Key result
The WHO/ISH low information and high information risk prediction models disagreed on cardiovascular disease risk classification for 14.5% of patients in rural India (p <0.01).
Why the study?
Can a simplified point-of-care test using age and systolic blood pressure identify patients in rural India who would benefit from total cholesterol testing for WHO/ISH cardiovascular risk assessment?
Population
1,066 subjects from a cross-sectional study in rural Andhra Pradesh, India, with recorded blood cholesterol…
Comparison
Point-of-care machine learning models using age… vs Comparison between Low Information and High…
Design
Cross-sectional
Authors
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Model disagreement may cause inconsistent risk stratification in rural India; leaves open outcome validation of either WHO/ISH version.
Cross-Sectional (n=1,066)
Can a simplified point-of-care test using age and systolic blood pressure identify patients in rural India who would benefit from total cholesterol testing for WHO/ISH cardiovascular risk assessment?
p-value: p=<0.01
A simple point-of-care algorithm using age and systolic blood pressure can accurately identify patients in rural India who require total cholesterol testing for cardiovascular risk stratification, potentially saving resources in large-scale screening programs.
Raghu et al. (2015) conducted a cross-sectional in Cardiovascular disease risk (n=1,066). WHO/ISH low information (LI) risk prediction model vs. WHO/ISH high information (HI) risk prediction model was evaluated on Disagreement in CVD risk predicted by LI and HI WHO/ISH models (p=<0.01). The WHO/ISH low information and high information risk prediction models disagreed on cardiovascular disease risk classification for 14.5% of patients in rural India (p <0.01).
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