Trends in severe COPD exacerbations and mortality following the introduction of ultra-long-acting bronchodilators: an interrupted time-series study between 2007 and 2018 in the province Quebec, Canada
Bibliographic record
Abstract
Background: Little is known about the trends in severe chronic obstructive pulmonary disease (COPD) exacerbations and mortality at the population level that followed the introduction of ultra-long-acting beta2-agonists (ultra-LABA), and fixed-dose combinations of ultra-LABA/long-acting antimuscarinics (LAMA). Objectives: To evaluate whether the arrival of new bronchodilators was associated with changes in the temporal trends in severe exacerbations and mortality between 2007 and 2018 in the older population with COPD. Methods: Cohorts of individuals aged >65 years with COPD were created from the Quebec Integrated Chronic Disease Surveillance System. We used an interrupted time-series and three segments multivariate autoregressive models to evaluate the adjusted changes in slopes (i.e. trend effect) in monthly severe exacerbation and mortality (total and respiratory-related) rates after the introduction of ultra-LABA (03/2013) and ultra-LABA/LAMA (02/2015) compared to the pre-ultra-LABA period. Results: Significant changes in trends were seen after 03/2013 for all-cause mortality (-1.12%/month;95%CI -1.89% to -0.36%), which further decreased after 02/2015 (-1.74%/month;95%CI -2.62% to -0.86%). Decreases in respiratory-related mortality (-2.13%/month;95%CI -4.03% to -0.98%) and severe exacerbation (-1,88%/month;95%CI -2.99% to -0.77%) rates were only observed after 02/2015. Conclusion: The arrival of newer bronchodilators was associated with reduced trends in severe exacerbation, all-cause and respiratory-related mortality rates among people with COPD >65 years in the province of Quebec.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".