Greater Effect of Enhanced Pharmacist Care on Cholesterol Management in Patients with Diabetes Mellitus: A Planned Subgroup Analysis of the Study of Cardiovascular Risk Intervention by Pharmacists (SCRIP)
Bibliographic record
Abstract
STUDY OBJECTIVE: To determine the effect of enhanced pharmacist care on cholesterol management in patients with and without diabetes mellitus. METHODS: We conducted a planned subgroup analysis of the Study of Cardiovascular Risk Intervention by Pharmacists (SCRIP), a 54-center randomized trial of pharmacist intervention compared with usual care in patients at high risk for cardiovascular events. The patients involved had atherosclerotic disease or diabetes. We compared the effect of pharmacist intervention in patients with and without diabetes. The primary end point was a composite of performing a fasting cholesterol profile, or adding or increasing the dosage of a cholesterol-lowering drug. Secondary end points were individual components of the primary end point and change in 10-year risk for cardiovascular events, using the Framingham risk equation. RESULTS: Of the 675 patients enrolled in the SCRIP study, 294 (44%) had diabetes. Enhanced pharmacist care had a more beneficial effect on cholesterol management in those with diabetes (odds ratio [OR] 4.8) than without diabetes (OR 2.1), p=0.01. Secondary end points showed similar trends, and reduction in Framingham risk was greater in patients with diabetes than without. CONCLUSION: Pharmacist intervention for dyslipidemia appears to have a greater impact in patients with diabetes. Results of this substudy suggest that pharmacists should target this patient group for interventions in cholesterol risk management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".