Data Science To Optimize Cardiovascular and Brain Health Promotion (2025-2026)

Background

Cardiovascular diseases are the world’s leading causes of death and long-term disability. Tragically, there are pervasive inequalities in risk factors, access to treatments and cardiovascular outcomes. It is essential to disentangle the complex relationships involved in order to intervene effectively and prevent and treat cardiovascular disease.

The advent of electronic medical records containing detailed information such as patient demographics, medication use and chronic medical conditions could offer a new source of data to better understand cardiovascular disease and its risk factors and treatment strategies. This, in turn, could allow clinicians and policymakers to prioritize preventive interventions for the patients at greatest risk.

Project Description

This project team will use large, national electronic health record databases to evaluate the risk factors and treatment strategies for cardiovascular disease. Building off the success of the related 2024-2025 project, the team will seek to identify new targets to prevent cardiovascular disease and predict risk of both cardiovascular disease and brain health impairment (e.g., cognitive decline).

Team members will also explore possible links between common medications and cardiovascular and brain health risk. Finally, the team will take advantage of natural experiments (such as adding medications to clinical practice guidelines) to understand the comparative effectiveness of different management strategies for cardiovascular disease prevention and brain health promotion.

The project is divided into three “threads:”

• In Thread 1, students are currently developing a novel risk score to predict recurrence of cardiovascular disease among patients with established cardiovascular disease. In 2025-2026, team members will validate that model using external data sources such as the UK Biobank and perform exploratory studies of risk factors for cardiovascular disease.
• In Thread 2, students are evaluating the efficacy and safety of a variety of medications. In 2025-2026, they will extend this work to evaluate synergistic or antagonistic effects that could give rise to unique risk profiles, especially among patients with baseline cardiovascular disease.
• In Thread 3, students are emulating complex cardiovascular outcomes trials using real-world data. In 2025-2026, team members will use health econometrics methods to understand how to optimize the design of cardiovascular systems of care to inform policy and clinical practice.

Anticipated Outputs

Peer-reviewed publications; grant applications; poster or oral presentations at the American Heart Association Scientific Sessions and/or International Stroke Conference

Student Opportunities

Ideally, this project team will include 3-6 graduate students and 8-12 undergraduate students. The project is open to any interested student. Students with interests or backgrounds such as computer science, economics, public policy, mathematics, statistical science, sociology, biology, public health, data science, clinical medicine or allied health professions are encouraged to apply, but there is no requirement that prospective applicants be majors in any of these disciplines.

The team will be divided into three subteams, but all team members will participate in discussions on all threads, and students will likely have opportunities to cross between threads as they advance their own projects. Graduate students will take on leadership of each thread, and undergraduates will be assigned focused projects within each thread. Meetings will typically be biweekly, in addition to individual meetings with each student.

Students will learn skills in data science, statistics, applied epidemiology and population health science. Students will receive support and one-on-one mentorship in statistical analysis, manuscript development and oral presentation of results. Team members will have the opportunity to participate in seminars, research days, journal clubs and invited speaker series through the Department of Neurology as well as clinical shadowing, depending on student interest and department policy. Collaboration with the UNC Department of Epidemiology will allow students to develop professional connections with epidemiologists and public health professionals, which may be particularly helpful for students interested in careers in epidemiology and public health.

Up to eight students may have the opportunity to travel to and submit first-author abstracts to the American Heart Association Scientific Sessions in November 2025.

See the related Data+ project for Summer 2025; there is a separate application process for students who are interested in this optional component. There is also an optional summer component (10 hours per week) for non-Data+ students.

Timing

Summer 2025 – Summer 2026

• Summer 2025 (optional): Wrap up 2024-2025 project milestones, such as preparation of abstracts for American Heart Association Scientific Sessions; conduct literature review and exploratory data analysis for 2025-2026 projects
• Fall 2025: Devise and commence statistical analysis; participate in structured seminar series on research methodology and clinical implications
• Spring 2026: Complete statistical analysis; prepare early drafts of manuscripts
• Summer 2026 (optional): Complete manuscript drafting; prepare abstracts for American Heart Association Scientific Sessions

Crediting

Academic credit available for fall and spring semesters; summer funding available

See related Data+ summer project, Data Science To Optimize Cardiovascular and Brain Health Promotion (2025), and earlier related team, Data Science to Optimize Cardiovascular Disease Prevention (2024-2025).