The Effects of an Aerobic and Resistance Exercise Training Program on Cognition Following Stroke
Bibliographic record
Abstract
BACKGROUND: Cognitive benefits obtained from exercise in healthy populations support the idea that aerobic and resistance training (AT+RT) would confer benefit for poststroke recovery. However, there is little evidence regarding the effectiveness of such programs. OBJECTIVE: To evaluate the effects of a 6-month exercise program of AT+RT on cognition in consecutively enrolled patients with motor impairments ≥10 weeks poststroke. METHODS: Outcomes were measured before and after 6 months of AT+RT on 41 patients. Cognition was measured by the Montreal Cognitive Assessment (MoCA). Secondary measures included evaluation of gas exchange anaerobic threshold (ATge), body composition by dual energy X-ray absorptiometry, and depressive symptoms by questionnaire. RESULTS: There were significant improvements in overall MoCA scores (22.5 ± 4.5 to 24.0 ± 3.9, P < .001) as well as in the subdomains of attention/concentration (4.7 ± 1.7 to 5.2 ± 1.3, P = .03) and visuospatial/executive function (3.4 ± 1.1 to 3.9 ± 1.1, P = .002). There was a significant reduction in the proportion of patients meeting the threshold criteria for mild cognitive impairment (MCI) at baseline compared with posttraining (65.9% vs 36.6%, P < .001). In a linear regression model, there was a positive association between change in cognitive function and change in fat-free mass of the nonaffected limbs (β = .002; P = .005) and change in attention/concentration and change in ATge (β = .383; P ≤ .001), independent of age, sex, time from stroke, and change in fat mass and depression score. CONCLUSION: A combined training model (AT+RT) resulted in improvements in cognitive function and a reduction in the proportion of patients meeting the threshold criteria for MCI. Change in cognition was positively associated with change in fat-free mass and ATge.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".