Weight status and nonadherence to asthma maintenance therapy among children enrolled in a public drug insurance plan
Bibliographic record
Abstract
Objective: The pediatric obese-asthma phenotype is associated with poor control, perhaps because of medication nonadherence. This study aimed to assess whether weight status is associated with nonadherence in children prescribed new asthma maintenance therapies.Methods: A historical cohort was constructed from a clinical database linking individual patient and prescription data to Quebec’s prescription claims registry. Children aged 2–18 years with specialist-diagnosed asthma who were newly prescribed one of the following maintenance controllers: leukotriene receptor antagonists (LTRA); low-dose inhaled corticosteroids (ICS); medium/high-dose ICS; or combination therapy (ICS with long-acting beta-2 agonists and/or LTRA), at the Asthma Center of the Montreal Children’s Hospital from 2000–2007 were included. Primary nonadherence was defined as not claiming any prescriptions, whereas secondary nonadherence was measured with the proportion of prescribed days covered (PPDC ≤ 50%) among primary adherers over a 6-month follow-up period. A modified Poisson regression model served to estimate the effect of excess weight (BMI > 85th percentile) on primary and secondary nonadherence.Results: Approximately one third of patients were primary nonadherers and 60% took less than 50% of prescribed therapy. Excess weight was associated with a trend toward increased risk of primary nonadherence in children newly prescribed low-dose ICS (RR 1.53, 95%CI 0.94–2.49), and of secondary nonadherence in children initiating medium/high-dose ICS (RR 1.24; 95%CI 0.98–1.59).Conclusions: Excess weight status is a possible determinant of primary nonadherence in children initiating low-dose ICS and secondary nonadherence to higher-dose ICS regimens. This hypothesis-generating study suggests that nonadherence may be a potential contributor to higher morbidity in children with obese-asthma.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 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".