Expanding team-based care for hypertension and cardiovascular risk management with HEARTS in the Americas
Bibliographic record
Abstract
Cardiovascular diseases remain the leading cause of premature morbidity and mortality globally, with hypertension as their main modifiable risk factor. In Latin America and the Caribbean, hypertension affects more than 30% of adults, yet control rates remain alarmingly low. The HEARTS in the Americas Initiative, led by the Pan American Health Organization, promotes a model of team-based care to enhance risk management for hypertension and cardiovascular diseases within primary health care. Team-based care leverages the skills of diverse health professionals, including nurses, pharmacists and community health workers, to optimize resource allocation, task-sharing and care delivery. Evidence underscores the effectiveness of team-based care in improving blood pressure control, reducing hospitalizations and enhancing quality of life through strategies such as periodic follow up and medication titration. Despite its benefits, implementing team-based care faces cultural and systemic barriers. This special report outlines a policy framework to scale team-based care across the Region of the Americas, ensuring equitable access to high-quality, cost-effective prevention and care for cardiovascular diseases.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".