Sex Disparities in Intracranial Aneurysm Trial Participation: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: Females have a higher incidence of aneurysmal subarachnoid hemorrhage and a higher prevalence and rupture risk of unruptured intracranial aneurysms than men. Underrepresentation of females in clinical trials would, therefore, limit their generalizability. The study aimed to evaluate sex disparities in aneurysmal subarachnoid hemorrhage and unruptured intracranial aneurysm trial enrollment and identify factors influencing female representation. METHODS: The authors searched Ovid Medline, Embase, Cochrane Central, Clinicaltrials.gov , and International Clinical Trials Registry for clinical trials on aneurysmal subarachnoid hemorrhage or unruptured intracranial aneurysms, published before June 2023, with ≥100 adult patients, requiring informed consent for participation. The primary outcome was the proportion of female patients enrolled. Random effects meta-analysis was performed, and multivariate beta-regression was used to assess the impact of trial characteristics and predefined subgroups on female participation. RESULTS: A total of 134 trials were included, with a total of 38,042 patients. Meta-analysis of the proportions of female participants resulted in a pooled proportion of 0.64 (95% CI: 0.63-0.66). Female participation was higher in trials on endovascular treatment (beta-estimate 1.32; 95% CI: 1.01-1.71) and in multicenter studies (beta-estimate 1.16; 95% CI: 1.01-1.33) but lower in Asian (beta-estimate 0.80; 95% CI: 0.67-0.95) and South American trials (beta-estimate 0.67; 95% CI: 0.47-0.97). Recruitment and consent procedures, sex of primary investigator, or burden of trial participation had no significant impact on female representation. Time trend analysis showed no statistically significant change in female participation over time. CONCLUSION: Females are not underrepresented in clinical trials for aneurysmal subarachnoid hemorrhage and unruptured intracranial aneurysms. Female participation is higher in trials on endovascular treatment and in multicenter studies and has regional differences, but other factors did not influence female representation. Our findings imply a good generalizability regarding sex distribution of the study results, strengthening the evidence guiding current clinical practice.
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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 | 0.026 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.028 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".