Cardiovascular risk moderates the effect of aerobic exercise on executive functions in older adults with subcortical ischemic vascular cognitive impairment
Bibliographic record
Abstract
Aerobic training (AT) can promote cognitive function in adults with Subcortical Ischemic Vascular Cognitive Impairment (SIVCI) by modifying cardiovascular risk factors. However, pre-existing cardiovascular health may attenuate the benefits of AT on cognitive outcomes in SIVCI. We examined whether baseline cardiovascular risk moderates the effect of a 6-month progressive AT program on executive functions with a secondary analysis of a randomized controlled trial in 71 adults, who were randomized to either: (1) 3×/week progressive AT; or (2) education program (CON). Three executive processes were measured: (1) response inhibition by Stroop Test; (2) working memory by digits backward test; and (3) set shifting by the Trail Making Test. Baseline cardiovascular risk was calculated using the Framingham cardiovascular disease (CVD) Risk Score (FCRS), and participants were classified as either low risk (< 20% FCRS score; LCVR) or high risk (≥ 20% FCRS score; HCVR). A complete case analysis (n = 58) was conducted using an analysis of covariance (ANCOVA) to evaluate between-group differences in the three executive processes. A significant interaction was found between cardiovascular risk group and intervention group (AT or CON) for the digit span backward and the Trail Making Test. AT improved performance compared with CON in those with LCVR, while in those with HCVR, AT did not improve performance compared with CON. Baseline cardiovascular risk significantly moderates the efficacy of AT on cognition. Our findings highlight the importance of intervening early in the disease course of SIVCI, when cardiovascular risk may be lower, to reap maximum benefits of aerobic exercise.
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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 | 0.001 | 0.001 |
| 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".