Long-acting bronchodilators improve exercise capacity in COPD patients: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: We carried out a systematic review and meta-analysis with the aim to evaluate the efficacy of longacting bronchodilators on exercise capacity in COPD patients. Methods: The endpoints were the efficacy of long-acting bronchodilators (altogether, and by single classes) vs. placebo in modifying endurance time (ET), inspiratory capacity (IC) and dyspnea during exercise, taking into consideration the outcomes according to different patients’ inclusion criteria and exercise methodology. Results: Twenty-two studies were deemed eligible for analysis. Weighted mean increase in ET resulted of 67 s (95% CI ranges from 55 to 79). For isotime IC and dyspnea during exercise, weighted improvements were 195 ml (162–229), and − 0.41 units (− 0.56 to − 0.27), respectively. The increase in trough IC was 157 ml (138–175). We found a trend in favour of LAMA compared to LABA in terms of ET. In the 11 studies which reported a value of functional residual capacity > 120% as inclusion criterion, weighted mean increase in endurance time was 94 s (65 to 123); however we did not find any significant correlation between ET and mean trough IC (P: 0.593). The improvement of ET in the 5 studies using walking as exercise methodology resulted of 58 s (− 4 to 121). Conclusions: Long-acting bronchodilators improve exercise capacity in COPD. The main effect of long-acting bronchodilators seems to be a increase of basal IC rather than a modification of dynamic hyperinflation during exercise. The efficacy in terms of endurance time seems higher in studies which enrolled patients with hyperinflation, with a similar efficacy on walking or cycling.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".