BIOLOGICAL SEX MODERATES THE EFFECT OF EXERCISE ON COGNITIVE FUNCTION IN ADULTS WITH CHRONIC STROKE
Bibliographic record
Abstract
Abstract Exercise (EX) and cognitive/social enrichment (ENRICH) are promising strategies for promoting cognitive function post-stroke. The effects of these interventions on cognitive function may vary by biological sex, i.e. males (M) vs females (F). We conducted a secondary analysis of a three-arm, six-month, assessor-blinded, randomized clinical trial among 120 community-dwelling adults aged 55+ years with chronic stroke (i.e., ≥12 months since stroke), to examine if biological sex moderates the effects of EX or ENRICH on cognitive function. Participants were randomly assigned to 2x/week EX (N=34, M=21, F=13), 2x/week ENRICH (N=34, M=23, F=11), or 2x/week balance and tone control (BAT, M=30, F=22). Our primary outcome of cognitive function was the Alzheimer’s Disease Assessment Scale Cognitive Subscale Plus (ADAS-COG-Plus) at baseline, end of intervention (6 months), and follow-up (12 months). Using linear mixed models, we examined if biological sex moderated the effects of EX or ENRICH on cognitive function using planned contrasts. Baseline ADAS-Cog-Plus and Mini Mental State Exam score were included as fixed-effect covariates. Biological sex moderated the effect of EX, but not ENRICH, on ADAS-Cog-Plus (F = 5.75, p< 0.01). The effects of EX compared to BAT were significantly larger for females than males (estimated mean difference: -0.394, 95% CI: -0.778, -0.011, p< 0.05). EX females had better ADAS-COG-PLUS performance at end of the intervention (estimated mean difference: -0.463, 95% CI: -0.758, -0.168, p< 0.005) compared with females in the BAT group. Findings suggest that exercise may be a key strategy to promote cognitive function among older females living with stroke.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".