Bibliographic record
Abstract
In the National Cholesterol Education Program Adult Treatment Panel III guidelines published in 2001, estimation of cardiovascular risk was recommended based on the Framingham score for 10-year risk of myocardial infarction and the Canadian Cardiovascular Society currently recommends the Framingham total cardiovascular risk score. During development of joint guidelines released in 2013 by the American College of Cardiology (ACC) and American Heart Association (AHA), the decision was taken to develop a new risk score. This resulted in the ACC/AHA Pooled Cohort Equations Risk Calculator. This risk calculator, based on major National Heart, Lung, and Blood Institute-funded cohort studies, is designed to predict 10-year risk of 'hard' atherosclerotic cardiovascular disease (ASCVD) events, namely, nonfatal myocardial infarction, fatal coronary heart disease, nonfatal, or fatal stroke. Considerable strengths are its inclusion of stroke as an end point and race as a characteristic, which allows better risk prediction especially in African-American individuals, plus provision of lifetime ASCVD risk estimates for adults aged 20-59 years. Notable omissions from the risk factors include chronic kidney disease and any measure of social deprivation. An early criticism of the Pooled Cohort Equations Risk Calculator has been its alleged overestimation of ASCVD risk which, if confirmed in the general population, is likely to result in statin therapy being prescribed to many individuals at lower risk than the intended 7.5% 10-year ASCVD risk threshold for treatment in the joint ACC/AHA cholesterol guidelines. In this review we discuss the development of the new risk calculator, its strengths and weaknesses, and potential implications for its routine use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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; both teacher heads agree on what is shown here.
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".