Mediation of Post-Stroke Function by Cognition in the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
INTRODUCTION: Cognitive and functional impairment after stroke are common, but the relation between cognitive and functional decline after stroke is not well studied. METHODS: We used the comprehensive cohort in the Canadian Longitudinal Study on Aging to identify those with prior stroke, and we calculated reliable cognitive change scores from baseline to follow-up for the memory and executive domains. Functional decline was defined as an increase in the number of dependent daily activities. Using formal mediation analysis, we tested the presence and degree of mediation of the association between stroke and functional decline by cognitive decline. RESULTS: There were 22,648 individuals with memory change scores (325 with stroke) and 17,613 individuals with executive change scores (241 with stroke). History of stroke was significantly associated with memory decline (-0.26 standard deviations, 95% CI -0.33 to -0.19), executive decline (-0.22, 95% CI -0.36 to -0.09), and new functional impairment (adjusted odds ratio 2.31, 95% CI 1.80-2.97) over a median of 3-year follow-up. Cognitive decline was a significant mediator of functional decline. Memory decline mediated only 5% of the relationship, whereas executive and overall cognitive decline mediated 13% and 22%, respectively. CONCLUSION: Cognitive decline is a mediator of the association between prior stroke and functional decline; consequently, strategies to delay, attenuate, or prevent cognitive decline after stroke may be important to preserving long-term functional status.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| 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".