Facilitating Harmonization of Variables from the Framingham, MESA, ARIC, and REGARDS Studies Through a Metadata Repository

May 21, 2024
12:00 pm to 1:00 pm

Event sponsored by:

AI Health
+DataScience (+DS)
Biomedical Engineering (BME)
Biostatistics and Bioinformatics
Computer Science
Division of Cardiology
Duke Clinical and Translational Science Institute (CTSI)
Electrical and Computer Engineering (ECE)


Duke AI Health



Presented by: • Pratheek Mallya, MS; Product Development Manager, Data Science; American Heart Association • Chuan Hong, PhD; Assistant Professor of Biostatistics & Bioinformatics, Duke University School of Medicine Moderated by: • Andrew Olson, MPP, Associate Director, Policy Strategy and Solutions for Health Data Science
Research in stroke prevention requires inclusion of a broad range of data sets from different cohorts. Integrating and harmonizing different data sources are essential to increase generalizability, sample size, and representation of understudied populations-strengthening the evidence for the scientific questions being addressed. To that end, Duke AI Health and the American Heart Association have developed an open metadata repository for the harmonization of stroke risk prediction variables from four large, National Institutes of Health (NIH)-funded cohort studies: REGARDS (Reasons for Geographic and Racial Differences in Stroke), FHS (Framingham Heart Study), MESA (Multi-Ethnic Study of Atherosclerosis), and ARIC (Atherosclerosis Risk in Communities). In this webinar, we will present an overview of the metadata repository and walk through its features, including variable distributions, collection time periods, and search filters. We will also discuss several use cases for incorporating this resource into your research for harmonizing data.