Methodological Rigor and Temporal Trends of Cardiovascular Medicine Meta‐Analyses in Highest‐Impact Journals
Bibliographic record
Abstract
Background Well‐conducted meta‐analyses are considered to be at the top of the evidence‐based hierarchy pyramid, with an expansion of these publications within the cardiovascular research arena. There are limited data evaluating the trends and quality of such publications. The objective of this study was to evaluate the methodological rigor and temporal trends of cardiovascular medicine‐related meta‐analyses published in the highest impact journals. Methods and Results Using the Medline database, we retrieved cardiovascular medicine‐related systematic reviews and meta‐analyses published in The New England Journal of Medicine, The Lancet, Journal of the American Medical Association, The British Medical Journal, Annals of Internal Medicine, Circulation, European Heart Journal, and Journal of American College of Cardiology between January 1, 2012 and December 31, 2018. Among 6406 original investigations published during the study period, meta‐analyses represented 422 (6.6%) articles, with an annual decline in the proportion of published meta‐analyses (8.7% in 2012 versus 4.6% in 2018, P trend =0.002). A substantial number of studies failed to incorporate elements of Preferred Reporting Items for Systematic Reviews and Meta‐Analyses or Meta‐Analysis of Observational Studies in Epidemiology guidelines (51.9%) and only a minority of studies (10.4%) were registered in PROSPERO (International Prospective Register of Systematic Reviews). Fewer manuscripts failed to incorporate the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses or Meta‐Analysis of Observational Studies in Epidemiology elements over time (60.2% in 2012 versus 40.0% in 2018, P trend <0.001) whereas the number of meta‐analyses registered at PROSPERO has increased (2.4% in 2013 versus 17.5% in 2018, P trend <0.001). Conclusions The proportion of cardiovascular medicine‐related meta‐analyses published in the highest impact journals has declined over time. Although there is an increasing trend in compliance with quality‐based guidelines, the overall compliance remains low.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.496 | 0.811 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.023 |
| Bibliometrics | 0.039 | 0.051 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".