Abstract 18274: Under Use of Statins and LDL-C Control Among People With a Framingham 10-Year Coronary Heart Disease Risk > 20%
Bibliographic record
Abstract
Statins reduce the incidence of coronary heart disease (CHD) in individuals with a history of CHD or risk equivalents. A 10-year CHD risk >20% is considered a CHD risk equivalent but is frequently not estimated. We studied the use of statins and control of LDL-C among participants with a history of CHD or CHD risk equivalents in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study (n=30,239) The 8,812 participants with CHD or risk equivalents were categorized into four mutually exclusive groups: (1) history of CHD, (2) no history of CHD but with a history of stroke and/or aortic aneurysm, (3) no history of CHD, stroke or aortic aneurysm but with diabetes mellitus, or (4) no history of the conditions listed in (1) through (3) but with a Framingham 10-year CHD risk > 20% at baseline. Lipids were measured after an overnight fast, LDL-C was calculated using the Friedewald equation, and statin use was assessed through pill bottle review during an in-home study visit. The mean age of study participants was 65 years (SD=9), 45% were women and 46% were black. In fully adjusted models, compared to those with a history of CHD, the use of statins was statistically significantly lower among people with a history of stroke/aortic aneurysm, history of diabetes, and especially 10-year CHD risk > 20% (Table). Among high risk participants taking statins, the prevalence of LDL-C < 100 mg/dL was similar for those with a history of CHD, a history of stroke/aortic aneurysm and diabetes, but participants with a 10-year CHD risk > 20% were less likely to have an LDL-C < 100 mg/dL. These data suggest many people with high CHD risk, especially those with a FRS >20%, were not receiving guideline-concordant lipid-lowering therapy and quality improvement efforts should focus on this group.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".