The Safety of Long-Acting β-Agonists among Patients with Asthma Using Inhaled Corticosteroids
Bibliographic record
Abstract
Abstract Rationale Inhaled long-acting β-agonists (LABAs), when used as monotherapy in asthma, may increase asthma-related hospitalizations, life threatening events requiring intubation/mechanical ventilation, and asthma-related deaths, but concomitant use of inhaled corticosteroids (ICS) may modify this effect. Objectives To determine the safety of long-acting β-agonists among patients with asthma using corticosteroids. Methods We conducted a systematic review and metaanalysis of parallel-group, blinded, randomized, controlled trials with at least 12 weeks of treatment addressing the impact of LABA on asthma-related and total morbidity and mortality in patients concomitantly using ICS. We searched MEDLINE, EMBASE, ACPJC, and Cochrane (Central) databases, and contacted authors and sponsors. Measurements and Main Results We used a random effects model to pool results from different studies as odds ratios (ORs) (95% confidence interval [CI]) (OR < 1.0 favors LABA). The search yielded 62 relevant studies included in this analysis. Among over 29,000 participants (15,710 taking LABA, with over 8,000 patient-years observed in the LABA groups), there were three asthma-related deaths and two asthma-related, nonfatal intubations (all in LABA groups; ≤ one event per study). Differences in asthma-related hospitalizations (OR, 0.74; 95% CI, 0.53–1.03) and asthma-related serious adverse events (mostly hospitalizations; OR, 0.75; 95% CI, 0.54–1.03) failed to reach statistical significance. The OR for total mortality was 1.26 (95% CI, 0.58–2.74), reflecting 14 deaths in LABA groups and eight deaths in control groups, respectively. Conclusions In patients with asthma using ICS, LABA did not increase the risk of asthma-related hospitalizations. There were very few asthma-related deaths and intubations, and events were too infrequent to establish LABA's relative effect on these outcomes.
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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 | 0.049 | 0.167 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.012 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".