The Benefits of High-Intensity Interval Training on Cognition and Blood Pressure in Older Adults With Hypertension and Subjective Cognitive Decline: Results From the Heart & Mind Study
Bibliographic record
Abstract
Background: The impact of exercise on cognition in older adults with hypertension and subjective cognitive decline (SCD) is unclear. Objectives: We determined the influence of high-intensity interval training (HIIT) combined with mind-motor training on cognition and systolic blood pressure (BP) in older adults with hypertension and SCD. Methods: We randomized 128 community-dwelling older adults [age mean (SD): 71.1 (6.7), 47.7% females] with history of hypertension and SCD to either HIIT or a moderate-intensity continuous training (MCT) group. Both groups received 15 min of mind-motor training followed by 45 min of either HIIT or MCT. Participants exercised in total 60 min/day, 3 days/week for 6 months. We assessed changes in global cognitive functioning (GCF), Trail-Making Test (TMT), systolic and diastolic BP, and cardiorespiratory fitness. Results: Participants in both groups improved diastolic BP [ F (1, 87.32) = 4.392, p = 0.039], with greatest effect within the HIIT group [estimated mean change (95% CI): −2.64 mmHg, (−4.79 to −0.48), p = 0.017], but no between-group differences were noted ( p = 0.17). Both groups also improved cardiorespiratory fitness [ F (1, 69) = 34.795, p < 0.001], and TMT A [ F (1, 81.51) = 26.871, p < 0.001] and B [ F (1, 79.49) = 23.107, p < 0.001]. There were, however, no within- or between-group differences in GCF and systolic BP at follow-up. Conclusion: Despite improvements in cardiorespiratory fitness, exercise of high- or moderate-intensity, combined with mind-motor training, did not improve GCF or systolic BP in individuals with hypertension and SCD. Clinical Trial Registration: ClinicalTrials.gov (NCT03545958).
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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 | 0.002 | 0.002 |
| 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".