Both Traditional and Stair Climbing–based HIIT Cardiac Rehabilitation Induce Beneficial Muscle Adaptations
Bibliographic record
Abstract
PURPOSE: There is a lack of knowledge as to how different exercise-based cardiac rehabilitation programming affects skeletal muscle adaptations in coronary artery disease (CAD) patients. We first characterized the skeletal muscle from adults with CAD compared with a group of age- and sex-matched healthy adults. We then determined the effects of a traditional moderate-intensity continuous exercise program (TRAD) or a stair climbing-based high-intensity interval training program (STAIR) on skeletal muscle metabolism in CAD. METHODS: Sixteen adults (n = 16, 61 ± 7 yr), who had undergone recent treatment for CAD, were randomized to perform (3 d·wk-1) either TRAD (n = 7, 30 min at 60%-80% of peak heart rate) or STAIR (n = 9, 3 × 6 flights) for 12 wk. Muscle biopsies were collected at baseline in both CAD and healthy controls (n = 9), and at 4 and 12 wk after exercise training in CAD patients undertaking TRAD or STAIR. RESULTS: We found that CAD had a lower capillary-to-fiber ratio (C/Fi, 35% ± 25%, P = 0.06) and capillary-to-fiber perimeter exchange (CFPE) index (23% ± 29%, P = 0.034) in Type II fibers compared with healthy controls. However, 12 wk of cardiac rehabilitation with either TRAD or STAIR increased C/Fi (Type II, 23% ± 14%, P < 0.001) and CFPE (Type I, 10% ± 23%, P < 0.01; Type II, 18% ± 22%, P = 0.002). CONCLUSION: Cardiac rehabilitation via TRAD or STAIR exercise training improved the compromised skeletal muscle microvascular phenotype observed in CAD patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".