Cessation of long-acting β2-agonist in children with persistent asthma on inhaled corticosteroids
Bibliographic record
Abstract
International guidelines recommend adding long-acting β2-agonists (LABA) to inhaled corticosteroids (ICS) as a step 3 or 4 strategy in children in whom ICS, with or without adjunct therapy, is ineffective in adequately controlling asthma [1–4]. Contrary to adults, the beneficial effects of ICS/LABA in children are limited to improving lung function and short-acting β2-agonist use (SABA), with no significant reduction in symptoms compared with ICS alone [5]; moreover, a nonsignificant trend towards more exacerbations requiring oral corticosteroids and/or hospital admissions raised concerns [5]. Asthma-related intubations and deaths linked to LABA [6] have led the US Food and Drug Administration to issue label changes recommending that LABA is discontinued once asthma control has been achieved [7]. Most asthmatic children can be successfully weaned off long-acting β2-agonists to inhaled corticosteroid monotherapy We are indebted to Pierre Gaudreault (University of Montreal, Montreal, Canada) and Caroline Chartrand (CHU Sainte-Justine, Montreal, Canada) who assisted in the diligent data collection during their patients' medical visits and thank the parents of the children enrolled in this study.
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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.019 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".