New developments in optimizing bronchodilator treatment of COPD: a focus on glycopyrrolate/formoterol combination formulated by co-suspension delivery technology
Bibliographic record
Abstract
Anthony D D’Urzo,1 Mario Cazzola,2 Nicola A Hanania,3 Roland Buhl,4 M Reza Maleki-Yazdi5 1Department of Family and Community Medicine, Faculty of Medicine, University of Toronto, Toronto, ON, Canada; 2Department of Experimental Medicine and Surgery, Tor Vergata University of Rome, Rome, Italy; 3Section of Pulmonary and Critical Care Medicine, Baylor College of Medicine, Houston, TX, USA; 4Pulmonary Department, Mainz University Hospital, Mainz, Germany; 5Division of Respiratory Medicine, Women’s College Hospital, University of Toronto, Toronto, ON, Canada Abstract: COPD causes considerable health and economic burden worldwide, with incidence of the disease expected to continue to rise. Inhaled bronchodilators, such as long-acting muscarinic antagonists (LAMAs) and long-acting β2-agonists (LABAs), are central to the maintenance treatment of patients with COPD. Clinical studies have demonstrated that combined LAMA + LABA therapies improve efficacy while retaining a safety profile similar to LAMA or LABA alone. This has led to the development of several LAMA/LABA fixed-dose combination (FDC) therapies, which provide patients with the convenience of two active compounds in a single inhaler. GFF MDI (Bevespi Aerosphere®) is an FDC of glycopyrrolate/formoterol fumarate 18/9.6 µg formulated using innovative co-suspension delivery technology for administration via metered dose inhaler (MDI). GFF MDI was developed to make a treatment option available for patients who have a requirement or preference to use an MDI, rather than a dry powder or soft mist inhaler. Now that several LAMA/LABA FDCs have been approved for use in COPD, we review the impact of dual-bronchodilator treatment on COPD therapy and discuss recent clinical studies that are helping to develop a more comprehensive understanding of how LAMA/LABA FDCs can improve patient outcomes. Keywords: long-acting bronchodilator, LAMA, LABA, chronic obstructive pulmonary disease, fixed-dose combination, GFF MDI
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".