Prestroke Physical Activity and Poststroke Cognitive Performance
Bibliographic record
Abstract
INTRODUCTION: Physical activity (PA) is associated with a lower risk of stroke and stroke mortality as well as a favorable stroke outcome. PA may also prevent general cognitive decline. Poststroke cognitive impairment is both common and disabling, and focusing on all possible preventive measures is important. Studies on the effect of PA on poststroke cognitive performance are sparse, however. We therefore aimed to examine the association between prestroke PA and poststroke cognitive performance. METHODS: We studied the correlation between prestroke PA and poststroke cognitive performance in a prespecified analysis in The Efficacy of Citalopram Treatment in Acute Ischemic Stroke (TALOS) trial. We used the Physical Activity Scale for the Elderly (PASE) to collect information on PA during the 7-day period before stroke. PA was quantified, and patients were stratified into quartiles based on their PASE score. Cognitive performance was measured using the Symbol Digit Modalities Test (SDMT) at 1 and 6 months and the Mini-Mental State Examination (MMSE) at 6 months. The functional outcome was assessed using the modified Rankin Scale (mRS). RESULTS: In total, 625 of 642 patients (97%) completed the PASE questionnaire. The median age was 69 (interquartile range [IQR]: 60-77), and the median PASE score was 137 (82-205). Higher prestroke PASE quartiles (2nd, 3rd, and 4th, each compared to the 1st) were independently associated with a higher SDMT score at 1 month in the both the univariable and multivariable analyses (2nd: 3.99 points, 95% confidence interval [CI]: 1.01-6.97; 3rd: 3.6, CI: 0.6-6.61; 4th: 4.1, CI: 0.95-7.24). This association remained at 6 months. PA was not statistically associated with the MMSE score or mRS. CONCLUSION: Higher prestroke PA was associated with a better cognitive performance as measured by the SDMT at 1 and 6 months poststroke. We found no significant association between prestroke PA and functional outcome. Our results are encouraging and support further investigations of PA as a protective measure against poststroke cognitive impairment.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".