Short-acting beta agonist, antibiotics, oral corticosteroid and association with mortality and cardiopulmonary events in patients with COPD: a retrospective cohort study in Alberta, Canada
Bibliographic record
Abstract
OBJECTIVE: The purpose of the study was to examine the association between short-acting beta agonist (SABA), antibiotic and oral corticosteroid (OCS) use and mortality and cardiopulmonary outcomes in chronic obstructive pulmonary disease (COPD). DESIGN: Retrospective cohort study using administrative health data from 1 April 2011 to 31 March 2020. SETTING: Alberta, Canada. PARTICIPANTS: Patients ≥35 years old with COPD were identified using diagnostic codes. PRIMARY AND SECONDARY OUTCOME MEASURES: Patient characteristics included age, sex, geographical zone and comorbidities (as defined by the Charlson Comorbidity Index). Outcome variables included all-cause and COPD-related mortality. Outcomes were assessed in consecutive 90-day intervals, starting from cohort entry, paired with time-varying COPD-related medication history in the 1 year preceding each interval. Associations were modelled between mortality and SABA, antibiotic and OCS history, and between major adverse cardiac events (MACE) and cardiovascular disease (CVD) death and SABA history. RESULTS: Among 188 969 patients, dose-response effects were observed. Adjusting for covariates, rates were higher for patients with 6+ (vs 1) SABA dispenses (all-cause mortality HR: 1.20, 95% CI 1.16 to 1.24, p<0.001; COPD-related mortality HR: 1.40, 95% CI 1.34 to 1.46, p<0.001). Patients receiving 6+ (vs 1-2) antibiotic dispenses had 62% (HR: 1.62, 95% CI 1.57 to 1.66, p<0.001) and 43% (HR: 1.43, 95% CI 1.38 to 1.49, p<0.001) higher rates of all-cause and COPD-related mortality, respectively. Patients experiencing 6+ (vs 1-5) OCS burst-days had 27% (HR: 1.27, 95% CI 1.18 to 1.36, p<0.001) and 29% (HR: 1.29, 95% CI 1.19 to 1.40, p<0.001) higher rates of all-cause and COPD-related mortality, respectively. Adjusting for covariates, patients with 2-5 (vs 1) SABA dispenses had higher rates of postexacerbation MACE and CVD death (incidence rate ratio: 1.26, 95% CI 1.16 to 1.36, p<0.001 and 1.27, 95% CI 1.16 to 1.40, p<0.001, respectively). CONCLUSIONS: One-year COPD reliever or exacerbation management medication history was associated with higher rates of mortality and postexacerbation MACE (SABA specific).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".