Effective approaches to address the global cardiovascular disease burden
Bibliographic record
Abstract
PURPOSE OF REVIEW: Describe the global burden of cardiovascular disease (CVD), highlight barriers to evidence-based care and propose effective interventions based on identified barriers. RECENT FINDINGS: The global burden of CVD is increasing worldwide. This trend is steeper in lower income countries, where CVD incidence and fatality remains high. Risk factor control, around the world, remains poor, especially in lower and middle-income countries. Barriers at the patient, healthcare provider and health system have been identified. The use of multifaceted interventions that target identified contextual barriers to care, including increasing awareness of CVD and related risk, improving health policy (i.e. taxation of tobacco), improving the availability and affordability of fixed-dose combined medications and task-shifting of healthcare responsibilities are potential solutions to improve the global burden of CVD. SUMMARY: There is a need to address identified barriers using evidence-based and multifaceted interventions. Global initiatives, led by the World Heart Federation and the WHO, to facilitate the implementation of such interventions are underway.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".