Diagnosing hypertension in Indigenous Canadians (<scp>DREAM</scp>‐<scp>GLOBAL</scp>): A randomized controlled trial to compare the effectiveness of short message service messaging for management of hypertension: Main results
Bibliographic record
Abstract
Hypertension, the leading cause of cardiovascular morbidity and mortality, affects more than 1 billion people globally. The rise in mobile health in particular the use of mobile phones and short message service (SMS) to support disease management provides an opportunity to improve hypertension awareness, treatment, and control, in remote and vulnerable patient populations. The primary objective of this randomized controlled study was to assess the effect of active (with hypertension specific management SMS) or passive (health behaviors SMS alone) on the difference in blood pressure (BP) reduction between the active and passive SMS groups in hypertensive Canadian First Nations people from six rural and remote communities. Pragmatic features of the study included shifting of BP measures to non-medical health workers. Despite an overall reduction in BP over the study, there was no difference in the BP change between groups from baseline to final for systolic 0.8 (95% CI -4.2 to 5.8 mm Hg) or diastolic -1.0 (95% CI -3.7 to 1.8 mm Hg, P = 0.5) BP. Achieved BP control was 37.5% (25.6%-49.4%, 95% CI) in the active group and 32.8% (20.6%-44.8%, 95% CI) in the passive group (difference in proportions -4.74% (-21.7% to 12.2%, 95% CI, P = 0.6). The study looked at changes in health services delivery, mobile health technologies, and patient engagement to support better management of hypertension in Canadian First Nations communities. The active hypertension specific SMS did not lead to improvements in BP control.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.007 | 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".