Multidisciplinary approaches to the management of high blood pressure
Bibliographic record
Abstract
PURPOSE OF REVIEW: Studies on collaborative and multidisciplinary approaches to the management of hypertension published in the past 2 years are summarized. Expanding scopes of practice for nonphysician health professionals, a need to build capacity in the healthcare system, and a movement toward multidisciplinary care warrant an examination of the evidence in this area. RECENT FINDINGS: Multidisciplinary care for hypertension management, across the majority of studies identified, resulted in improved blood pressure (BP) outcomes and the timeliness of achieving treatment targets. Interventions involving therapeutic decision-making by nonphysician health professionals consistently resulted in significant BP improvements compared with usual care, whereas more passive approaches, such as education and lifestyle monitoring programs, were unable to significantly benefit participants' BP. SUMMARY: Our findings support recent efforts to integrate collaborative care approaches into chronic disease management, with the strongest evidence for pharmacist care. Expanding scopes of practice and clinical decision-making protocols for nurses, pharmacists, dietitians, and physiotherapists have the potential to further improve hypertension care.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".