Predicting control of cardiovascular disease risk factors in South Asia using machine learning
Year: 2024
Type: article
Abstract: A substantial share of patients at risk of developing cardiovascular disease (CVD) fail to achieve control of CVD risk factors, but clinicians lack a structured approach to identify these patients. We applied machine learning to longitudinal data from two completed randomized controlled trials among 1502 individuals with diabetes in urban India and Pakistan. Using commonly available clinical data, we predict each individual's risk of failing to achieve CVD risk factor control goals or meaningful improvements in risk factors at one year after baseline. When classifying those in the top quartile of predicted risk scores as at risk of failing to achieve goals or meaningful improvements, the precision for not achieving goals was 73% for HbA1c, 30% for SBP, and 24% for LDL, and for not achieving meaningful improvements 88% for HbA1c, 87% for SBP, and 85% for LDL. Such models could be integrated into routine care and enable efficient and targeted delivery of health resources in resource-constrained settings.
Source: npj Digital Medicine
Institutions: Heidelberg University, Federal Institute for Population Research, Heidelberg Institute of Global Health, Emory University, Woodruff Health Sciences Center, Madras Diabetes Research Foundation, Dr. Mohan's Diabetes Specialities Centre, University of Washington, Public Health Foundation of India, All India Institute of Medical Sciences, Technical University of Munich, Ludwig-Maximilians-Universität München
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,790
Funders: U.S. Department of Health and Human Services, Vanderbilt University, Emory University, UnitedHealth Group, Public Health Foundation of India, National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute of Mental Health, Fogarty International Center, National Institute of Child Health and Human Development, Eunice Kennedy Shriver National Institute of Child Health and Human Development
OpenAlex ID: W4405222931