Supervised exercise training improves aerobic capacity and muscle strength in older women with heart failure.
Bibliographic record
Abstract
BACKGROUND: The effect that supervised or unsupervised exercise training has on aerobic capacity (peak oxygen consumption [VO2peak]), muscle strength and quality of life in older women with heart failure remains unknown. OBJECTIVE: To examine the effect of six months (three months supervised followed by three months unsupervised) of aerobic training (AT) or combined aerobic and strength training (CAST) on VO2peak, muscle strength and quality of life in older women with heart failure. METHODS: Twenty older women (mean age +/- SD, 72+/-8 years) with clinically stable heart failure were randomly assigned to AT (n=10) or CAST (n=10). Supervised AT was performed two days per week at 60% to 70% heart rate reserve, whereas unsupervised training was performed two days per week at a rate of perceived exertion of 12 to 14 on the Borg scale. The CAST group also performed one to two sets of low-to-moderate intensity strength training two days per week. RESULTS: Supervised AT or CAST resulted in an increase in VO2peak (12%; P<0.05) and leg press strength (13%; P<0.05) that returned to baseline after unsupervised training. Vertical row strength was greater (+23%; P<0.05) after supervised CAST and remained unchanged after supervised or unsupervised AT. Supervised or unsupervised exercise training was not associated with a significant change in quality of life. CONCLUSIONS: Supervised AT or CAST are effective modes of exercise to improve VO2peak and muscle strength in older women with heart failure. However, the improvements in VO2peak and muscle strength are not maintained with unsupervised exercise training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".