Primary Prevention Statins in Older Adults: Personalized Care for a Heterogeneous Population
Bibliographic record
Abstract
The 2018 American College of Cardiology/American Heart Association guidelines on the management of cholesterol acknowledge a lack of robust randomized clinical trial data to support routine use of statin therapy for primary prevention in adults older than 75 years. Shared decision making is emphasized because potential recommendations should reflect limitations of the current data, as well as heterogeneity of the older adult population, spanning the robust to the most frail. Although the National Institute on Aging recently funded PRagmatic EValuation of EvENTs And Benefits of Lipid-Lowering in OldEr Adults (PREVENTABLE), a trial to study benefits of statins in very old adults, data are not anticipated for 5 years. Thus interim guidance is essential. Furthermore, even when PREVENTABLE is completed, individual idiosyncrasies among older adults suggest that decisions for each patient will still need to be personalized, relative to their unique clinical situation. In this article, we present three case studies to highlight dynamics that commonly impact choices regarding statins in older adults. Details underlying shared decision making are also described including the evolving application of coronary artery calcium to inform this practice. J Am Geriatr Soc 68:467-473, 2020.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".