The role of inhaled corticosteroids in the management of acute asthma
Bibliographic record
Abstract
Acute exacerbations are common occurrences for asthmatics. Contact with airway irritants ( e.g. viral upper respiratory tract infections, aero-allergens) and nonadherence to controller medications, along with the natural history of the disease can result in deterioration in lung function, increased symptoms and an increased need for reliever medication. It is estimated that nearly 2 million emergency department (ED) asthma visits occur annually in the USA alone 1. Since the frequency of exacerbations is related to asthma severity on the one hand, and increasing degrees of airway eosinophilia are associated with increased disease severity on the other 2, understanding the pathophysiology of exacerbations is critically important to disease control. The medical consequences of these events can range from minor life interruptions to severe illness. These severe exacerbations often result in ED presentation or unscheduled visits to health professionals for urgent care, and may require hospital admission. While rare, death from exacerbations does occur. The economic consequences of asthma have been well documented 3, 4 and the acute attack has been estimated to represent ∼25% of overall asthma costs 5. The control of chronic asthma with the use of inhaled corticosteroids (ICS), with or without the use of additional agents ( e.g. long-acting β-agonists or leukotriene receptor antagonists), anticholinergics and in some cases newer biological agents, have proven effective in reducing the frequency and severity of these exacerbations. In addition, nonpharmacological approaches (regular follow-up, action plans, immunisation, asthma education) have also proven to be effective but adherence to these can be low 6, 7. Despite these advances, a gap between what is known and what is practiced hampers efforts to improve the quality of life of patients with asthma. This gap may be the result of poor access to care and resources, failure of physicians to treat the disease …
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".