[P2–574]: DIRECT AND MODERATING EFFECTS OF RECENT LEISURE ACTIVITY PARTICIPATION UPON COGNITIVE FUNCTIONS AFTER STROKE OR TIA
Bibliographic record
Abstract
The objective of this study is to examine the effects of recent regular participation in physical (PA) and intellectual activities (IA) upon cognition at 3 to 6 months after stroke or TIA. We also explored whether the cognitive effects interacted with the severity of white matter hyperintensities (WMH) in patients with low and high education. Two-hundred and ninety-two subjects with mean age of 66 (11.0) years were recruited at median 161(131–180) days post event. Regular activity participation was determined as ≥3 times/week over the past year before stroke or TIA. Cognitive functions were measured using the Montreal Cognitive Assessment (MoCA). Multiple linear regression analysis was conducted to explore the associations between leisure activity participation with WMH and the moderating effects of leisure activities upon relationship between WMH and MoCA (with respective activity x WMH volume interaction). Analyses were further stratified by low (<6 years) or high education (≥6 years). Effect of aerobic and non-aerobic physical activities was also compared. All models were adjusted with age, sex and years of education. PA, but not IA, was negatively related to WMH volume (b=-3.45, p<.05). IA (b=3.81, p<.001) contributed to the MoCA scores. Only IA, but not PA, has main effect towards MoCA score after stroke/TIA (b=3.81, p<.001). Significant interaction with WMH volume was found for PA (b=0.27, p<.01) but not with IA. Such interaction was found in the lower education group (b=.28, p<.01) but not in the higher education group.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".