Participation of Women in Cardiovascular Trials From 2017 to 2023
Bibliographic record
Abstract
Importance: Cardiovascular (CV) disease is the leading cause of death globally for both men and women, yet women remain historically underrepresented in CV clinical trials, despite facing a disproportionately high burden of morbidity and mortality in many forms of CV disease. Objective: To determine the representation of women across a broad range of CV trials. Evidence Review: The participation of women in CV trials registered on ClinicalTrials.gov from 2017 to 2023 was systematically determined through the extraction of publicly available information. Data were extracted to identify the country of study, disease type, trial size, clinical intervention, and age of the participants. The proportion of women and the ratio of number of female to male participants (F:M ratio) were calculated for each trial. The women's participation:prevalence ratio (PPR) was estimated for each trial based on the relative prevalence of the disease by sex in the specified region. Findings: A total of 1079 registered CV trials were identified, including 1 396 104 participants, of whom 571 641 (41.0%) were women. The F:M ratio was significantly lower for studies on arrhythmia (median [IQR], 0.5), coronary heart disease (median [IQR], 0.39 [0.33-0.70]), acute coronary syndrome (median [IQR], 0.32 [0.24-0.51]), and heart failure (median [IQR], 0.51 [0.32-0.87]) but higher for obesity (median [IQR], 1.44 [1.08-4.50]) and pulmonary hypertension (median [IQR], 2.86 [1.50-3.97]) trials. The F:M ratio was higher for trials on lifestyle interventions (median [IQR], 1.51 [0.77-3.24]) than for drug trials. PPRs were low for clinical trials on coronary heart disease (median [IQR], 0.66 [0.50-0.86]), acute coronary syndrome (median [IQR], 0.79 [0.51-0.87]), and stroke (median [IQR], 0.74 [0.61-0.95]). Representation of women in CV trials varied by disease state, region, intervention, and sponsor type. Conclusions and Relevance: These findings highlight both progress and persistent challenges in representation of women within CV trials. These gaps not only limit the generalizability of trial outcomes but also perpetuate inequities in evidence-based care for women with CV conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".