Sex/Gender Disparities in Randomized Controlled Trials of Statins: The Impact of Awareness Efforts
Bibliographic record
Abstract
PURPOSE: Studies have demonstrated gender differences in the burden of cardiovascular outcomes for patients with dyslipidemia. Progress in identification of the sex/gender composition in Randomized Controlled Trials (RCTs) is crucial for understanding the distribution of therapeutics effectiveness in the population according to sex/gender. The purpose of this study was to investigate the evolving pattern of sex/gender disparity in participants of RCTs on statins between 1990 and 2010. A secondary objective was to evaluate changes in the pattern of the average age of participants of RCTs on statins between 1990 and 2010. METHODS: This review focused on RCTs on statins that reported participants' numbers by sex/gender. Studies were identified from an initial PubMed search using several combinations of MeSH terms. The search was limited to the RCTs on adults in English-language publications. The dates for search were set between January 1, 1990 and December 31, 2010. RESULTS: In the 1990s, RCTs on statins with an average of more than 500 participants included 18.6% women [95% Confidence Interval (95% C.I.): 16.31%, 21.13%]. By the first decade of the 2000s, women comprised, on average, 31.45% [29.45%, 32.52% (95% C.I.)] of the total cohort of RCTs with more than 500 participants. Regression analysis illustrated a significant increase in the recruitment of women for RCTs of statins (p-value < 0.01). Furthermore, analysis of the average age of participants illustrated a significant trend (p-value = 0.03) towards an increase in the average age of the participants in RCTs on statin between 1990 and 2010: the average age of participants in the 1990s was 58 years [56, 60 (95% C.I.)] and in the 2000s it was 62 years [56, 60 (95% C.I.)]. CONCLUSION: This study demonstrates significant progress in the inclusion of women in RCTs on statins. This finding reflects the efforts of different agencies and groups to increase the representation of women in clinical trials.
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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 | 0.431 | 0.689 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.013 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".