Sex, gender, and stroke recovery: Functional limitations and inpatient care needs in Canadian and European survivors
Bibliographic record
Abstract
BACKGROUND: Stroke is a leading cause of long-term disability among survivors. Past literature already investigated the biological sex differences in stroke outcome; still limited work on gender differences is published. Therefore, the study aimed at investigating whether biological sex and sociocultural gender of survivors play a role as determinants of disability and quality of life among stroke survivors across Europe and Canada. METHODS: Data were gathered from the European Health Information Survey (EHIS, n = 316,333) and Canadian Community Health Survey (CCHS, n = 127,462) data sets. Main outcomes of interest were disability, assessed through evaluating the impairment of Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (iADL), and inpatient care needs, such as hospitalization or institutionalization. Multivariate logistic regression models were utilized to identify factors independently associated with outcomes. Federated analysis was conducted for cross-country comparisons. Data were adjusted for the country-specific Gender Inequality Index (GII), with higher score corresponding to more gender inequality toward females. RESULTS: Female survivors showed greater impairments in iADL (odds ratio [OR] = 1.73, 95% confidence interval [CI]:1.53-1.96) and ADL (OR = 1.25, 95% CI: 1.09-1.44), without a corresponding increase in inpatient care needs. Socioeconomic factors such as marital status and income level were significant predictors of disability, with low income and being single/divorced associated with higher risks. The impact of sex was more pronounced in countries with higher GII, indicating the influence of gender inequality on stroke outcomes. INTERPRETATION: The findings highlight the significant impact of biological sex and gender-related social determinants on post stroke disability, with female sex and unfavorable socioeconomic conditions being associated with worse outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".