Underuse of Inhaled Corticosteroids in Adults with Asthma
Bibliographic record
Abstract
Despite strong evidence that inhaled corticosteroids are beneficial in treating asthma, a number of small studies suggest a use rate of only 34-56%. The primary objective of this study was to determine patterns of prescribing inhaled corticosteroids for high-risk patients with asthma. Secondary objectives were to assess patterns of practice with respect to other agents prescribed before and at hospital discharge, and to determine if an emergency room asthma care map at one of the study hospitals was being followed. We retrospectively reviewed charts of 1022 patients with an acute attack of asthma treated in the emergency rooms of the Royal Alexandra Hospital and University of Alberta Hospital from January 1, 1996, to March 31, 1997. A forward stepwise logistic regression analysis was performed with the dependent variable defined as whether or not the patient was using an inhaled or oral corticosteroid during the index visit, and the independent variable being all major demographic variables. Inhaled corticosteroids were prescribed for 460 patients (52.0%) at the index visit. Overall, antiinflammatory drugs were prescribed for 548 patients (62.1%). An asthma care map was followed for 107 (16.8%) patients treated at the Royal Alexandra Hospital at the index visit. Logistic regression analysis showed that women and patients with more than one emergency room visit most likely were to be using inhaled or inhaled plus oral corticosteroids at the index visit. Documentation of drug therapy at discharge was poor for 42% of patients; therefore, analysis of practice patterns in this group was not attempted. This study shows that inhaled corticosteroids were prescribed for only about one-half of patients with an acute asthma attack. Given this low use by high-risk patients, the need for programs designed to improve asthma therapy is evident.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".