How to Improve Awareness, Treatment, and Control of Hypertension in Africa, and How to Reduce Its Consequences: A Call to Action From the World Hypertension League
Bibliographic record
Abstract
Hypertension is the leading preventable risk factor for cardiovascular diseases and disability globally. In low- and middle-income countries hypertension has a major social impact, increasing the disease burden and costs for national health systems. The present call to action aims to stimulate all African countries to adopt several solutions to achieve better hypertension management. The following 3 goals should be achieved in Africa by 2030: (1) 80% of adults with high blood pressure in Africa are diagnosed; (2) 80% of diagnosed hypertensives, that is, 64% of all hypertensives, are treated; and (3) 80% of treated hypertensive patients are controlled. To achieve these aims, we call on individuals and organizations from government, private sector, health care, and civil society in Africa and indeed on all Africans to undertake a few specific high priority actions. The aim is to improve the detection, diagnosis, management, and control of hypertension, now considered to be the leading preventable killer in Africa.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".