A real-life comparative effectiveness study into the addition of antibiotics to the management of asthma exacerbations in primary care
Bibliographic record
Abstract
BACKGROUND: Asthma exacerbations are major contributors to asthma morbidity and mortality. They are usually managed with bronchodilators and oral corticosteroids (OCS), but clinical trial evidence suggests that antibiotics could be beneficial. We aimed to assess whether treatment of asthma exacerbations with antibiotics in addition to OCS improved outcomes in larger, more representative routine-care populations. METHOD: OCS plus antibiotics was conducted using the Optimum Patient Care Research Database. The dataset included 28 637 patients; following propensity score matching 20 024 adults and 4184 children were analysed. RESULTS: Antibiotics in addition to OCS were prescribed for the treatment of asthma exacerbations in 45% of adults and 32% of children. Compared to OCS alone, OCS plus antibiotics was associated with reduced risk of having an asthma/wheeze consultation in the following 2 weeks (children hazard ratio (HR) 0.84 (95% CI 0.73-0.96), p=0.012; adults HR 0.86 (95% CI 0.81-0.91), p<0.001), but an increase in risk of a further OCS prescription for a new/ongoing exacerbation within 6 weeks in adults (HR 1.11 (95% CI 1.01-1.21), p=0.030), but not children. Penicillins, but not macrolides, were associated with a reduction in the odds of a subsequent asthma/wheeze consultation compared to OCS alone, in both adults and children. CONCLUSION: Antibiotics were frequently prescribed in relation to asthma exacerbations, contrary to guideline recommendations. Overall, the routine addition of antibiotics to OCS in the management of asthma exacerbations appeared to confer little clinical benefit, especially when considering the risks of antibiotic overuse.
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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 | 0.018 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".