Association of Short-Acting-β-2 Agonist (SABA) Overuse and Risk of COPD among Adult Asthma Patients
Bibliographic record
Abstract
Background: Despite the well-known availability of treatment guidelines on the proper use of asthma medications, excessive SABA use and suboptimal adherence to controller medications persist. Methods: We conducted a retrospective observational study using a linked population-based administrative claim database from the population data in British Columbia. The study included adult asthma patients aged 18 years and older during the index period from January 1, 1998 to December 31, 1999, using ICD codes and drug identification numbers. The identified patients were followed to measure COPD incidence from January 1, 2000 to December 31, 2018. The primary exposure variable "SABA overuse" was defined as the collection of more than two (2) SABA canisters in a calendar year. The standard Cox proportional hazard model was employed to examine the association. Results: A total of 68,211 adult asthma patients with a mean age of 48.2 years, 40,455 of whom were female, met the study’s inclusion criteria based on a validated case definition. In the multivariate Cox proportional hazard model, overuse of SABA at baseline was significantly associated with increased risk of COPD compared to appropriate SABA users at the 5-year follow-up period [adjusted Hazard Ratio (aHR): 2.35, 95% CI:1.92-2.87), (aHR: 2.38, 95% CI: 2.0-2.83) at the 10-year follow-up period, and (aHR: 2.38, 95% CI: 2.03, 2.78) at the 18-year follow-up duration after controlling for all relevant covariates and confounders. Conclusion: Interventions aimed at increasing healthcare providers’ adherence to the updated asthma clinical practice guidelines should be prioritized to minimize excess prescription of short-acting bronchodilators.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".