HEARTS en las Américas: innovaciones para mejorar el manejo de la hipertensión y del riesgo cardiovascular en la atención primaria
Bibliographic record
Abstract
Global Hearts is the flagship initiative of the World Health Organization to reduce the burden of cardiovascular diseases, the leading cause of death and disability worldwide. HEARTS in the Americas Initiative is the regional adaptation that envisions HEARTS as the model for cardiovascular disease risk management, including hypertension and diabetes, in primary health care in the Americas by 2025. This initiative is entering its sixth year of implementation and now includes 22 countries and 1 380 primary health care centers. The objectives of this report are three-fold. First, it describes the emergence and the main elements of HEARTS in the Americas. Secondly, it summarizes the main innovations developed to catalyze and sustain implementation of the initiative. These innovations include: a) introduction of hypertension control drivers; b) development of a comprehensive and practical clinical pathway; c) development of a strategy to improve the accuracy of blood pressure measurement; d) creation of a monitoring and evaluation platform; and e) development of a standardized set of training and education resources. Thirdly, this report discusses future priorities of the initiative. The goal of implementing these innovative and pragmatic solutions is to create a more effective health system and shift the focus of cardiovascular and hypertension programs from the highly specialized care level to primary health care. In addition, HEARTS in the Americas can serve as a model for more comprehensive, effective, and sustainable noncommunicable disease prevention and treatment practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".