Heart Failure in Sub-Saharan Africa: Current and Future Systems of Care
Bibliographic record
Abstract
Sub-Saharan Africa is undergoing rapid demographic and epidemiological transitions, fuelled by urbanisation, lifestyle changes and ageing populations. Consequently, the continent is faced with a ballooning burden of both communicable and non-communicable diseases (NCDs). Cardiovascular diseases are the leading cause of NCD-related mortality in SSA, with heart failure (HF) being the common phenotypic manifestation, afflicting a relatively younger population compared to other world regions. Even though the burden of HF is expected to double by 2030, HF systems of care remain poor in sub-Saharan Africa. Poor outcomes are especially aggravated by systemic barriers including under-resourced and siloed prevention, diagnostic, treatment and research efforts. Integrating HF care delivery through a systems approach and addressing risk factor prevention, screening and treatment across various tiers of care is crucial in abating the increasing burden of HF and NCDs. Further, a more patient-centred system of care that strengthens health financing, policies and system capabilities should be adopted to improve HF care and outcomes in sub-Saharan 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".