Effect of nurse-directed hypertension treatment among First Nations people with existing hypertension and diabetes mellitus: the Diabetes Risk Evaluation and Microalbuminuria (DREAM 3) randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: First Nations people with diabetes mellitus and hypertension are at greater risk of renal and cardiovascular complications than are non-native patients because of barriers to health care services. We conducted this randomized controlled trial to assess whether a community-based treatment strategy implemented by home care nurses would be effective in controlling hypertension in First Nations people with existing hypertension and type 2 diabetes. METHODS: We compared 2 community-based strategies for controlling hypertension in First Nations people with existing hypertension and diabetes. In the intervention group, a home care nurse followed a predefined treatment algorithm of pharmacologic antihypertensive therapy. In the control group, treatment decisions were made by each subject's primary care physician. The primary outcome measure was the difference between the 2 groups in the change in systolic blood pressure after 12 months. Secondary outcome measures were the change in diastolic blood pressure over time, the change in urine albumin status and the incidence of adverse events. RESULTS: Both groups experienced a significant reduction in systolic blood pressure by the final visit (by 24.0 [standard deviation (SD) 13.5] mm Hg in the intervention group and by 17.0 [SD 18.6] mm Hg in the control group); p < 0.001 in each case). However, the difference between the 2 groups in this change was not significant. Patients in the intervention group had a larger decrease in diastolic blood pressure over time than did those in the control group (by 11.6 [SD 10.6] mm Hg v. 6.8 [SD 11.1] mm Hg respectively; p = 0.05). The groups did not differ significantly in terms of changes in urine albumin excretion or incidence of adverse events. INTERPRETATION: High rates of blood pressure control in the community were achieved in both groups in the DREAM 3 study. The addition of a home care nurse to implement a treatment strategy for blood pressure control was more effective in lowering diastolic than systolic blood pressure compared with home care visits for blood pressure monitoring alone and follow-up treatment by a family physician.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".