Comparison of outpatient and home‐based exercise training programmes for COPD: A systematic review and meta‐analysis
Bibliographic record
Abstract
Chronic obstructive pulmonary disease is a common, preventable and treatable disease. Exercise training programmes (ETPs) improve symptoms, health-related quality of life (HRQoL) and exercise capacity, but the optimal setting is unknown. In this review, we compared the effects of ETPs in different settings on HRQoL and exercise capacity. We searched (5 July 2016) the Cochrane Airways Group Specialised Register, ClinicalTrials.gov and World Health Organization trials portal. We selected studies, extracted data and assessed risk of bias with two independent reviewers. We calculated mean differences (MD) with 95% CI. We assessed the quality of evidence using Grades of Recommendation, Assessment, Development and Evaluation. Ten trials (934 participants) were included. Hospital (outpatient) and home-based ETPs (seven trials) were equally effective at improving HRQoL on the Chronic Respiratory Questionnaire (CRQ) (dyspnoea: MD -0.09, 95% CI: -0.28 to 0.10; fatigue: MD -0.00, 95% CI: -0.18 to 0.17; emotional: MD 0.10, 95% CI: -0.24 to 0.45; and mastery: MD -0.02, 95% CI: -0.28 to 0.25; moderate quality) and on the St George's Respiratory Questionnaire (SGRQ) (MD -0.82, 95% CI: -7.47 to 5.83, low quality). Hospital (outpatient) and community-based ETPs (three trials) were equally effective at improving HRQoL (CRQ dyspnoea: MD 0.29, 95% CI: -0.05 to 0.62, moderate quality; fatigue: MD -0.02, 95% CI: -1.09 to 1.05, low quality; emotional: MD 0.10, 95% CI: -0.40 to 0.59, moderate quality; and mastery: MD -0.08, 95% CI: -0.45 to 0.28, moderate quality). There was no difference in exercise capacity. There was low to moderate evidence that outpatient and home-based ETPs are equally effective. See related Editorial.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.023 | 0.032 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".