Convert clinical case data (medical records, IO sheets, lab data, imaging) into a professional, timeline-based PowerPoint presentation (PPTX) and interactive HTML website for M&M conference, case report, or morning conference presentation.
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Convert clinical case data (medical records, IO sheets, lab data, imaging) into a professional, timeline-based PowerPoint presentation (PPTX) and interactive HTML website for M&M conference, case report, or morning conference presentation.
allowed-tools
Bash, Read, Write, Glob, Grep
Case Report Presentation
Overview
When a user provides clinical case data and asks for a case report / M&M / morning conference presentation, use this skill to generate a timeline-based python-pptx presentation and an interactive HTML website. The input is typically a folder containing:
Markdown medical records (醫師記錄/): Admission note, Progress notes, Discharge note, Surgical records, Objective findings
IO sheets (IO/): PNG screenshots of fluid intake/output records by shift
Lab data images (LABS/): PNG screenshots of lab trend charts (CBC, SMAC, CRP, etc.)
Chest X-rays / imaging (CXR/): PNG images with date-based filenames
Nursing records (護理紀錄/): PDF files
Medication records: PDF files at root level
The slide structure should be timeline-based — organized chronologically around the clinical course, with adaptive granularity (finer detail for the main focus period, coarser for secondary periods).
Prerequisites
pip3 install python-pptx pymupdf
Workflow
0a. Ask for Presenter Information & Presentation Type
Before starting, ask the user two things in a concise one-liner:
Presenter info: Who is presenting and who is the supervisor? (e.g., "R2 王大明 / VS 李教授") — press Enter to skip.
Structure into tables for the fluid resuscitation slides (Pattern G)
If OCR is needed for hard-to-read values, use the macOS Vision OCR script from the notebooklm-to-editable-pptx skill
Lab data strategy
Primary source:Objective finding.md — already has parsed, structured lab values by date
Lab images (PNG): Use as visual verification and can be embedded as supplementary reference
DO NOT recreate charts — use the structured data to build formatted tables
Medication records (PDF — 急診用藥紀錄, 住院後用藥簽用記錄)
Extract using PyMuPDF (fitz.open()). Key data to parse:
IV fluids: LR, NS, D5W — with execution times (not order times). Multiple execution records under the same order number may represent either separate bags or multi-nurse sign-offs — cross-reference with nursing records to disambiguate.
Blood products: FFP, FP, RBC — doses and execution times
Antibiotics: Drug name, dose, frequency, start/stop dates, route
CRITICAL: Use execution timestamps (執行時間), not order timestamps (開立時間), for fluid volume calculations. The same order number with multiple execution records may be the same bag signed by different nurses — verify with nursing records and IO sheets.
CXR and imaging
Copy all CXR images to figures/ directory with date-based filenames
These will be used in serial comparison slides (Pattern I)
Label by actual imaging location — check PACS header (institution name) in the image. Do NOT assume the first CXR is from an outside hospital.
Wound / clinical photos
Check for existing PPTX files (e.g., trauma team presentations) that may contain clinical photos
Extract images via shape.image.blob from python-pptx
Resize large images (>3MB) using sips -Z 2000 -s format jpeg -s formatOptions 80 before embedding in PPTX
2. Build Clinical Timeline
Construct a chronological timeline from all parsed data. The timeline granularity should be adaptive:
Timeline structure (acute/critical care default):
├── Pre-hospital: mechanism, rescue, initial hospital management
├── ED / Arrival (Hour 0): vital signs, primary survey, initial labs
├── Hour 0–8: resuscitation phase 1 (MAIN FOCUS — finest granularity)
├── Hour 8–24: resuscitation phase 2 (MAIN FOCUS)
├── Day 2–3: early ICU course
├── Day 4–7: continued course
└── Day 7+: later course / outcome
Fluid balance: intake by category, output (UOP), cumulative balance
Medications: new starts, dose changes
3. Design Slides Based on Clinical Timeline
3.5. Text Formatting Rules (CRITICAL)
Same rules as journal-reading skill — apply to ALL python-pptx text:
Never use p.text = "..."
Always use set_run() or p.add_run(). The p.text = pattern does not guarantee formatting.
Never use \n in text strings
Each line must be a separate paragraph with its own run and explicit formatting.
Every text element must have explicit formatting
Every run must set: font.size, font.color.rgb, font.name. Never rely on defaults.
Every paragraph must have explicit alignment (CRITICAL)
Always set p.alignment = PP_ALIGN.LEFT (or CENTER/RIGHT) on every paragraph. Never rely on PowerPoint defaults — they are inconsistent across text boxes, tables, and shapes. Without explicit alignment, text may render LEFT in some boxes and CENTER in others.
# CORRECT — explicit alignment on every paragraph
p = tf.paragraphs[0]
p.alignment = PP_ALIGN.LEFT # ← MUST SET
set_run(p, "text", font_size, color)
# WRONG — missing alignment → inconsistent rendering
p = tf.paragraphs[0]
set_run(p, "text", font_size, color) # ← alignment undefined
Vital signs cards, table headers, table data (non-first-column):PP_ALIGN.CENTER
Slide numbers:PP_ALIGN.RIGHT
Title/ending slide (Thank You):PP_ALIGN.CENTER
Content slide titles:PP_ALIGN.LEFT
Prevent text overlap between elements (CRITICAL)
When a slide has multiple vertically stacked elements (bullets + key_point box, timeline + bullets, etc.), calculate the available vertical space before adding content. If content exceeds the space, either:
Split into two slides — preferred for dense content
Reduce font size — minimum Pt(12) for readability
Move the emphasis box lower — but never below top=Inches(6.2) (slide numbers at 7.05)
Rule of thumb for vertical spacing:
Mini-timeline occupies y=0.92 to y=1.75 (~0.83 inches)
Content area after timeline: top=Inches(1.85) to top=Inches(5.5) max
Key_point/highlight box: calculate top = bullets_top + (n_lines × line_height)
Never stack more than 12–14 bullet lines + 1 emphasis box on a single slide
4. Slide Structure
Do NOT force a fixed slide count. Use as many slides as needed. Prefer more slides with less content each over fewer dense slides.
Layout density principles:
Max 4–5 bullet points per slide
Max 1 table + 1–2 figures per slide
Font sizes for projection: body text ≥ Pt(18), titles ≥ Pt(28), table cells ≥ Pt(14), captions ≥ Pt(12)
Leave breathing room — generous padding, whitespace between elements
Required slides (always present):
Title slide — Case type label (M&M / Case Report / Morning Conference), chief complaint as title, patient demographics summary, presenter info
Outline slide — Numbered TOC matching subsequent sections. Use uniform 0.5"×0.5" rounded-square badges (not circles) so 2-digit numbers fit. Badge font: 16pt for 1-digit, 13pt for 2-digit, bold white, vertically + horizontally centered, word_wrap=False, zero margins. Row step 0.6", label font 18pt vertically aligned with badge center. (Implemented in add_outline_slide() in generate_aesthetic_pptx.py.)
Patient Profile — Demographics, comorbidities, baseline functional status, social history
Mechanism / Presentation — How the injury/illness occurred, pre-hospital care, include outside hospital fluids/medications with execution times
Initial Assessment — Arrival vitals (Pattern K cards), primary/secondary survey
Injury/Disease Assessment — e.g., TBSA by region (Pattern J) for burns, staging for cancer
Wound / Injury Photos — Clinical photos from ER and procedures (Pattern I). Source from existing PPTX (add_picture extraction) or image folder. Always include if available.
Initial Labs — Key lab results in table (Pattern H) with abnormal highlighting
Initial Imaging — CXR/CT with interpretation. Label by actual source (e.g., "ER Arrival" if taken at receiving hospital, not "Outside Hospital")
Treatment Focus slides — Detailed slides on the main focus area (e.g., fluid resuscitation for burns). Use PBD (Post-Burn Day) or post-event timeline, not calendar dates, for time reference
Daily Course slides (PBD-based) — Each slide MUST include: Weight (with Δ), Labs, IO balance, Rx (daily management), Abx (antibiotics), Vitals from nursing records. Add a mini-timeline indicator (Pattern L) on each slide
Lab Trends — Serial lab tables (Pattern H) grouped by system (Renal, Hematology, Inflammatory)
Serial Imaging — Side-by-side comparison (Pattern I)
Complications — Summary of complications encountered
Outcome — Final status, contributing factors
Learning Points / Discussion / Summary — Based on presentation type selected in step 0a
Ending slide — "Thank You — Questions?" with presenter info
Supplementary slides (after Thank You) — Individual CXR with radiology reports, IO screenshots, SMAC/CBC/CRP screenshots, blood sugar. Marked with "SUPPLEMENTARY" tag and gray accent bar
Case-specific slide templates:
For burns / fluid resuscitation:
Weight: Use pre-burn weight from op note (not admission weight which includes pre-hospital fluids). Flag the discrepancy explicitly.
TBSA: Report both ED assessment and post-op reassessment if different.
Parkland formula: Calculate from burn time (not hospital admission). Account for late presentation — if first 8h window passed, note explicitly. Show mL/kg/%TBSA actual vs expected (4 mL).
PBD-based fluid slides: Break down by Phase (outside hospital → ER → BU shifts). Show fluid type detail (LR, NS, NaHCO₃, Albumin, blood products) with execution times from 急診用藥紀錄/住院後用藥簽用記錄.
UOP tracking: Calculate mL/kg/hr using pre-burn weight per PBD phase. Red-highlight when below target.
Outside hospital fluids: Include in PBD1 total. Note Foley bladder drainage vs sustained UOP.
Wound/escharotomy photos: Extract from existing PPTX if available (e.g., trauma team PPTX). Use slide.shapes → shape.image.blob to export images.
Weight trend: Daily weights with Δ from baseline and % change.
For surgical complications:
Pre-operative assessment slide
Intra-operative events timeline
Post-operative complication timeline
For infection / sepsis:
Antibiotic timeline per PBD — show ER empiric → BU definitive → changes
Culture results with sensitivity data
Inflammatory marker trends (CRP, PCT, WBC)
Slide Layout Patterns (16:9, coordinates in Inches)
Reuse patterns A–E from journal-reading skill, plus these new patterns:
Daily course slides — use add_pbd_timeline_header(slide, days, current_idx); current day highlighted, past blue, future gray. Container width is mandatory so first/last day labels never overflow.
Emphasis Box Policy
Same as journal-reading:
add_key_point() — deep blue box, white text — for KEY FINDING, most important takeaway
Default font: 14pt, left-aligned (both helpers). Override font_size= only when a slide truly needs larger emphasis. Never use centered alignment for multi-line summary text.
5. Generate the PPTX
Write a self-contained Python script to /tmp/create_case_report.py that inlines all helper functions from both:
