Systematic Review of Worldwide Female Enrollment in Randomized Controlled Trials of Poststroke Lower Extremity Rehabilitation
Bibliographic record
Abstract
ABSTRACT: This review systematically examined the reporting of sex and female participation in poststroke lower extremity motor rehabilitation randomized controlled trials over time and identified differences in female participation across randomized controlled trials conducted in low- and middle-income countries, high-income countries, and high-income country regions. Systematic searches were conducted of MEDLINE, Embase, CINAHL, and PsycINFO from 1970 to May 2022. Randomized controlled trials in English were included if they examined poststroke LE motor rehabilitation interventions in adults diagnosed with stroke. A total of 1283 randomized controlled trials were analyzed; 4.5% of randomized controlled trials did not report sex, and the overall female participation was 39.5%. The percentage of female participants did not significantly differ between high-income countries and low- and middle-income countries. Within high-income countries, the percentage of female participants was significantly higher in European randomized controlled trials than randomized controlled trials in Asia and Oceania ( P = 0.01). No significant changes in female participation were found for any of the countries or regions over the last two decades. Female participation was significantly higher in randomized controlled trials conducted in the acute phase compared to those in the chronic phase ( P < 0.001). More research is needed to understand the reasons behind female underenrollment and further efforts are required to ensure adequate enrollment of males and females.
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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 | 0.038 | 0.146 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".