Extent, trends, and determinants of controller/reliever balance in mild asthma: a 14-year population-based study
Bibliographic record
Abstract
BACKGROUND: The majority of patients with asthma have the mild form of the disease. Whether mild asthma patients receive appropriate asthma medications has not received much attention in the literature. We examined the trends in indicators of controller/reliever balance. METHODS: Using administrative health databases of British Columbia, Canada (2000 to 2013), we created a population-based cohort of adolescents/adults with mild asthma using validated case definition algorithms. Each patient-year of follow-up was assessed based on two markers of inappropriate medication prescription: whether the ratio of controller medications (inhaled corticosteroids [ICS] and leukotriene receptor antagonists [LTRA]) to total asthma-related prescriptions was low (cut-off 0.5 according to previous validation studies), and whether short-acting beta agonists (SABA) were prescribed inappropriately according to previously published criteria that considers SABA in relation to ICS prescriptions. Generalized linear models were used to evaluate trends and to examine the association between patient-, disease-, and healthcare-related factors and medication use. RESULTS: The final cohort consisted of 195,941 mild asthma patients (59.5% female; mean age at entry 29.6 years) contributing 1.83 million patient-years. In 48.8% of patient-years, controller medications were suboptimally prescribed, while in 7.2%, SABAs were inappropriately prescribed. There was a modest year-over-year decline in inappropriate SABA prescription (relative change - 1.3%/year, P < 0.001) and controller-to-total-medications (relative change - 0.5%/year, P < 0.001). Among the studied factors, the indices of type and quality of healthcare (namely respirologist consultation and receiving pulmonary function test) had the strongest associations with improvement in controller/reliever balance. CONCLUSIONS: Large number of mild asthma patients continue to be exposed to suboptimal combinations of asthma medications, and it appears there are modifiable factors associated with such phenomenon.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".