Bronchodilators do not change ventilatory efficiency during exercise in COPD
Bibliographic record
Abstract
The ventilatory equivalent for carbon dioxide (VE/VCO2) during exercise is increased in COPD compared with healthy controls, mainly reflecting increased wasted ventilation or reduced pulmonary perfusion relative to alveolar ventilation [Elbehairy et al. AJRCCM 2015;191:1384-94]. Thus, VE/VCO2 may serve as a useful surrogate for evaluation of ventilation/perfusion abnormalities in COPD. The aim of this study was to determine if treatment with inhaled bronchodilators, by improving regional lung hyperinflation and distribution of ventilation, alters VE/VCO2 during exercise. Methods In a randomized, double-blind, crossover study, 16 patients with COPD (FEV1=43±10 % predicted; mean±SD) performed pulmonary function tests and symptom-limited constant-work rate exercise at 75% peak work rate after nebulized bronchodilator (BD; ipratropium 0.5mg + salbutamol 2.5mg) or placebo (PL). Arterialized capillary blood gases were measured during rest and exercise. Results: After BD compared with PL: FEV1 increased 0.33±0.26 L and inspiratory capacity (IC) increased 0.31±0.28 L (both p<0.001); exercise endurance increased 1.69±3.44 min (p=0.067). At a standardized exercise time after BD versus PL: dyspnea decreased 1.4±1.8 Borg units, IC increased 0.25±0.28 L and tidal volume increased 0.18±0.15 L (all p<0.05); with no significant difference in ventilation, VE/VCO2, arterial CO2 tension or physiological dead space (VD/VT). BD did not change VE/VCO2 at rest or at its nadir. Across tests, VE/VCO2 during exercise correlated with VD/VT (p=0.002). Conclusion: Bronchodilator-induced improvements in expiratory flow rates, operating lung volumes and breathing pattern did not influence VE/VCO2 or VD/VT 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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 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".