meta-manuscript-assembly（元手稿组装）

Meta-Analysis Manuscript Assembly

Complete systematic review and meta-analysis manuscripts for journal submission by creating publication-ready tables, figures, and references.

When to Use

• Completing meta-analysis manuscript after analyses are done
• Creating tables from meta-analysis results
• Assembling multi-panel figures from forest/funnel plots
• Generating BibTeX references for systematic reviews
• Formatting manuscripts for high-impact journals (Lancet, JAMA, NEJM)

Prerequisites

Before using this skill, ensure you have:

• Completed meta-analyses with results tables (CSV format)
• Generated individual figures (PNG at 300 DPI)
• Manuscript text sections written (Abstract, Introduction, Methods, Results, Discussion)
• List of all citations needed

Workflow

Phase 1: Tables Creation

Create comprehensive tables from analysis results:

Main Text Tables

1. Table 1: Trial Characteristics

- Extract from extraction.csv or similar - Include: NCT number, first author, year, design, sample sizes, intervention details, follow-up - Format as markdown with abbreviations section

1. Table 2: Efficacy Outcomes Summary

- Combine results from all meta-analyses (pCR, survival outcomes) - Include: effect estimates, 95% CI, p-values, I², absolute benefits, NNT - Add GRADE certainty ratings

1. Table 3: Safety Outcomes Summary

- From safety meta-analysis results - Include: adverse events, rates, RR/OR, NNH - Add clinical management guidance

Supplementary Tables

1. Risk of Bias Assessment

- Use RoB 2 or ROBINS-I tool format - Domain-by-domain assessment for each trial - Overall risk rating with justifications

1. GRADE Evidence Profile

- Summary of Findings table format - All outcomes with certainty ratings - Domain-specific justifications (bias, inconsistency, indirectness, imprecision)

1. Detailed Results Tables

- Individual trial results - Subgroup analyses - Sensitivity analyses

Phase 2: Figure Assembly

Create multi-panel publication-ready figures:

Tool: Python Script with PIL/Pillow

# Create assemble_figures.py
from PIL import Image, ImageDraw, ImageFont
from pathlib import Path

def add_panel_label(img, label, position='top-left', font_size=80, offset=(40, 40)):
    """Add A, B, C labels to panels"""
    draw = ImageDraw.Draw(img)

    # Try to use system font
    try:
        font = ImageFont.truetype("/System/Library/Fonts/Helvetica.ttc", font_size)
    except:
        font = ImageFont.load_default()

    x, y = offset

    # Draw white background box for visibility
    bbox = draw.textbbox((x, y), label, font=font)
    padding = 10
    draw.rectangle(
        [bbox[0] - padding, bbox[1] - padding,
         bbox[2] + padding, bbox[3] + padding],
        fill='white',
        outline='black',
        width=2
    )

    draw.text((x, y), label, fill='black', font=font)
    return img

def create_multi_panel_figure(images_list, output_path, labels=['A', 'B', 'C'], spacing=40):
    """Combine multiple images vertically with labels"""
    # Add labels to images
    labeled_images = [add_panel_label(img, label) for img, label in zip(images_list, labels)]

    # Calculate dimensions
    max_width = max(img.width for img in labeled_images)
    total_height = sum(img.height for img in labeled_images) + spacing * (len(labeled_images) - 1)

    # Create combined image
    combined = Image.new('RGB', (max_width, total_height), 'white')

    # Paste images
    y_offset = 0
    for img in labeled_images:
        combined.paste(img, (0, y_offset))
        y_offset += img.height + spacing

    # Save at 300 DPI
    combined.save(output_path, dpi=(300, 300))
    return output_path

Typical Figure Structure

Main Text:

• Figure 1: Multi-panel efficacy (pCR, EFS, OS forest plots)
• Figure 2: Subgroup analysis (e.g., by biomarker status)
• Figure 3: Safety + Publication bias (SAE forest plot, funnel plot)

Supplementary:

• Supp Figure 1: Sensitivity analyses (leave-one-out plots)
• Supp Figure 2: Publication bias (funnel plots for all outcomes)

Phase 3: References Management

Create comprehensive BibTeX file:

Steps:

1. Extract all citations from manuscript using grep grep -E "¹|²|³|⁴|⁵|⁶|⁷|⁸|⁹|⁰|\[\d+\]" manuscript_sections.md
2. Create BibTeX entries for each reference

- Include DOI for all entries - Use standardized journal abbreviations (Index Medicus) - Format author names correctly

1. Create mapping document

- Map superscripts (¹, ², ³) to BibTeX keys - Document citation locations in manuscript

1. Create usage guide

- Pandoc conversion instructions - Zotero import instructions - Manual formatting examples (Lancet, JAMA style)

Phase 4: Figure Legends

Write comprehensive legends for all figures:

Legend Structure:

**Panel A. Outcome Name**
Description of what the panel shows. Forest plot showing [effect measure] for [outcome]
across [N] trials ([total participants]). [Statistical method used]. [Key result].
Horizontal lines represent 95% confidence intervals; diamond represents pooled effect.
Vertical line at [null value] indicates no treatment effect.

**Abbreviations**: List all abbreviations used.

Include:

• Statistical methods (random-effects, Hartung-Knapp adjustment)
• Heterogeneity measures (I², Cochran's Q)
• Clinical interpretations
• Abbreviations definitions

Phase 5: Quality Assurance

Before submission, verify:

Tables

• All data matches analysis results exactly
• Abbreviations defined
• Footnotes explain all symbols
• Column/row headers clear
• Statistical notation consistent

Figures

• All figures at 300 DPI minimum
• Panel labels (A, B, C) visible and not obscuring data
• Legends match figures exactly
• Font sizes readable (≥8pt for final print size)
• Color schemes work in grayscale

References

• All citations have corresponding references
• Reference numbers sequential
• DOIs correct and working
• Journal abbreviations standardized
• Author names match original publications

Output Structure

07_manuscript/
├── tables/
│   ├── Table1_Trial_Characteristics.md
│   ├── Table2_Efficacy_Summary.md
│   ├── Table3_Safety_Summary.md
│   ├── SupplementaryTable1_RiskOfBias.md
│   ├── SupplementaryTable2_GRADE_Profile.md
│   └── ...
├── figures/
│   ├── Figure1_Efficacy.png (300 DPI)
│   ├── Figure2_Subgroup.png (300 DPI)
│   ├── Figure3_Safety.png (300 DPI)
│   ├── SupplementaryFigure1_Sensitivity.png
│   └── ...
├── references.bib
├── FIGURE_LEGENDS.md
├── CITATION_MAPPING.md
└── REFERENCES_USAGE_GUIDE.md

Time Estimates

• Tables creation: 2-3 hours
• Figure assembly: 1-2 hours
• References: 1-2 hours
• Legends: 1 hour
• QA: 1 hour
• Total: 6-9 hours

Journal-Specific Formatting

Lancet Oncology

• Word limit: 4000-5000 words
• Tables: 3-4 main text, unlimited supplementary
• Figures: 3-4 main text, unlimited supplementary
• References: Vancouver style, 30-40 typical
• Resolution: 300 DPI minimum

JAMA

• Word limit: 3500 words
• Tables: 4 max
• Figures: 4 max
• References: 40 max
• Resolution: 300-600 DPI

New England Journal of Medicine

• Word limit: 3000 words
• Tables: 3 max
• Figures: 3 max
• References: 40 max
• Resolution: 300 DPI minimum

Common Pitfalls to Avoid

1. Tables: Don't mix effect measures (RR vs OR vs HR) without clear labeling
2. Figures: Don't compress below 300 DPI
3. References: Don't use auto-generated citations without verification
4. Legends: Don't omit statistical methods or abbreviations
5. Overall: Don't submit without independent verification of all numbers

Related Skills

• /meta-analysis - Perform the statistical analyses
• /prisma-flow - Create PRISMA flow diagram
• /grade-assessment - Complete GRADE evidence profiles
• /risk-of-bias - Assess trial quality with RoB 2 tool

Example Invocation

/meta-manuscript-assembly

Or with specific phase:

/meta-manuscript-assembly tables
/meta-manuscript-assembly figures
/meta-manuscript-assembly references

Success Criteria

• ✅ All tables publication-ready with comprehensive notes
• ✅ All figures 300 DPI with professional panel labels
• ✅ Complete BibTeX file with all 30-40 references
• ✅ Comprehensive figure legends
• ✅ All numbers verified against original analyses
• ✅ Manuscript follows target journal guidelines
• ✅ Ready for co-author review and submission