Primary Prevention Drug Therapy: Can It Meet Patients’ Requirements for Reduced Risk?
Bibliographic record
Abstract
The objective was to identify, in primary prevention, patients whose "required risk reduction" (ReqRR) is greater than the "achievable risk reduction" (ARR) that cholesterol-lowering or antihypertensive medication could provide. Individualized estimates of 10-year coronary heart disease or stroke risk were derived for 66 hypercholesterolemic (HC) and 64 hypertensive (HT) patients without symptomatic cardiovascular disease. These estimates were used in trade-off tasks identifying each individual's ReqRR. Then individual ARRs were estimated (in HC patients by assuming total cholesterol/high density lipoprotein ratio reductions to 5.0; in HT patients by assuming systolic blood pressure reductions to 120 mmHg). 12 (18%) HC and 12 (19%) HT subjects would refuse medication regardless of the risk reduction offered. Of the remaining patients, 15/54 (28%; 95% C.I.:16-40%) HC and 19/52 (37%; 95% C.I: 24-51%) HT subjects were "over-requirers," in that their ReqRR/ARR ratio was 1.5. There maybe a notable proportion of patients whose ReqRR is considerably greater than what is achievable, implying that decision aids may help individuals clarify preferences about accepting/refusing medication for the primary prevention of cardiovascular disease.
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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 | 0.012 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 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".