Inhaled Corticosteroid Therapy Does Not Control Asthma
Bibliographic record
Abstract
BACKGROUND: Randomized clinical trials demonstrate efficacy and show that inhaled corticosteroid therapy can control asthma, but details concerning their effectiveness in achieving this goal in the community are lacking. OBJECTIVES: To determine whether inhaled corticosteroid therapy is effective in controlling asthma and to examine the rates of asthma control in relation to inhaled corticosteroid use outside the realm of randomized controlled trials. METHODS: Different populations were examined cross-sectionally to determine whether self-reported use of inhaled corticosteroids was associated with control of asthma. Subjects with asthma in the community and those attending a university-based asthma program were studied. The definition of asthma control was based on the recommendations of the Canadian Consensus Report. The elements of asthma control were examined in the context of the subject's stated use and dose of the inhaled corticosteroid. RESULTS: Asthma was controlled in 20% (95% CI 18.7% to 21.3%) of the 3427 subjects included in the present study. Only 15% (95% CI 13.5% to 16.5%) of the 2437 subjects using inhaled corticosteroids exhibited asthma control compared with 33% (95% CI 31.1% to 35.9%) of the 990 subjects not using inhaled corticosteroids (P<0.000001). CONCLUSIONS: Although it is known that inhaled corticosteroid therapy can result in asthma control in most individuals with asthma, the present study has shown that this result may not be attained outside the realm of randomized clinical trials. Inhaled corticosteroid use for asthma in a 'real world' setting appears to reflect disease severity.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".