What have we learnt about asthma control from trials of budesonide/formoterol as maintenance and reliever?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite improvements in medications, devices and understanding of the disease, about half of all asthma patients worldwide remain inadequately controlled, suggesting the need for a new approach to asthma management. Poor adherence to prescribed maintenance therapy and over-reliance on SABA reliever medication is a common cause of inadequate control. This article reviews published data from 6- to 12-month, double-blind, RCT and open-label real-world studies involving budesonide/formoterol maintenance and reliever therapy (MART) and relevant comparator approaches to asthma management, and considers how these compare in achieving the treatment goals described in guidelines. The data confirm that patients with asthma treated with budesonide/formoterol MART achieved the same or better asthma symptom control compared with ICS/LABA plus SABA regimens at similar or higher ICS doses, with consistently lower rates of exacerbations and considerably lower annual requirement for oral corticosteroids. These findings have been confirmed across a range of severities of persistent asthma. With the MART approach, maintenance dosing ensures coverage for day-to-day control, and the use of a reliever with anti-inflammatory properties (budesonide/formoterol) provides extra doses of ICS as soon as symptoms prompt the use of reliever, resulting in a 40-50% reduction of exacerbations compared with an ICS-based treatment approach plus as-needed SABA as reliever. As-needed, budesonide/formoterol has also recently been shown to be more effective as a reliever in mild asthma than SABA alone, reducing exacerbations by up to 64% in the SYGMA studies.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it