Abstract 10426: One Year Impact of the 2013 Cholesterol Guidelines on Patterns of Lipid Lowering Treatment
Bibliographic record
Abstract
Background: In 2013, national organizations issued new cholesterol guidelines to emphasize evidence-based treatment with moderate- to high-dose statins for patients at high risk for atherosclerotic cardiovascular disease (ASCVD), which includes coronary heart disease, stroke, and peripheral arterial disease. Whether these new guidelines have influenced patterns of treatment one year after their dissemination is unknown. Methods: Using pharmacy and medical claims from a large U.S. health insurance organization, we identified 610,535 adult patients with ASCVD (n=301,440) or diabetes mellitus (n=309,095) and examined statin treatment rates before and one year after the new cholesterol guidelines. Among patients receiving statins post-guidelines, we also evaluated whether patients were treated with guideline-recommended intensity of statin therapy. A standardized difference (SD) of at least 10% was required to declare the effect size meaningful. Results: Overall, there was no change in statin treatment rates for patients with ASCVD (48.0% before guidelines vs. 47.3% after, SD [1.4]) or diabetes (50% vs. 51.5% after, SD [2.4]). Statin initiation rates among patients not on statins pre-guidelines were 10.1% in patients with ASCVD and 14.3% in patients with diabetes, and these gains were offset by 13.0% and 12.2% statin discontinuation rates among ASCVD and diabetes patients, respectively. Among patients taking statins one year post-guidelines, 80% of patients with ASCVD and < 75 years of age were not on guideline-recommended high-intensity statin therapy, whereas >75% of patients with ASCVD and >75 years of age or patients with diabetes were on moderate- or high-intensity statin treatment. Conclusion: One year after dissemination of the new 2013 cholesterol guidelines, overall treatment rates with statins among patients with ASCVD and diabetes have not changed appreciably, and many patients remain either untreated or under-treated. Character Count: 1683
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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 | 0.007 | 0.039 |
| 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) | 0.003 | 0.001 |
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".