Developing the model of pulmonary rehabilitation for chronic heart failure
Bibliographic record
Abstract
Patients with chronic obstructive pulmonary disease (COPD) and chronic heart failure (CHF) commonly suffer from exertional symptoms of breathlessness and fatigue. The similar systemic manifestations of the conditions, including skeletal muscle dysfunction, are a major contributing factor to the limitation in exercise capacity. A period of exercise training has been shown to improve exercise performance and health-related quality of life for both conditions. Exercise training is a key component of pulmonary rehabilitation (PR) which is now a standard of care for patients with COPD and is symptom based. Although it may be assumed that patients with CHF could be incorporated into cardiac rehabilitation, this is predominantly a secondary prevention programme for patients who are largely asymptomatic. It has been shown that patients with CHF can be successfully trained together with patients with COPD by the same therapists within PR. There are comparable outcome measures that can be used for both COPD and CHF. Many patients with CHF still do not have access to an exercise rehabilitation programme and incorporating them into the PR model of care could be one solution. This article reviews the (1) similar symptoms, mechanisms and consequences between COPD and CHF, (2) rationale and evidence for exercise training in CHF, (3) model of PR, (4) safety of exercise training in CHF, (5) evidence for combined exercise rehabilitation for CHF and COPD, (6) adaptations necessary to include patients with CHF into PR, (7) the chronic care model and (8) summary.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".