Asthma Control Score Based on Filled Medication Prescriptions: A Validation Study
Bibliographic record
Abstract
BACKGROUND: Periodic measurement of disease control is recommended to characterize asthma and monitor treatment. OBJECTIVE: To elaborate and validate an asthma control score (ACS) for use in studies based on administrative health databases. METHODS: Adult patients with asthma were recruited from a clinic. The ACS is based on the average number of doses of short-acting inhaled beta(2)-agonists taken per week and short courses of oral corticosteroids dispensed over a three-month period. Data were obtained from the Régie de l'assurance maladie du Québec database in Canada. The ACS was compared with the asthma control questionnaire and the use of health care services for asthma over a 12-month period. RESULTS: A total of 60 patients were enrolled. They had a mean (+/- SD) age of 50.4+/-13.9 years, and 43.3% were male. Patients had had asthma for 20.8+/-15.1 years on average and had a mean prebronchodilator forced expiratory volume in 1 s of 77.0% of the predicted value. The mean ACS was 8.3+/-11.6, with a range of 0 to 60. The ACS was not found to be correlated with the asthma control questionnaire, but it was significantly associated with health care services used. For each additional point in the ACS, patients were 2% more likely to need acute care for asthma (rate ratio 1.02; P=0.02). CONCLUSIONS: Further studies including patients followed by general practitioners are required before the general use of this score. This innovative score is useful to rapidly assess the control of asthma over long periods of time and at a low cost in studies using administrative drug databases.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".