Trends in prevalence, incidence and mortality of diagnosed and silent coronary heart disease in Quebec
Bibliographic record
Abstract
INTRODUCTION: Of all cardiovascular causes of mortality, coronary heart disease (CHD) remains the leading cause of death. Our objectives were to establish trends in the prevalence and incidence of CHD in the province of Quebec, and to determine the proportion of CHD mortality that had no previous CHD diagnosis. METHODS: Trends in prevalence, incidence and mortality were examined with a population-based study using the Quebec Integrated Chronic Disease Surveillance System, which links several health administrative databases. Data are presented using two case definitions for Quebecers aged 20 years and over: 1) a validated definition, and 2) CHD causes of death codes added to estimate the proportion of deaths that occurred without any previous CHD diagnosis as a proxy for sudden cardiac death (SCD). RESULTS: In 2012/2013, the crude prevalence of CHD was 9.4% with the first definition (593 000 people). Between 2000/2001 and 2012/2013, the age-standardized prevalence increased by 14%, although it has been decreasing slightly since 2009/2010. Age-standardized incidence and mortality rates decreased by 46% and 26% respectively, and represented a crude rate of 6.9 per 1000 and 5.2% in 2012/2013. The proportion identified only by CHD mortality, our SCD proxy, was only significant for the incident cases (0.38 per 1000 in 2009/2010) and declined over the study period. CONCLUSION: The prevalence of CHD has tended to decrease in recent years, and incidence and mortality have been declining in Quebec. Most CHD mortality occurs in previously diagnosed patients and only a small proportion of incident cases were not previously identified.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".