Abstract 1006: Impact of a Change to Global Cardiovascular Risk Estimation in Lipid-Lowering Guidelines: Findings From the National Health and Nutrition Examination Survey (NHANES) 2001 to 2006
Bibliographic record
Abstract
Background: Current ATP-III guidelines use absolute risk for hard coronary heart disease (CHD) to determine need for lipid-lowering therapy. It is unknown how many more US adults would potentially be eligible for therapy (i.e., 10-year risk ≥10%) with a broader focus on risk for global cardiovascular disease (CVD; all CHD, stroke, TIA, claudication and heart failure). Methods: We included 6,685 nonpregnant, nondiabetic, CVD-free participants aged 30 to 74 years from NHANES 2001–2006, representing 168 million US adults. We estimated 10-year predicted risk for hard CHD (using the Framingham risk score [FRS]) and global CVD (using the updated Framingham risk profile [UFRP]) in each participant. We compared the numbers of US adults in each of four predicted risk categories (0- 20%) by FRS vs. UFRP for ages 30 – 49 and 50 –74 years. Results: For those aged 50 –74 years (see Table), 27% have 10-year predicted risk for hard CHD ≥10% by FRS, whereas 47% have 10-year predicted risk for global CVD ≥10% using UFRP. In other words, 16 million men and women are changed from Conclusions: Use of an expanded endpoint of global CVD (rather than hard CHD) for risk estimation results in 20.2 million men and women moving from lower (
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".