2131Pragmatic clinical trials in cardiovascular medicine: trends over time in major medical journals
Bibliographic record
Abstract
Abstract Background Pragmatic trials provide results that may be more applicable to the population in which the intervention will be eventually applied and are discussed extensively in the current healthcare environment. The aim of this study was to investigate how pragmatic or explanatory cardiovascular (CV) randomized controlled trials (RCT) are, if this was changing over time, and if they were more or less likely to meet their primary endpoint. Methods Using the six top-ranked (based on impact factors) medical and CV journals, all CV-related RCTs that were published during the years of 2000, 2005, 2010 and 2015 were identified, data extracted and reviewed by 2 adjudicators. The PRECIS-2 tool was used to evaluate the level of pragmatism. PRECIS-2 uses a 5-point ordinal scale (ranging from very pragmatic to very explanatory) across 9 domains of trial design, including eligibility, recruitment, setting, organization, intervention delivery, intervention adherence, follow-up, primary outcome, and analysis. A higher score indicates a more pragmatic score on an individual domain, and aggregated scores are a simplified formula across all domains. Cohen's D was used to quantify the mean difference relative to the variation. Results There were 616 RCTs, distributed evenly over the 2 decades, and 64% achieved their primary endpoint. The mean (±SD) PRECIS-2 score was 3.26±0.70 among 616 included RCTs. The level of pragmatism increased over time from a score of 3.07±0.74 in 2000 to 3.47±0.67 in 2015 (p<0.0001 for trend; Cohen's D relative effect size 0.57). The increase in pragmatism occurred mainly in the domains of eligibility, setting, intervention delivery, and primary endpoint (Figure). PRECIS-2 score was higher for neutral trials than those with positive results (p=0.0015) and in phase III/IV trials as compared to phase I/II trials (p<0.0001) (Figure). Furthermore, trials that involve more sites, with larger sample sizes, longer follow-ups, and those with mortality as the primary endpoint were found to be more pragmatic. There was no difference in the level of pragmatism between different sources of funding (public, industry, or both; p=0.52). Study characteristics and pragmatism Conclusion The PRECIS-2 tool can be used for appraising trials to assess their placement in the pragmatic-explanatory continuum. The level of pragmatism increased over time in CV trials. Greater focus on the design and delivery of CV trials will be required for the broad application. Acknowledgement/Funding Dr. Sepehrvand receives scholarship from Alberta Innovates Health Solutions.
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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 | 0.185 | 0.607 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.032 | 0.053 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".