Inhaled vilanterol trifenatate/fluticasone furoate (VFF) improves respiratory muscle function and walking performance in severe COPD without change in pulmonary function
Bibliographic record
Abstract
Long acting beta2 agonist/corticosteroids (LABA/ICS) change breathing pattern and chest wall parasternal muscle (PARA) activity in severe COPD (Chest 2010 137:558). However, the global effect on diaphragm and other respiratory muscles, and on exercise performance, is unknown. Aim: Examine effects of ultra-LABA/ICS VFF (Relvar) on respiratory muscle output and walking performance, as well as breathing pattern, dyspnea and PARA EMG in severe COPD. Methods: In N=21 severe Gold IV (2001) COPD (mean FEV1 0.85L;30% Pred), implanted with fine-wire PARA EMG, at baseline, 2hr and 3hr, after 2 puffs VFF, we measured: pulmonary function, breathing pattern, dyspnea (BORG), PARA EMG, global respiratory muscle output by Sniff Nasal Inspiratory Pressure (SNIP), and walking performance during 6 Minute Walk test. Results: With VFF, pulmonary function change was extremely minimal – FEV1 +1.8%, FRC -2.5%, IC +2.8%. Yet, tidal volume increased and respiratory rate decreased (P<0.05), less dyspnea (Borg 13.5 to 9.2 (P<0.05)), peak tidal PARA EMG decreased (P<0.01). Global respiratory muscle output and walk performance increased very significantly: 30.8% and 32.8% respectively, (P<0.01) (Fig1). Conclusion: Even without pulmonary function change, inhaled VFF (Relvar) induced significant improvement in respiratory muscle output and walking performance in severe 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".