The short version
Coventra is a systematic-review workspace for research teams that need one place to manage studies, screen records, extract data from PDFs, run evidence synthesis, assess quality, collaborate, and export publication-ready materials.
It is built around a human-review model. Coventra can organize work, surface suggestions, enforce access rules, preserve provenance, run supported statistical workflows, and generate reproducible outputs, but researchers remain responsible for decisions, interpretation, and manuscript conclusions.
Core functions
- Project setup: create a review project, track protocol checklist items, define project metadata, configure analysis settings, and organize studies.
- Search and import: search external bibliographic sources, import selected records, bring in RIS files, look up DOI metadata, and record search history for reporting.
- Screening: run title/abstract and full-text screening, assign reviewers, use blind mode, collect include/exclude/maybe decisions, resolve conflicts, and export screening/reporting artifacts.
- Extraction: upload or fetch open-access PDFs, view evidence in the browser, extract baseline, outcome, and study-design fields, keep source quotes/pages, and preserve field-level provenance.
- Analysis: run supported pairwise, single-arm, network, Bayesian, survival, diagnostic test accuracy, diagnostic, subgroup, sensitivity, and publication-bias workflows with saved settings and reviewable outputs.
- Quality review: use generic risk-of-bias and quality-assessment workflows, record assessments, resolve conflicts, and generate supported plots or summaries.
- Collaboration: invite full-project collaborators or screening-only reviewers, assign work, comment on screening decisions, review unresolved comments, and track activity.
- Exports: generate data exports, manuscript-support tables, PRISMA/reporting files, analysis materials, reproducibility packages, RIS/BibTeX, and audit-oriented outputs.
Advanced analysis scope
Coventra's analysis workspace is intended for systematic reviews and evidence synthesis rather than a single forest-plot workflow. The app connects extracted data to method-aware analysis pages so basic users can run standard models while advanced users can inspect settings, assumptions, diagnostics, and reproducibility material.
Availability depends on project configuration, extracted data, plan access, and whether the analysis family has enough data to run.
- Pairwise meta-analysis: binary, continuous, generic inverse-variance, time-to-event, forest plots, leave-one-out and cumulative sensitivity, subgroup analysis, meta-regression, funnel/small-study views, prediction intervals, sparse-data controls, and saved runs.
- Single-arm analysis: pooled proportions, rates, and raw means with natural-scale summaries, heterogeneity, prediction intervals, funnel/sensitivity outputs where appropriate, and method transparency for transformations and GLMM settings.
- Network meta-analysis: contrast-based and arm-level binary workflows where eligible, network graph, model estimates, rankings/P-scores, rankogram where supported, forest plot, league table, comparison-adjusted funnel plot, netsplit/netheat where loops exist, and confidence-oriented diagnostics.
- Bayesian analysis: Bayesian pairwise random-effects models with explicit priors, posterior summaries, prior-sensitivity checks, and structured diagnostics; supported Bayesian network workflows are project- and data-dependent.
- Specialized analyses: survival HR synthesis, diagnostic test accuracy using TP/FP/TN/FN inputs, median-reported outcome support where available, and generic adjusted/design-specific estimates when users supply defensible pre-adjusted inputs.
Advanced analysis support does not remove the need for statistical review. Complex designs, sparse data, adjusted estimates, IPD-derived inputs, and network assumptions should be checked by qualified reviewers before publication.
What Coventra does not do
- It does not make include/exclude decisions for reviewers.
- It does not guarantee that PDF extraction or AI suggestions are correct.
- It does not replace a statistician, methodologist, or content expert.
- It does not bundle proprietary RoB1/RoB2, ROBINS, QUADAS, JBI, or AXIS wording.
- It is not a clinical decision tool and should not be used as the only basis for clinical recommendations.
Always verify extracted values, statistical settings, model assumptions, and final exports before submission or clinical use.
Recommended end-to-end workflow
- Create a project and record the review question, protocol details, planned outcomes, and basic analysis configuration.
- Search or import studies, then deduplicate and organize the records before starting screening.
- Invite reviewers, configure screening settings, assign records, and run title/abstract screening.
- Resolve title/abstract conflicts, move eligible records to full-text review, then repeat decisions and conflict resolution.
- Upload or fetch PDFs for included/eligible studies and extract baseline, study-characteristic, and outcome data with source evidence.
- Run validation checks and freeze data when the extraction set is ready for final analysis.
- Run the appropriate analysis model, inspect figures and diagnostics, and document settings.
- Complete quality/GRADE work where applicable, then export manuscript tables, PRISMA/reporting files, data files, and reproducibility artifacts.