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 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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".