Key result
The Jos cardiovascular disease risk app correlated more strongly with CIMT-determined high atherosclerotic risk than the Framingham Risk Score (correlation coefficient 0.448 vs 0.300).
Why the study?
Existing cardiovascular risk algorithms can misclassify risk, with up to 60% of cardiovascular events occurring in individuals not categorized as high risk.
Does a new CVD risk algorithm incorporating novel anthropometric indices improve risk classification compared to the Framingham Risk Score in native Africans?
Observational (n=221)
Does a new CVD risk algorithm incorporating novel anthropometric indices improve risk classification compared to the Framingham Risk Score in native Africans?
Absolute Event Rate: 0.448% vs 0.3%
A novel CVD risk algorithm incorporating anthropometric indices improved atherosclerotic risk classification compared to the Framingham Risk Score in an African population.
Background: Algorithms determining cardiovascular disease (CVD) risk can misclassify risk in the population. With existing algorithms, up to 60% of cardiovascular events occur in individuals not classified as high risk. We therefore decided to improve on existing tools by including new anthropometric indices in a new algorithm. Methods: We secondarily analysed data involving demographic, anthropometric, biochemical and carotid intima media thickness (CIMT) measurements. An algorithm utilizing 10 risk factors: age, abdominal height (AH), body surface index (BSI), systolic blood pressure (SBP), diastolic blood pressure (DBP), gender, family history of CVD, alcohol use, physical inactivity and smoking was designed. Using the CIMT as a standard with the cut of value of ≥0.078 cm for high atherosclerotic risk we compared our new tool with Framingham Risk Score (FRS). Results: With our new algorithm, 24/221 (10.9%) were at high risk with 109 and 88 at low and intermediate risks respectively. Using the FRS, 218/221 were at low risk; only 3 being in the intermediate and high risk. Both risk algorithms correlated significantly with CIMT determined risk but correlation coefficient was more for the new (0.448) than the FRS (0.300). Conclusions: Misclassification of a disease risk presents dire consequences. Our new risk detection tool, among native Africans will close the gap created by existing algorithms not capturing adequately people of African ethnicity.
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Sirisena et al. (2022) conducted an observational in Atherosclerotic cardiovascular diseases (n=221). Jos cardiovascular disease risk app vs. Framingham Risk Score was evaluated on Correlation with CIMT determined risk. The Jos cardiovascular disease risk app correlated more strongly with CIMT-determined high atherosclerotic risk than the Framingham Risk Score (correlation coefficient 0.448 vs 0.300).
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