Standardized treatment to improve hypertension control in primary health care: The HEARTS in the Americas Initiative
Bibliographic record
Abstract
Hypertension is the leading risk factor for cardiovascular disease (CVD) worldwide. Despite the availability of effective antihypertensive medications, the control of hypertension at a global level is dismal, and consequently, the CVD burden continues to increase. In response, countries in Latin America and the Caribbean are implementing the HEARTS in the Americas, a community-based program that focuses on increasing hypertension control and CVD secondary prevention through risk factor mitigation. One key pillar is the implementation of a standardized hypertension treatment protocol supported by a small, high-quality formulary. This manuscript describes the methodology used by the HEARTS in the Americas program to implement a population-based standardized hypertension treatment protocol. It is rooted in a seamless transition from existing treatment practices to best practice using pharmacologic protocols built around a core set of ideal antihypertensive medications. In alignment with recent major hypertension guidelines, the HEARTS in the Americas protocols call for the rapid control of blood pressure, through the use of two antihypertensive medications, preferably in the form of a single pill, fixed-dose combination, in the initial treatment of hypertension. To date, the HEARTS in the Americas program has seen the improvement in antihypertensive medication formularies and the establishment of pharmacologic treatment protocols tailored to individual participating countries. This has translated to significant increases in hypertension control rates post-program implementation in these jurisdictions. Thus, the HEARTS in the Americas program could serve as a model, for not only the Americas Region but globally, and ultimately decrease the burden of CVD.
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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 | 0.087 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".