Excess inhaled corticosteroid adherence may be a marker of uncontrolled asthma
Bibliographic record
Abstract
Background: The relationship between adherence to inhaled corticosteroids (ICS) in excess of 100% and asthma control is unclear. Methods: The Respiratory Effectiveness Group conducted a real-life study using a US healthcare database to examine the association between ICS medication possession ratio (MPR) >100% (a proxy measure of excess adherence) and asthma control. Eligible patients were 12–80 yrs and initiated ICS as hydrofluoroalkane beclometasone (n=2578) or fluticasone (n=7734). Over the one-year period following ICS initiation, MPR was calculated as the number of days’ supply of ICS/365 x 100% (categorized as ≤100%; >100%). Measures of asthma control consisted of severe exacerbations (unscheduled hospital admission or ER attendance for asthma or an acute course of oral corticosteroids) and Risk Domain Asthma Control (RDAC: no admission, ER attendance, or outpatient hospital attendance for asthma; no acute oral corticosteroids prescriptions; no consultation, hospital admission, or ER attendance for a lower respiratory tract infection requiring antibiotics, and no hospital admission or ER attendance for lower respiratory reasons) during the same period. Results: MPR>100% occurred in 7.2% of patients (n=742). Severe exacerbations were more common and RDAC attainment lower in patients with MPR >100% than in patients with MPR ≤100% (see table). MPR≤100% MPR>100% p-value ≥1 exacerbation 25% 43% <0.001 ≥2 exacerbations 8% 21% <0.001 RDAC attainment 59% 40% <0.001 Conclusions: In clinical practice, adherence to ICS in excess of the label-defined dosing interval appears to be a marker of poorer asthma control. A MPR >100% may be a simple tool to identify patients in need of more intensive evaluation.
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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 | 0.008 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".