Candidate Interventions for Integrating Hypertension and Cardiovascular-Kidney-Metabolic Care in Primary Health Settings: HEARTS 2.0 Phase 1
Bibliographic record
Abstract
Background: HEARTS in the Americas is the regional adaptation of the WHO Global HEARTS Initiative, aimed at helping countries enhance hypertension and cardiovascular disease (CVD) risk management in primary care settings. Its core implementation tool, the HEARTS Clinical Pathway, has been adopted by 28 countries. To improve the care of hypertension, diabetes, and chronic kidney disease (CKD), HEARTS 2.0 was developed as a three-phase process to integrate evidence-based interventions into a unified care pathway, ensuring consistency across fragmented guidelines. This paper focuses on Phase 1, highlighting targeted interventions to improve and update the HEARTS Clinical Pathway. Methods: First, the coordinating group defined the project's scope, objectives, principles, methodological framework, and tools. Second, international experts from different disciplines proposed interventions to enhance the HEARTS Clinical Pathway. Third, the coordinating group harmonized these proposals into unique interventions. Fourth, experts appraised the appropriateness of the proposed interventions on a 1-to-9 scale using the adapted RAND/UCLA Appropriateness Method. Finally, interventions with a median score above 6 were deemed appropriate and selected as candidates to enhance the HEARTS Clinical Pathway. Results: Building on the existing HEARTS Clinical Pathway, 45 unique interventions were selected, including community-based screening, early detection and management of risk factors, lower blood pressure thresholds for diagnosing hypertension in high-CVD-risk patients, reinforcement of single-pill combination therapy, inclusion of sodium-glucose cotransporter-2 inhibitors for patients with diabetes, CKD, or heart failure, expanded roles for non-physician health workers in team-based care, and strengthened clinical documentation, monitoring, and evaluation. Conclusion: HEARTS 2.0 Phase 1 identifies key interventions to integrate and improve hypertension and cardiovascular-kidney-metabolic care within primary care, enabling their seamless incorporation into a unified and effective clinical pathway. This process will inform an update to the HEARTS Clinical Pathway, optimizing resources, reducing care fragmentation, improving care delivery, and advancing health equity, thereby supporting global efforts to combat the leading causes of death and disability.
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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 | 0.070 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".