Risk Factors Associated With Myocardial Infarction in Africa
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease (CVD) is rising in low-income countries. However, the impact of modifiable CVD risk factors on myocardial infarction (MI) has not been studied in sub-Saharan Africa (SSA). Therefore, we conducted a case-control study among patients with acute MI (AMI) in SSA to explore its association with known CVD risk factors. METHODS AND RESULTS: First-time AMI patients (n=578) were matched to 785 controls by age and sex in 9 SSA countries, with South Africa contributing approximately 80% of the participants. The relationships between risk factors and AMI were investigated in the African population and in 3 ethnic subgroups (black, colored, and European/other Africans) and compared with those found in the overall INTERHEART study. Relationships between common CVD risk factors and AMI were found to be similar to those in the overall INTERHEART study. Modeling of 5 risk factors (smoking history, diabetes history, hypertension history, abdominal obesity, and ratio of apolipoprotein B to apolipoprotein A-1) provided a population attributable risk of 89.2% for AMI. The risk for AMI increased with higher income and education in the black African group in contrast to findings in the other African groups. A history of hypertension revealed higher MI risk in the black African group than in the overall INTERHEART group. CONCLUSIONS: Known CVD risk factors account for approximately 90% of MI observed in African populations, which is consistent with the overall INTERHEART study. Contrasting gradients found in socioeconomic class, risk factor patterns, and AMI risk in the ethnic groups suggest that they are at different stages of the epidemiological transition.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| 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 it