Chronic Underrepresentation of Females and Women in Stroke Research Adversely Impacts Clinical Care
Bibliographic record
Abstract
Unequal sex and gender sample sizes in rehabilitation studies have implications for the generalizability of the evidence and for the clinicians that utilize their recommendations. Physical therapists rely on evidence-based guidelines to tailor their assessments and interventions to optimize outcomes for patients. We currently know that females and women have worse stroke outcomes and prognoses than their counterparts, however, rehabilitation guidelines remain the same for all individuals. Notably, stroke prevention and acute care has recently shifted to include female- and women-oriented guidelines, however, rehabilitation guidelines have not yet caught up. This article summarizes the key differences that females and women with stroke experience, how they may impact recovery, and calls for researchers and rehabilitation professionals to consider sex and gender when working with patients who've had a stroke. Doing so will improve the lives for those with stroke and maximize treatment options and rehabilitation outcomes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".