Mortality trends in women and men with COPD in Ontario, Canada, 1996–2012
Bibliographic record
Abstract
IMPORTANCE: COPD is the third leading cause of death worldwide. Mortality trends offer an indication of how well a society is doing in fighting a disease. OBJECTIVE: To examine trends in all-cause, lung cancer, cardiovascular and COPD mortalities in people with COPD, overall and in men and women. DESIGN, SETTING, PARTICIPANTS: Population, cohort study using health administrative data from Ontario, Canada, 1996 to 2011. EXPOSURE: A previously validated COPD case definition was used to identify all people with COPD. MAIN OUTCOMES AND MEASURES: All-cause, lung cancer, cardiovascular and COPD mortality rates were determined annually from 1996 to 2011 overall, and in men and women. All-cause trends were compared with all-cause trends in the non-COPD population. All rates were standardised to the 2006 Ontario population. RESULTS: The prevalence of COPD was 11.0% in 2011. Over the study period, all-cause mortality decreased significantly more in men with COPD than the non-COPD population. The same was not observed in women. COPD-specific and lung cancer mortalities, which started higher in men with COPD, decreased faster in them than in women with COPD with the two rates becoming more similar over time. Cardiovascular disease mortality declined at a relatively equal rate in both sexes. CONCLUSIONS AND RELEVANCE: Mortality in people with COPD has decreased; however, the decrease has been greater in men than in women. Public health interventions and medical care appear to be improving mortality in individuals with COPD but more research is needed to determine if they are benefiting both sexes equally.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".