Effect of Adding Pharmacists to Primary Care Teams on Blood Pressure Control in Patients With Type 2 Diabetes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect of adding pharmacists to primary care teams on the management of hypertension and other cardiovascular risk factors in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: We conducted a randomized controlled trial with blinded ascertainment of outcomes within primary care clinics in Edmonton, Canada. Pharmacists performed medication assessments and limited history and physical examinations and provided guideline-concordant recommendations to optimize medication management. Follow-up contact was completed as necessary. Control patients received usual care. The primary outcome was a ≥10% decrease in systolic blood pressure at 1 year. RESULTS: A total of 260 patients were enrolled, 57% were women, the mean age was 59 years, diabetes duration was 6 years, and blood pressure was 129/74 mmHg. Forty-eight of 131 (37%) intervention patients and 30 of 129 (23%) control patients achieved the primary outcome (odds ratio 1.9 [95% CI 1.1-3.3]; P = 0.02). Among 153 patients with inadequately controlled hypertension at baseline, intervention patients (n = 82) were significantly more likely than control patients (n = 71) to achieve the primary outcome (41 [50%] vs. 20 [28%]; 2.6 [1.3-5.0]; P = 0.007) and recommended blood pressure targets (44 [54%] vs. 21 [30%]; 2.8 [1.4-5.4]; P = 0.003). The 10-year risk of cardiovascular disease, based on changes to the UK Prospective Diabetes Study Risk Engine, were predicted to decrease by 3% for intervention patients and 1% for control patients (P = 0.005). CONCLUSIONS: Significantly more patients with type 2 diabetes achieved better blood pressure control when pharmacists were added to primary care teams, which suggests that pharmacists can make important contributions to the primary care of these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it