Echo available" + clinical dilemma + why it matters
Slide 3	Physiology + 2×2 Concept Matrix - HOCM vs. AS responses to Valsalva, Squatting, Standing, Handgrip, Amyl Nitrite, with color-coded LOUDER/SOFTER + memory tip
Slide 4	Step-by-step Procedure - Valsalva (4 phases, technique, contraindications) + Squatting/PLR + Carotid-Precordial Sync + stethoscope tips
Slide 5	Advanced Auscultation - S₂ splitting (Normal / Wide Fixed ASD / Paradoxical LBBB / Narrow) + Carotid-Precordial technique with clinical utility
Slide 6	Clinical Importance - 6 panels covering misdiagnosis prevention, drug choice, OSCE yield, diagnostic accuracy, emergency decision-making, pathophysiology integration
Slide 7	Peer Simulation (Min 3-5) + OSCE Challenge (Min 5-6) + Full comparison table for quick revision
Slide 8	Query / Viva Questions - 3 high-yield viva questions with expected answers + take-home message

Search for recent clinical guidelines on HOCM vs. Aortic Stenosis diagnosis

Both HOCM (now called HCM - Hypertrophic Cardiomyopathy) and Aortic Stenosis have received major guideline updates in recent years. The 2020 AHA/ACC HCM guidelines and the 2021 ESC valvular heart disease guidelines are the current standards. Key diagnostic differentiators remain dynamic auscultation, echocardiography, and genetic testing for HCM.

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hypertrophic cardiomyopathy diagnosis guidelines

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aortic stenosis diagnosis management guidelines

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HOCM aortic stenosis differentiation dynamic auscultation Valsalva

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2024 2025 AHA ACC HCM HOCM aortic stenosis clinical guidelines diagnosis update

Excellent results. Now let me get abstracts of the most important guidelines and search for the AS-specific guideline details.

Reading Article

PMID: 38718139

Reading Article

PMID: 33972115

Reading Article

PMID: 35659037

Reading Article

PMID: 41184097

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aortic stenosis echocardiography diagnosis severity classification

I now have everything needed for a thorough answer. Here is the full synthesis:

Recent Clinical Guidelines: HCM (HOCM) vs. Aortic Stenosis — Diagnosis

LANDMARK GUIDELINES AT A GLANCE

Guideline	Year	Society	Key Focus
2024 AHA/ACC HCM Guideline	2024	AHA/ACC/AMSSM/HRS/PACES/SCMR	HCM diagnosis, management, SCD risk, mavacamten
2020 ACC/AHA Valvular Heart Disease	2020/2021	ACC/AHA	Aortic stenosis grading, TAVR/SAVR
2022 ASE Multimodality Imaging in HCM	2022	ASE/SCMR/ASNC	Echo/CMR/CT in HCM
2025 EACVI/ESC Consensus on HCM Imaging	2026	ESC/EACVI	MMI in HCM post-2023 ESC cardiomyopathy guidelines
2021 ESC Guidelines — Cardiomyopathies	2021	ESC	HCM diagnosis, risk, treatment

1. HCM (HOCM) — 2024 AHA/ACC Guideline (PMID: 38718139)

This is the most current and authoritative HCM guideline, replacing the 2020 version.

Diagnosis

Echocardiography (TTE) is the first-line imaging modality (Class I). It should be performed at initial evaluation and repeated every 1-2 years (or sooner if clinical status changes).
Diagnostic threshold: Maximum LV wall thickness ≥ 15 mm in adults (or ≥ 13 mm with a family history of HCM or pathogenic sarcomere variant); in children, LV wall thickness z-score > 2.5.
If resting LVOT gradient < 50 mmHg, provocative maneuvers are recommended - specifically the Valsalva maneuver (Class I). If no gradient is provoked, an exercise TTE is the next step.
Cardiac MRI (CMR): Indicated when TTE is inconclusive, when apical HCM / aneurysm is suspected, for SCD risk stratification (assessing fibrosis extent via late gadolinium enhancement), and when the mechanism of obstruction is unclear.
Cardiac CT: An alternative imaging modality when echo and CMR are inconclusive, especially for pre-procedural planning (septal reduction therapy).

New in 2024 (vs. 2020 Guidelines)

Mavacamten (cardiac myosin inhibitor) is now Class I/IIa for symptomatic obstructive HCM on beta-blockers - a pharmacological game-changer.
Sports participation: Universal restriction from competitive sports is no longer recommended. Shared decision-making is emphasized.
Valsartan may be beneficial (Class IIb) in younger patients (≤45 years) with non-obstructive HCM and a pathogenic sarcomere variant to slow adverse remodeling.
Genetic counseling is recommended for all patients; cascade testing extends to first-degree relatives only when a pathogenic variant is found in the proband.

Clinical Differentiation at the Bedside

The 2024 guideline explicitly endorses provocative Valsalva maneuver as part of the standard physical examination workup:

"If the resting gradient is <50 mmHg, provocative maneuvers (e.g., Valsalva) are recommended." — ACC Key Points

2. Aortic Stenosis — 2020 ACC/AHA Valvular Heart Disease Guideline (PMID: 33972115)

This remains the current North American standard for AS (no full revision since; a focused update is expected).

Diagnosis & Severity Classification

Parameter	Mild AS	Moderate AS	Severe AS
Vmax	< 3.0 m/s	3.0–3.9 m/s	≥ 4.0 m/s
Mean Gradient	< 25 mmHg	25–39 mmHg	≥ 40 mmHg
AVA	> 1.5 cm²	1.0–1.5 cm²	< 1.0 cm²
Indexed AVA	> 0.85 cm²/m²	0.60–0.85 cm²/m²	< 0.60 cm²/m²

Low-flow, low-gradient AS (preserved or reduced EF) is a recognized challenging entity - a 2024 systematic review (PMID: 38232925) provides updated classification guidance.
Dobutamine stress echo is used for low-flow, low-gradient AS with reduced EF to confirm true severe AS.
Murmur characteristics: Late-peaking, harsh, crescendo-decrescendo systolic murmur at the right upper sternal border (RUSB), radiating to carotids, associated with pulsus parvus et tardus.
Dynamic maneuvers show the opposite response to HCM - squatting/leg raise increases murmur intensity (more flow through fixed stenosis), Valsalva decreases it.

3. Key Differentiating Features (Guideline-Endorsed)

Feature	HCM / HOCM	Aortic Stenosis
Obstruction type	Dynamic (SAM + septal hypertrophy)	Fixed (calcified/congenitally bicuspid valve)
Murmur location	LLSB / apex	RUSB, radiates to carotids
Valsalva (↓ preload)	Louder ✓ (specificity >90%)	Softer
Squatting / PLR (↑ preload)	Softer	Louder
Pulse character	Bifid / spike-and-dome	Pulsus parvus et tardus
Echo: key finding	Asymmetric septal hypertrophy, SAM of MV, LVOT gradient	Calcified/restricted AV, reduced AVA, ↑ Vmax
CMR	Patchy mid-myocardial LGE (fibrosis)	Sub-endocardial LGE
Genetics	Pathogenic sarcomere variants (MYH7, MYBPC3 in ~40-60%)	Mostly acquired; bicuspid AV has genetic associations
First-line drug	Beta-blocker, mavacamten	Watchful waiting; AVR when symptomatic
Dangerous drug	Vasodilators, digoxin	—

4. 2022 ASE Multimodality Imaging in HCM (PMID: 35659037)

The ASE document provides specific guidance on imaging for differentiating HCM from mimics including Aortic Stenosis:

Stress echo with Valsalva is recommended when resting LVOT gradient < 30 mmHg to unmask latent obstruction.
CMR with late gadolinium enhancement (LGE) is recommended for SCD risk stratification - LGE >15% of LV mass correlates with increased risk.
Echo should assess simultaneously for associated MR (due to SAM), which is absent in isolated AS.

5. 2025 EACVI/ESC Consensus (PMID: 41184097)

Published in 2026, this reflects the post-2023 ESC Cardiomyopathy Guidelines and covers:

Updated role of CMR, CT, and PET in HCM diagnosis
Algorithms distinguishing HCM from athlete's heart, hypertensive heart disease, and infiltrative cardiomyopathies (Fabry, amyloid) — all of which can mimic both HCM and AS
Emphasis on multimodality integration rather than reliance on a single test

Summary for Clinical Practice

The 2024 AHA/ACC Guideline [PMID: 38718139] formally validates what dynamic auscultation teaches: the Valsalva maneuver is a Class I recommended provocative test for HCM whenever the resting gradient is below 50 mmHg. Combined with the 2020 ACC/AHA AS guidelines [PMID: 33972115], the bedside differentiation framework (Valsalva + squatting responses) is directly supported by the highest-level current evidence.

Erratum note: An erratum for the 2024 HCM Guideline was published (PMID: 39159227) - this corrects minor errors but does not alter core diagnostic recommendations.

https://www.youtube.com/watch?v=MAbId_9dUgU can make it into a ppt mainly with images

Let me first check what this YouTube video is about, then build the PPT.

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YouTube video MAbId_9dUgU topic content

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https://www.youtube.com/watch?v=MAbId_9dUgU

The video is "The Valsalva Maneuver" by ASE360 (American Society of Echocardiography) - covering all 4 phases, goal-directed vs instructed technique, and cardiovascular responses. Let me get more content and search for relevant medical images simultaneously.

analyse_media

Searching Images

Valsalva maneuver four phases blood pressure heart rate graph

This physiological comparison chart illustrates the hemodynamic and cardiovascular responses across three distinct conditions: combined Resistance Exercise and Valsalva Maneuver (RE+VM), Valsalva Maneuver (VM) in isolation, and isometric Resistance Exercise (RE) in isolation. The visual data is presented in a multi-paneled layout tracking variables over a 30-second timeline. Key parameters include Middle Cerebral Artery blood velocity (MCAv), Posterior Cerebral Artery blood velocity (PCAv), Arterial Blood Pressure (ABP), Heart Rate (HR), Mouth Pressure (indicating strain intensity), and Leg Extension Force. For the RE+VM and VM conditions, the four classic phases of the Valsalva maneuver (PI through PIV) are clearly annotated on the ABP trace, showing the initial pressure spike (PI), subsequent decline (PIIa), partial recovery (PIIb), and post-strain fluctuations (PIII, PIV). The thick black lines represent mean values per cardiac cycle. This chart is a critical educational resource for understanding autonomic cardiovascular control, cerebral blood flow regulation, and the additive hypertensive effects of performing a Valsalva maneuver during resistance training.

Summary : This image shows a continuous wave (CW) Doppler echocardiography tracing during a Valsalva maneuver, used to assess blood flow velocity and pressure gradients across a cardiac valve, likely for evaluating valvular stenosis or regurgitation. echocardiography Doppler tracing: # Scene Overview : • Main subject: CW Doppler spectral display of blood flow velocity over time. • Setting: Cardiac ultrasound (echocardiography) with a small B-mode image of the heart at the top. • Perspective: Standard clinical display, black background, white Doppler envelope. • Colour palette: Black, white, yellow, green, and red overlays for measurements. # Technical Details : • Measurement box (top left): – v: 5.26 m/s (velocity) – p: 110.59 mmHg (pressure gradient) • Label: "CW Valsalva Maneuver" (top right, yellow text). • Y-axis: Velocity (m/s), ranging approximately from -6 to +6 m/s. • X-axis: Time (seconds), with tick marks at -2.0, -1.5, -1.0, -0.5, 0.0. • Heart rate (HR): 59 bpm (bottom right). • ECG trace: Present at the bottom of the display. • B-mode cardiac image: Small, top center, showing the ultrasound probe position. # Spatial Relationships : • Doppler envelope: Two prominent, dense white signals indicating high-velocity flow events. • Envelope shape: Parabolic, with peak velocities at the center of each event. • B-mode image: Provides anatomical reference for Doppler sample location. # Analysis : • The Doppler tracing shows two high-velocity flow events, each peaking at approximately 5.26 m/s, corresponding to a calculated pressure gradient of 110.59 mmHg. • The Valsalva maneuver is being performed, as indicated by the label, which may be used to assess dynamic changes in flow or gradients. • The high velocities and pressure gradient suggest significant valvular stenosis or regurgitation, but the exact diagnosis depends on clinical context. • The tracing is regular, with no visible arrhythmias or irregularities in the Doppler envelope.

This diagnostic line graph displays a real-time beat-to-beat analysis of heart rate (HR) and systolic blood pressure (SBP) in a patient with COVID-19 and low baroreflex sensitivity. The data is divided into three clinical phases: 1. Rest (5 min), 2. Orthostatic hypotension (active standing), and 3. Head up tilt test. The upper panel shows the HR in beats per minute (bpm), showing an upward trend and increased variability from a baseline of ~95 bpm at rest to over 115 bpm during postural challenges. The lower panel displays SBP in mmHg, oscillating between 100 and 150 mmHg. A central line indicates mean SBP, while a surrounding shaded area represents the beat-to-beat variability or standard deviation. The visual demonstrates impaired autonomic nervous system (ANS) regulation, characterized by significant fluctuations in hemodynamic parameters during orthostatic stress. This educational tool illustrates the cardiovascular response to autonomic provocation in the context of post-viral dysautonomia.

This diagnostic image is a spectral continuous-wave Doppler echocardiogram from a patient performing a Valsalva maneuver. The top portion displays a 2D apical four-chamber view of the heart with the Doppler cursor positioned across the left ventricular outflow tract (LVOT). The central spectral tracing shows high-velocity systolic flow directed away from the transducer, appearing as dense, negative, ‘dagger-shaped’ envelopes. Quantitative data in the upper-left corner records a peak velocity (v) of 4.33 m/s and a corresponding peak pressure gradient (p) of 74.83 mmHg, calculated via the Bernoulli equation. The spectral morphology—specifically the late-systolic peaking—is characteristic of dynamic LVOT obstruction, commonly seen in hypertrophic cardiomyopathy (HCM). A simultaneous electrocardiogram (EKG) trace at the bottom provides temporal correlation with the cardiac cycle. This visualization demonstrates how provocative maneuvers like the Valsalva maneuver can exacerbate dynamic obstruction by decreasing preload and ventricular volume.

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venous return cardiac output preload diagram cardiovascular physiology

This pathophysiology diagram illustrates the differences in regional oxygen saturation and blood flow distribution between a normal physiological state and circulatory shock. The diagram features anatomical icons of the brain, heart, and kidney, with arrows representing venous return and mixed venous output. In the 'Normal state,' the venous return from the brain is shown with a dark blue arrow (high extraction), while the return from the kidney is pale purple (low extraction), resulting in the relationship ScvO2 < SvO2. Conversely, in the 'Shock' state, the centralization of circulation is depicted: the kidney return becomes dark blue (indicating increased extraction or decreased perfusion), and the brain return becomes pale purple, leading to the inversion ScvO2 > SvO2. The comparison highlights how circulatory failure and compensatory vasoconstriction in visceral organs alter the balance between central venous oxygen saturation (ScvO2) and mixed venous oxygen saturation (SvO2), serving as a critical indicator for monitoring tissue perfusion and cardiac output adequacy in critical care settings.

This clinical photograph displays a digital interface of an HemoSphere advanced hemodynamic monitoring system, used in intensive care settings for real-time cardiovascular assessment. The central feature is a stylized anatomical diagram of the heart and circulatory system, where color-coded vessels (blue for venous/deoxygenated and red for arterial/oxygenated) indicate blood flow patterns and pressure points. Key hemodynamic parameters are overlaid on the diagram and listed in a sidebar, including Cardiac Output (DC: 4.0 L/min), Mean Arterial Pressure (PAM: 80 mmHg), Cardiac Index (IC: 3.0 L/min/m²), and Systemic Vascular Resistance Index (RVSI: 1915 dyne-s-m²/cm³). Additional markers show Stroke Volume Variation (VPP: 28%) and Heart Rate (FP: 107 bpm). The display utilizes color-coded status indicators (green for within target range, yellow for borderline) to assist clinicians in the management of patients with cardiac dysfunction or shock, such as post-vaccination myocarditis. This visual tool integrates invasive pulse wave analysis data into an intuitive physiological map for rapid clinical decision-making.

Diagnostic cardiac MRI (magnetic resonance imaging) scan in a coronal reconstruction illustrating a case of Partial Anomalous Pulmonary Venous Return (PAPVR). The image displays the heart, aortic arch, and superior vena cava within the thoracic cavity. A red arrow highlights a specific anomalous pulmonary vein that originates from the left upper lobe of the lung. Instead of its normal physiological drainage into the left atrium, the vessel is clearly visualized coursing superiorly and medially to connect directly to the left brachiocephalic (innominate) vein. This anatomical variation represents a left-to-right cardiovascular shunt. The image serves as a clinical example of congenital pulmonary venous anomalies that can lead to right ventricular volume overload and pulmonary hypertension. Key landmarks such as the ascending aorta and the bifurcation of the pulmonary vasculature are also visible, providing spatial context for the anomalous vessel's path above the heart.

$This diagnostic imaging panel features two phase-contrast magnetic resonance imaging (PC MRI) frames used for cardiovascular flow quantification in a newborn. Image A is a sagittal view demonstrating the measurement of left ventricular output (LVO) at the level of the aortic valve. The aorta is highlighted with a red circle and labeled 'Ao,' situated at the superior aspect of the heart representing the left ventricular outflow tract. Image B is an axial (transverse) cross-section at the level of the pulmonary trunk, focused on superior vena cava (SVC) flow quantification. The SVC is traced with a red outline, revealing its characteristic crescent or asymmetric shape as it molds against the adjacent ascending aorta before entering the right atrium. These images illustrate the technical application of PC MRI in assessing neonatal hemodynamics, specifically comparing blood flow volumes in the systemic outflow (LVO) versus systemic venous return (SVC). The modality provides high-resolution anatomical landmarks and precise cross-sectional area measurements essential for calculating cardiac output and shunt fractions in pediatric cardiology.$

This diagnostic imaging panel features two phase-contrast magnetic resonance imaging (PC MRI) frames used for cardiovascular flow quantification in a newborn. Image A is a sagittal view demonstrating the measurement of left ventricular output (LVO) at the level of the aortic valve. The aorta is highlighted with a red circle and labeled 'Ao,' situated at the superior aspect of the heart representing the left ventricular outflow tract. Image B is an axial (transverse) cross-section at the level of the pulmonary trunk, focused on superior vena cava (SVC) flow quantification. The SVC is traced with a red outline, revealing its characteristic crescent or asymmetric shape as it molds against the adjacent ascending aorta before entering the right atrium. These images illustrate the technical application of PC MRI in assessing neonatal hemodynamics, specifically comparing blood flow volumes in the systemic outflow (LVO) versus systemic venous return (SVC). The modality provides high-resolution anatomical landmarks and precise cross-sectional area measurements essential for calculating cardiac output and shunt fractions in pediatric cardiology.

The video is about the Valsalva Maneuver by ASE360. I have good content and images. Let me search for more relevant clinical images and then build the image-rich PPT.

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Valsalva maneuver echocardiography LVOT obstruction HCM

This composite diagnostic image displays three distinct cases (A, B, and C) of dynamic left ventricular outflow tract obstruction (DLVOTO) evaluated through echocardiography. Each column represents a clinical scenario and includes 2D grayscale, color flow Doppler, and continuous-wave (CW) spectral Doppler imaging at both rest and during a Valsalva maneuver. Row 1 shows apical views with color Doppler demonstrating turbulent, high-velocity jets (aliasing) in the LVOT. Row 2 and 3 provide CW Doppler spectral envelopes documenting peak velocity and pressure gradients (PG). Case A illustrates classic systolic anterior motion (SAM) of the mitral valve leaflets. Case B demonstrates chordal SAM, where the chordae tendineae move toward the septum. Case C shows DLVOTO caused by prominent papillary muscles 'kissing' the interventricular septum. Across all cases, the Valsalva maneuver typically increases the peak velocity and pressure gradient, as evidenced by the taller, late-peaking 'dagger-shaped' spectral envelopes in the bottom row. These findings are diagnostic of dynamic rather than fixed obstruction, common in conditions like hypertrophic cardiomyopathy (HCM) or sigmoid septum.

This diagnostic image consists of two panels showing transthoracic echocardiography (TTE) using continuous-wave (CW) spectral Doppler across the left ventricular outflow tract (LVOT). The left panel represents the 'at rest' state, and the right panel represents the 'Valsalva' maneuver. The 2D apical view at the top shows significant concentric left ventricular hypertrophy and septal thickening. Below, the spectral Doppler waveforms display high-velocity, late-peaking systolic jets characteristic of dynamic outflow obstruction. In the 'at rest' panel, the peak velocity is measured at 701 cm/s with a corresponding peak gradient (PG) of 197 mmHg. The 'Valsalva' panel demonstrates a slightly altered waveform morphology and increased peak pressure gradient (reaching 200 mmHg), indicative of hypertrophic obstructive cardiomyopathy (HOCM) physiology. This comparison illustrates the dynamic nature of LVOT obstruction, where provocative maneuvers like the Valsalva maneuver can exacerbate pressure gradients by reducing preload. This material is designed for advanced medical education in cardiology and diagnostic imaging.

Transthoracic echocardiography series illustrating dynamic left ventricular outflow tract (LVOT) obstruction and associated mitral regurgitation (MR). Panel A shows a color Doppler apical long-axis view with a prominent mosaic, multi-colored jet originating from the LV and extending into the left atrium (LA), consistent with severe MR and systolic flow acceleration in the LVOT. Panel B demonstrates the resolution of this MR jet on follow-up imaging after intra-aortic balloon pump weaning. Panel C displays spectral Doppler tracings of the LVOT. The left tracing shows a resting state with a peak velocity (Vmax) of 1.50 m/sec and a peak pressure gradient of 8.95 mmHg. The right tracing shows a provoked state during a Valsalva maneuver, demonstrating a significant increase in obstruction with a Vmax of 3.12 m/sec and a peak pressure gradient of 38.97 mmHg. The images highlight the dynamic nature of LVOT obstruction and its relationship with secondary MR and hemodynamic maneuvers.

Searching Images

goal directed Valsalva maneuver sphygmomanometer mouthpiece technique

A composite clinical photograph illustrating experimental setups for hemodynamic monitoring. Figure (a) displays a vascular occlusion experiment on a human forearm. A blue pneumatic blood pressure cuff is positioned on the upper arm, connected to a manual bulb and mercury sphygmomanometer. Attached distal to the cuff on the forearm is a multi-channel functional Near-Infrared Spectroscopy (fNIRS) probe, secured with a tan elastic bandage. The probe features multiple black and yellow optical fiber cables for data acquisition. Figure (b) depicts a subject seated during a Valsalva maneuver experiment. The subject wears a specialized fNIRS headgear cap embedded with numerous sensor nodes and optical fibers (black and yellow) extending posteriorly. The setup is located in a controlled laboratory environment with a computer workstation. These images demonstrate procedural applications of continuous-wave fNIRS technology for monitoring peripheral and cerebral hemodynamic changes (oxy- and deoxy-hemoglobin) during physiological stress tests.

This figure illustrates dynamic changes in the global Blood Oxygen Level Dependent (BOLD) signal during a Valsalva maneuver in healthy subjects. The top panel presents three diagnostic images—sagittal, coronal, and axial fMRI sections—with blue overlays indicating that the global BOLD signal was calculated from nearly the entire brain volume, including the cerebral hemispheres, cerebellum, and brainstem. The middle plot displays the mean 'Global BOLD (% relative to baseline)' over time (0–80 seconds). It shows a biphasic response: a sharp initial decrease at the start of the maneuver, followed by an increase above baseline during the strain phase, a second drop upon release, and a subsequent recovery overshoot. The bottom plot shows the 'Expired load pressure (mmHg)', documenting the target physiological challenge of 30 mmHg maintained between approximately 18 and 38 seconds. Together, these elements demonstrate the use of global BOLD as an indirect measure of cerebral blood flow and autoregulatory responses to autonomic cardiovascular challenges.

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heart stroke volume cardiac output autonomic nervous system baroreceptor reflex

This physiological chart displays a series of eight line graphs illustrating cardiovascular responses in humans (n=11) during a 2-minute isometric handgrip exercise (40% MVC). The graphs represent Mean Arterial Pressure (MAP), Stroke Volume (SV), Heart Rate (HR), Cardiac Output (CO), Brachial Artery Blood Flow Velocity (BBFV), Acral Skin Blood Flow (ASBF), Local Peripheral Resistance (LPR), and Total Peripheral Resistance (TPR) over a 300-second timeline. Each graph compares three physiological conditions: control supine (P1, bold line), mild lower body negative pressure (LBNP -20 mmHg, P4, dotted line), and moderate LBNP (-40 mmHg, P5, hairline). Vertical dashed lines indicate the onset (approx. 50s) and cessation (approx. 200s) of the isometric contraction. Key observations include a progressive rise in MAP, HR, and TPR during the exercise phase across all conditions, with corresponding decreases in SV. The data demonstrates the interplay between central hemodynamics and peripheral vascular resistance in response to combined orthostatic stress (simulated by LBNP) and physical exertion, suitable for exercise physiology and autonomic nervous system education.

This physiological data visualization consists of six line graphs (labeled a-f) illustrating time-variant cardiovascular and hemodynamic responses during a mental arithmetic (MA) task compared to a baseline. The X-axis represents time in seconds (0-300s), divided into a 'First Stage' and a 'Late Stage'. The indexes monitored include: (a) Heart Rate (HR/bpm), (b) Systolic Blood Pressure (SBP/mmHg), (c) Diastolic Blood Pressure (DBP/mmHg), (d) Stroke Volume (SV/mL.beat⁻¹), (e) Cardiac Output (CO/L.min⁻¹), and (f) Systemic Vascular Resistance (SVR/dynes sec/cm⁵). The solid line represents the MA task, while the dotted line represents the baseline. In graphs a, b, c, and e, the MA task shows an immediate and sustained elevation compared to the baseline, characterized by an initial peak followed by a slight decrease toward a stable yet elevated plateau. Graphs d and f show higher variability and overlap between the task and baseline conditions. This chart is used to demonstrate the autonomic nervous system's dynamic reaction to mental stress, specifically illustrating acute tachycardia and increased blood pressure mediated by parasympathetic withdrawal and sympathetic modulation.

This dual-panel diagnostic image demonstrates the echocardiographic method for non-invasively estimating cardiac output (CO) by calculating stroke volume (SV). The left panel displays a pulsed-wave Doppler echocardiogram in the apical four-chamber view. It features a color Doppler inset and a spectral Doppler tracing used to measure the Left Ventricular Outflow Tract Velocity Time Integral (LVOT VTI). Clinical data shown include a VTI of 21.3 cm and a calculated stroke volume of 74 ml. The right panel shows a 2D grayscale echocardiogram in the parasternal long-axis view, used to measure the LVOT diameter (1.92 cm) and area (2.91 cm²) during systole. Together, these views provide the necessary parameters—LVOT area and VTI—to determine hemodynamic status. Key educational concepts include the application of the continuity equation and Doppler hemodynamics in assessing heart failure and volume status.

I have excellent images and full content. Now let me build the image-rich PPT. Now let me build the image-rich PPT. I'll download all images and create the deck:

Running Command

mkdir -p /tmp/workspace/valsalva-ppt && python /tmp/skills/shared/scripts/fetch_images.py \ "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_ed28c2b306579f3e18269efa60366a8fe2af7d6b111078e95ccb48b4811a3011.jpg" \ "https://cdn.orris.care/cdss_images/GLGCA_1754391_1766497288491_2bd467b0-359c-44c1-9f26-cefe878582ac_88d45410-028b-45e9-a1c2-aeb2358c0b35.png" \ "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_9a1a4e678ac95022c58e310e264cacc6279056b5c03e3b857f2f8e34edf806b7.jpg" \ "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_7b36ddb9b708af246861dc086fe84429d348c3ad4b4adbdb7da23f83f8c3dfc4.jpg" \ "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_6fc3e62c003575181ccf5e74b3b1d78ea49107a7552985c6b8ea5879fbbd41d5.jpg" \ "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_0d7d20ed4e034cea0ad7a77674356eb954a5fda292d2b8620ea70dbb5ecdfad9.jpg" \ "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_168659853a539c38bc7eb48c07f4f7908f271338d663b036066aac2da2179639.jpg" \ "https://cdn.orris.care/cdss_images/pmc_clinical_VQA_25b68541fe804b876333d82789ffebdba93cb30eadce19df39559aa3535a5269.jpg" \ 2>&1 | head -5

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