Acute bronchodilator therapy does not reduce wasted ventilation during exercise in COPD
Bibliographic record
Abstract
This randomized, double-blind, crossover study aimed to determine if acute treatment with inhaled bronchodilators , by improving regional lung hyperinflation and ventilation distribution , would reduce dead space-to-tidal volume ratio (V D /V T ); thus contributing to improved exertional dyspnea in COPD . Twenty COPD patients (FEV 1 = 50 ± 15% predicted; mean ± SD) performed pulmonary function tests and symptom-limited constant-work rate exercise at 75% peak-work rate (with arterialized capillary blood gases) after nebulized bronchodilator (BD; ipratropium 0.5mg + salbutamol 2.5 mg) or placebo (PL; normal saline). After BD versus PL: Functional residual capacity decreased by 0.4L (p = .0001). Isotime during exercise after BD versus PL (p < .05): dyspnea decreased: 1.2 ± 1.9 Borg-units; minute ventilation increased: 3.8 ± 5.5 L/min; IC increased: 0.24 ± 0.28 L and V T increased 0.19 ± 0.16 L. There was no significant difference in arterial CO 2 tension or V D /V T , but alveolar ventilation increased by 3.8 ± 5.5 L/min (p = .02). Post-BD improvements in respiratory mechanics explained 51% of dyspnea reduction at a standardized exercise time. Bronchodilator-induced improvements in respiratory mechanics were not associated with reduced wasted ventilation – a residual contributory factor to exertional dyspnea during exercise in COPD .
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".