Pharmacist interventions to improve hypertension management among patients with diabetes: a systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Improving blood pressure (BP) control is of major importance among patients with diabetes, due to their high risk of micro- and macrovascular complications. Community-based models of care with the involvement of pharmacists and other nonphysician healthcare providers can help manage hypertension. We aimed to estimate the effectiveness of pharmacist interventions, alone or in collaboration, on BP among outpatients with diabetes and hypertension. METHODS: We conducted systematic searches of randomized controlled trials (RCTs) assessing the effect of pharmacist interventions on BP among outpatients with hypertension and diabetes compared to usual care. The outcome was the systolic and diastolic BP change or BP control. We performed a meta-analysis with a random effects model to estimate mean differences in BP or relative risk of BP control, with 95% confidence intervals (CIs). The protocol was registered in PROSPERO (CRD42021279751) and published in an open-access peer-reviewed journal. RESULTS: Out of 2330 study records identified by electronic database searching, we included 12 studies in the systematic review, with 5,256 participants (control 2,906; intervention 2,350), published between 2002 and 2022. In comparison with usual care, mean systolic and diastolic BP were reduced after pharmacist interventions by -7.2 mmHg (95% CI: -12.5 to -1.9; I2 = 87%) and − 4.1 mmHg (95% CI: -6.9 to -1.4; I2 = 0%), respectively. BP control was improved after pharmacist intervention (relative risk: 1.76, 95% CI: 1.39 to 2.24; I2 = 50%). Analyses restricted to relatively large or high-quality studies yielded consistent but slightly lower estimates. CONCLUSION: Pharmacist interventions improve BP control in patients with diabetes and hypertension. PROSPERO REGISTRATION NUMBER: CRD42021279751.
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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 | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.034 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".