The Burden of Illness Related to Chronic Obstructive Pulmonary Disease Exacerbations in Québec, Canada
Bibliographic record
Abstract
Background. Chronic obstructive pulmonary disease (COPD) prevalence in Canada has risen over time. COPD-related exacerbations contribute to the increased health care utilization (HCU) in this population. This study investigated the impact of exacerbations on COPD-related HCU. Methods. This retrospective observational cohort study used patient data from the Québec provincial health insurance databases. Eligible patients with a new HCU claim with a diagnostic billing for COPD during 2001–2010 were followed until March 31, 2011. Exacerbation rates and time to first exacerbation were assessed. Unadjusted analyses and multivariable models compared the rate of HCU by exacerbation classification (any [moderate/severe], moderate, or severe). Results. The exacerbation event rate in patients with an exacerbation was 34.3 events/100 patient-years (22.7 for moderate exacerbations and 11.6 for severe exacerbations). Median time to first exacerbation of any classification was 37 months. In unadjusted analyses, COPD-related HCU significantly increased with exacerbation severity. In the multivariable, HCU rates were significantly higher after exacerbation versus before exacerbation ( p<0.01 ) for patients with an exacerbation or moderate exacerbations. For severe exacerbations, general practitioner, respiratory specialist, emergency room, and hospital visits were significantly higher after exacerbation versus before exacerbation ( p<0.001 ). Conclusions. Exacerbations were associated with increased HCU, which was more pronounced for patients with severe exacerbations. Interventions to reduce the risk of exacerbations in patients with COPD may reduce disease burden.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".