Cardiac adaptations to non-linear aerobic training in patients with COPD
Bibliographic record
Abstract
While the cardiac adaptations to exercise training are well documented in healthy individuals, the effects of exercise training on cardiac function in patients with COPD are not well known. The aim of this study was to investigate the effects of aerobic exercise training on the cardiac responses to exercise in patients with COPD. 22 COPD patients and 20 healthy controls underwent incremental exercise testing and echocardiography at rest, 25, 50 and 75% workload maximum (Wmax). Subjects then performed non-linear aerobic exercise training 3x/wk for 8 weeks. Individual slope analysis of heart rate (HR) vs. cardiac output (Q) were used to estimate changes in maximal Q. Patients with COPD and controls increased VO2peak following exercise training (p<0.01). Echocardiographic images were successfully obtained in 14 patients and 14 controls. Following training, HR was reduced at 75%Wmax in COPD and at all intensities in controls (p<0.05). Exercise training had no-significant effect on stroke volume (SV), end-diastolic volume (EDV) or end-systolic volume (ESV) in COPD. Estimated maximal Q was also not increased (7.25±3.50 vs. 7.82±2.88 L, p>0.05). In controls, no significant cardiac adaptations were observed at rest, 25 and 50%Wmax. However, at 75%Wmax, EDV was significantly increased following training, while there were no changes in SV, ESV or maximal Q (8.27±3.32 vs. 9.49±3.28 L, p>0.05). While exercise training increased VO2peak in COPD patients, the primary cardiac adaptation appears to be reduced submaximal HR with little change in LV filling, ejection or maximal Q. This finding is somewhat in contrast to healthy individuals who also have reduced HR but this is accompanied by increased filling post training.
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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 | 0.001 |
| 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".