| name | systematic-review |
| description | Orchestrates a systematic review and meta-analysis workflow following PRISMA 2020 guidelines, from protocol development through multi-database search, screening, data extraction, and evidence synthesis. Use when conducting evidence-based reviews, meta-analyses, or scoping revi... |
| license | MIT |
| author | AIPOCH |
Source: https://github.com/aipoch/medical-research-skills
Systematic Review (Meta Skill)
This meta-skill coordinates a complete systematic review pipeline following
PRISMA 2020 guidelines. It integrates multi-database literature searching,
structured screening, information extraction, quantitative synthesis, and
standardized reporting into a rigorous evidence review workflow by combining
three specialized skills.
Workflow
Step 1: Protocol Development
Define the review protocol before conducting any searches:
- Formulate the research question using the PICO framework
(Population, Intervention, Comparator, Outcome)
- Establish inclusion and exclusion criteria with explicit justification
- Define the search strategy: databases, date range, language restrictions
- Specify outcome measures and effect size metrics
- Pre-register the protocol (PROSPERO or OSF recommended)
- Document any planned sensitivity or subgroup analyses
Step 2: Multi-Database Systematic Search
Execute comprehensive searches across multiple bibliographic databases:
- PubMed/MEDLINE: Biomedical and clinical literature via structured MeSH queries
- arXiv: Preprints in quantitative and computational fields
- Semantic Scholar: AI-augmented citation graph and full-text search
- CrossRef: DOI-based metadata and cross-publisher discovery
- Construct database-specific search strings from the master strategy
- Document exact queries, dates, result counts; deduplicate exports
- Supplement with citation chaining (forward and backward) on key papers
Step 3: Screening and Eligibility Assessment
Apply a two-stage screening process to identify eligible studies:
- Title/abstract screening: Apply inclusion criteria, flag uncertain cases
- Full-text assessment: Evaluate against all criteria, document exclusion reasons
- Track inter-rater agreement (Cohen's kappa) if multiple reviewers
- Maintain a log of all screening decisions for the PRISMA flow diagram
- Resolve disagreements through discussion or third-reviewer arbitration
Step 4: Structured Data Extraction
Extract pre-defined data elements from each included study:
- Study characteristics: design, setting, sample size, follow-up duration
- Population, intervention, comparator: demographics, dosage, duration
- Outcomes and results: endpoints, effect estimates, confidence intervals
- Quality indicators: randomization method, blinding, attrition, funding
Use ScienceClaw information extraction to assist with structured data capture
from PDF full texts, reducing manual effort and transcription errors.
Step 5: Risk of Bias and Quality Assessment
Evaluate methodological quality of each included study:
- Apply appropriate tools (RoB 2 for RCTs, ROBINS-I for non-randomized, Newcastle-Ottawa)
- Assess each domain: selection, performance, detection, attrition, reporting
- Generate risk-of-bias summary figures (traffic light plots)
- Evaluate overall certainty of evidence using GRADE framework
- Document judgments with supporting quotations from study texts
Step 6: Meta-Analysis and Evidence Synthesis
Perform quantitative synthesis when studies are sufficiently homogeneous:
- Calculate standardized effect sizes (SMD, OR, RR, HR as appropriate)
- Fit random-effects or fixed-effects meta-analysis models
- Generate forest plots with study-level and pooled estimates
- Assess heterogeneity: I-squared statistic, Cochran's Q test, tau-squared
- Subgroup and sensitivity analyses: leave-one-out, trim-and-fill, funnel plots
Step 7: PRISMA Reporting and Final Output
Compile the review following PRISMA 2020 reporting standards:
- PRISMA flow diagram with identification, screening, eligibility, inclusion counts
- Characteristics of included studies table
- Risk-of-bias summary and individual study assessments
- Forest plots, funnel plots, and subgroup analysis figures
- Summary of findings table with GRADE certainty ratings
- Complete PRISMA 2020 checklist (Page et al., BMJ 2021;372:n71) cross-referenced
to report sections
Integration Points
- literature-search -- Multi-database querying, deduplication, citation chaining, export
- scienceclaw-ie -- Structured data extraction from PDFs, entity recognition, table parsing
- paper-writing -- PRISMA-compliant report generation, figure formatting, reference management
Output Formats
- PRISMA flow diagram: Study counts at each screening stage with exclusion reasons
- Study characteristics table: Design, population, intervention, outcomes per study
- Forest plot: Effect sizes with CIs, weights, pooled estimate, heterogeneity stats
- Risk-of-bias table: Domain-level judgments per study with traffic light visualization
- Summary of findings: GRADE-rated evidence table for each outcome
- Full report: PRISMA 2020 compliant manuscript with all required sections
PRISMA 2020 Checklist Reference
This workflow aligns with the PRISMA 2020 statement (Page et al., BMJ
2021;372:n71). The 27-item checklist spans title through other information,
and each workflow step maps to specific checklist items to ensure completeness.
Best Practices
- Register the protocol before beginning searches to reduce reporting bias
- Use at least two independent reviewers for screening and extraction
- Document every decision point for full transparency and reproducibility
- Never modify inclusion criteria after seeing search results without justification
- Report all pre-planned analyses regardless of statistical significance
- Use GRADE to rate certainty of evidence for each outcome separately
- Clearly distinguish direct evidence from indirect comparisons
- Acknowledge limitations in study-level quality and review-level methodology
- Update the review when substantial new evidence becomes available
- Make extracted data and analysis code publicly available when possible
Input Validation
This skill accepts requests that match the documented purpose of systematic-review and include enough context to complete the workflow safely.
Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:
systematic-review only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
