Respiratory rehabilitation of patients with chronic obstructive pulmonary disease
Bibliographic record
Abstract
Abstract Background Physical exercise is an important component of respiratory rehabilitation because it re-verses skeletal muscle dysfunction, a clinically important manifestation of COPD asso-ciated with reduced health-related quality of life (HRQL) and survival. However, thereis controversy regarding the components of the optimal exercise protocol. We systemat-ically evaluated and summarised randomised controlled trials (RCTs) comparing differ-ent exercise protocols for COPD patients. Methods We searched six electronic databases, congress proceedings and bibliographies of includ-ed studies without imposing language restrictions. Two reviewers independentlyscreened all records and extracted data on study samples, interventions and method-ological characteristics of included studies. Results The methodological quality of the 15 included RCTs was low to moderate. Strength ex-ercise led to larger improvements of HRQL than endurance exercise (weighted meandifference for chronic respiratory questionnaire 0.27, 95 % CI 0.02 to 0.52). Interval exer-cise seems to be of similar effectiveness compared to continuous exercise, but there arefew data on clinically relevant outcomes. One small RCT including patients with mildCOPD compared the effect of high and low intensity exercise (at 80 % and 40 % of themaximum exercise capacity, respectively) exercise intensities and found larger physio-logical training effects from high intensity exercise.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".