Increasing Prevalence and Incidence of Atherosclerotic Cardiovascular Disease in Adult Patients in Ontario, Canada From 2002 to 2018
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease is the second-leading cause of death in Canada. However, limited data are available on the prevalence of atherosclerotic cardiovascular disease (ASCVD) in Canada. The study objective was to describe the incidence and prevalence of ASCVD in adult patients in Ontario, Canada, and to evaluate temporal trends for subsequent ASCVD events among those with new-onset ASCVD. METHODS: This retrospective, observational study identified ASCVD incidence and prevalence data from the Institute for Clinical Evaluative Sciences Data Repository for adults from Ontario. Overall prevalence was established for the period from 2002 to 2018. Incident cases from April 1, 2005 to March 2016 were then identified, and followed up to 2018. Primary outcomes were date and type of index event/procedure, patient characteristics/baseline demographics, and comorbidities. Secondary outcomes assessed were time from first to second ASCVD event, subsequent event(s) and/or mortality, and type of subsequent event(s) relative to the type of index/primary event. RESULTS: A total of 1,042,621 eligible prevalent ASCVD cases were identified; of these, 743,309 patients (69%) were newly diagnosed with incident ASCVD. The 10-year prevalence rates for all ASCVD subtypes increased over the study period. Overall event incidence rates per 1000 person-years were mostly stable or increased. Among incident cases, 50% experienced subsequent events over the study period. CONCLUSIONS: This observational study demonstrated increasing prevalence and high incidence of new ASCVD diagnoses in adults from Ontario, over the study period. These data, together with the substantial number of subsequent events in ASCVD patients, demonstrate significant clinical burden of this disease in Ontario.
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".