Implementation of 2023 CTS guidelines for SITT could reduce exacerbation and mortality rates in COPD: PROMETHEUS Canada.
Bibliographic record
Abstract
Background: COPD is the 4th leading cause of death in Canada. The ETHOS ( NCT02465567 ) and IMPACT RCTs ( NCT02164513 ) demonstrated reduced exacerbations and all-cause mortality for COPD patients on single-inhaler triple therapy (SITT). The 2023 Canadian Thoracic Society (CTS) guidelines recommend triple therapy and preferably SITT use in patients with moderate/severe symptom burden and high future risk of exacerbations. The clinical impact of broader SITT use in Canada has not yet been studied. Aim: To estimate the impact of higher SITT use based on CTS guidelines on mortality, exacerbations and their corresponding costs in Canada. Methods: A stochastic model using literature-derived characteristics (i.e. incidence, changes in COPD severity, treatment, mortality, and exacerbations) simulated the Canadian COPD population. Patients were assigned % of FEV1 predicted levels and their annual characteristics were modeled for 2024-2033 under 2 scenarios: “status quo” (current practice) and “increased SITT” (consistent with guidelines). Results: Based on our simulated results, higher SITT use over 10 years compared to current treatment reduced severe and moderate exacerbations by 13% and 18%, respectively, and reduced all-cause mortality by 22% (Fig 1). Conclusion: Appropriate use of SITT informed by CTS guidelines could lower mortality, exacerbations and their corresponding costs in COPD patients. erj;64/suppl_68/PA1170/F1 F1 F1
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".