Aerobic and Resistance Training in Coronary Disease
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to compare resistance training (RT) (one set vs three sets) combined with aerobic training (AT) versus AT alone in persons with coronary artery disease. METHODS: Subjects (n = 72) were randomized to AT (5 d x wk(-1)) or combined AT (3 d x wk(-1)) with either one set (AT/RT1) or three sets (AT/RT3) of RT performed 2 d x wk(-1). VO2peak, ventilatory anaerobic threshold (VAT), strength and endurance, body composition, and adherence were measured before and after 29 wk of training. RESULTS: Fifty-three subjects (mean +/- SEM age 61 +/- 2) completed the training. The increase from baseline in VO2peak (L x min(-1)) averaged 11% for AT (P < 0.05), 14% for AT/RT1 (P < 0.01), and 18% for AT/RT3 (P < 0.001), however, the difference between groups was not significant. VAT improved significantly in the AT/RT3 group only (P < 0.05). The AT/RT3 group gained more lean mass than the AT group (1.5 versus 0.4 kg, P < 0.01), yet gains between AT/RT1 and AT were similar (P = 0.2). Only AT + RT groups demonstrated a reduction in body fat (P < 0.05). Strength and endurance increased more in the AT + RT groups than AT alone (P < 0.05). Adherence to number of sets performed was lower in AT/RT3 than AT/RT1 (P < 0.02). CONCLUSIONS: Combined AT + RT yields more pronounced physiological adaptations than AT alone and appears to be superior in producing improvements in VO2peak, muscular strength and endurance, and body composition. The data support the use of multiple set RT for patients desiring an increased RT stimulus which may further augment parameters that affect VO2peak, VAT, lower body endurance, and muscle mass in a cardiac population.
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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 | 0.000 |
| 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 | 0.001 | 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".