Recent Temporal Changes in Atherosclerotic Cardiovascular Diseases in Ontario: Clinical and Health Systems Impact
Bibliographic record
Abstract
BACKGROUND: It is unknown how the contemporary burden of atherosclerotic cardiovascular disease (ASCVD) compares with historical trends. METHODS: As part of the Cardiovascular Health in Ambulatory Care Research Team "big data" initiative, we used information from multiple population-based databases to study 20-year temporal trends in hospitalizations and deaths from ASCVD. We calculated hospitalization rates for 6 ASCVD events (acute myocardial infarction, unstable angina, stroke, transient ischemic attack, peripheral arterial disease, and congestive heart failure) and death rates resulting from ischemic heart disease, cerebrovascular disease and circulatory and noncirculatory causes in adults aged 20-105 years in Ontario, Canada from 1994-2014 (to 2012 for deaths). RESULTS: The overall age-standardized composite rate of hospitalization for the 6 conditions or circulatory deaths declined 49.2% in men (from 1533.4 per 100,000 in 1994 to 778.3 per 100,000 in 2012) and 49.9% in women (from 1191.2 per 100,000 in 1994 to 596.2 per 100,000 in 2012). The annual rates of decline were least evident among those aged 20-49 years for both sexes. The overall self-reported prevalence of Ontarians living with heart disease or stroke, or both, declined nonsignificantly (P for trend = 0.19), from 7.7% to 7.1% for men, and significantly (P for trend = 0.01), from 7.3% to 5.8% for women, from 2001-2012. CONCLUSIONS: Striking declines in hospitalizations and deaths from ASCVD were observed in Ontario from 1994-2014. However, the limited progress observed in younger Canadians highlights the need for ongoing efforts aimed at preventing and treating ASCVDs and their associated risk factors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".