Pharmacologic Interventions to Reduce the Risk of Asthma Exacerbations
Bibliographic record
Abstract
Inhaled corticosteroids (ICS) are known to reduce the risk of asthma exacerbations and asthma fatalities. In addition, an increased dose of ICS at the onset of exacerbation can reduce the need for systemic corticosteroids, although this may require a fourfold increase in dose. The overuse of short-acting beta(2)-agonists or long-acting inhaled beta(2)-agonists, used as monotherapy, increases these risks. By contrast, the use of long-acting beta(2)-agonists together with ICS has been demonstrated to reduce the doses of ICS needed for ideal asthma control, as well as to reduce asthma exacerbations. This has been best demonstrated in the Formoterol and Corticosteroids Establishing Therapy and Oxis and Pulmicort Turbuhaler in the Management of Asthma studies, which demonstrated that the combination of inhaled budesonide and formoterol reduced the risk of asthma exacerbations over that achieved by budesonide alone. Even the "as needed" use of inhaled formoterol added to ICS reduces asthma exacerbations. The combination inhaler, Symbicort, containing both budesonide and formoterol, reduced the risk of asthma exacerbations to a similar extent as the monocomponents, given separately. Treatment with either leukotriene receptor antagonists or anti-IgE also reduces the risks of asthma exacerbations, but the magnitude of the benefit compared with the combination of ICS and long-acting beta(2)-agonists is not yet known.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.008 | 0.001 |
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".