Impact of outcome definitions on cardiovascular risk prediction in a contemporary primary prevention population
Bibliographic record
Abstract
BACKGROUND: Estimation of an individual's cardiovascular disease (CVD) risk may enhance risk discussion and treatment decisions. Yet, common cardiovascular outcomes such as heart failure (HF) or coronary revascularization are not included in the estimation of atherosclerotic cardiovascular disease (ASCVD) risk. Our objective was to determine the incidence of ASCVD in a contemporary primary prevention population with >10 years of follow-up and how incidence estimates change when incorporating additional cardiovascular endpoints. METHODS: We used the population-level Cardiovascular Health in Ambulatory Care Research Team database of all Ontario residents alive 1 January 2008, aged 30-99 years, and with no prior history of CVD. Individuals were followed to 31 December 2018 for incident first and recurrent cardiovascular events. ASCVD outcomes were defined by hospitalizations for myocardial infarction, stroke, and circulatory death, while global CVD outcomes also included hospitalizations for unstable angina, transient ischemic attacks, peripheral arterial disease, out-of-hospital cardiac arrests, HF, and coronary revascularization. RESULTS: Among 7496 165 individuals free of CVD, their mean age was 50 years (SD: 13.9 years) and 52.3% were women. After 11 years of follow-up, the rate of an incident ASCVD event was 3.95 per 1000 person-years, while the rate of a global CVD event was almost doubled at 6.67 per 1000 person-years. The most common additional first manifestations of CVD were HF, which accounted for 12.0% of additional events and coronary revascularization, which accounted for 12.7%. When considering first and recurrent events, the rate of ASCVD was 5.20 per 1000 person-years, while the rate of all global CVD events was more than double at 10.90 per 1000 person-years. This was mainly due to a higher proportion of recurrent HF (13.8%) and coronary revascularization (23.2%) events. CONCLUSIONS: ASCVD accounts for just over half of all preventable first cardiovascular events and even fewer first and recurrent cardiovascular events in contemporary practice. Estimating broader CVD endpoints may enhance risk-discussions with patients and improve informed decision-making.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".