Effects of an aerobic and resistance training program on functional capacity and glucose regulation in patients with heart failure and diabetes
Bibliographic record
Abstract
Objective To examine the efficacy and metabolic effects of a supervised combined aerobic and resistance exercise training program on both maximal and submaximal exercise capacity and glucose regulation in diabetic patients with symptomatic heart failure (HF). Materials and methods Twenty-one patients with HF, type 2 diabetes mellitus, and left ventricular ejection fraction less than 40% were randomized either to an exercise training program (n=10) or to usual care (n=11) for 24 weeks. Maximal and submaximal cardiopulmonary exercise testing and glucose metabolism using the homeostasis model of assessment-insulin resistance index were assessed at baseline and after 24 weeks. Results VO2peak increased from 19.0±2.4 to 22.1±4.7 ml/min/kg and the submaximal test duration increased from 1234±439 to 2030±1172 s in the exercise training group (NS). However, there was a significant interaction between poor exercise capacity and the change in VO2peak in response to training (P=0.028). Similarly, insulin sensitivity improved in patients with the worst insulin resistance values (P<0.05). Conclusion Combined aerobic and resistance training is safe and exerts beneficial effects on functional capacity and glucose regulation in patients with diabetes mellitus and HF showing poor functional capacity and the worst metabolic profile.
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 | 0.001 | 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 | 0.000 | 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".