ECG abnormalities are strongly associated with CVD outcomes in low-risk individuals using the PREVENT risk equation. uri icon

Overview

abstract

  • BACKGROUND: Resting electrocardiogram (ECG) is not currently recommended as part of cardiovascular disease (CVD) risk assessment, although accumulating evidence suggests a potential role. OBJECTIVE: To examine the association between ECG abnormalities and incident CVD events as assessed by the 2023 Predicting Risk of Cardiovascular Disease Events (PREVENT) equations. DESIGN: Secondary data analysis from the REasons for Geographic And Racial Differences in Stroke (REGARDS) prospective cohort, including study participants without a baseline CVD. EXPOSURE: ECG abnormalities were classified by Minnesota Code (MC) as normal, any minor, or major abnormality at baseline (2003-2007). OUTCOME: Participants were followed for expert adjudicated incident CVD events through December 31, 2021. RESULTS: Among 19,173 participants (mean age at baseline of 63.7 years; 57.8% were female). According to the PREVENT risk equations, 39.4% were classified as <7.5% 10-year risk CVD risk, 44.6% as 7.5-20% risk, and 16.0% as >20% risk. Overall, 47.0% had normal ECG, 44.0% had any minor abnormality, and 9.0% had any major abnormality. During follow-up, CVD events occurred in 12.4% of participants with normal ECG, 17.0% of those with any minor abnormality, and 25.4% of those with any major abnormality. Compared to those without ECG abnormality, the adjusted HR for incident CVD were 1.19 (95% CI 1.10-1.29) for any minor abnormality, and 1.53 (1.36-1.72) for any major ECG abnormality. In the <7.5% risk group, 43.6% had at least one ECG abnormality; in this risk group compared to those without ECG abnormality, the HR for incident CVD associated with any major ECG abnormality, present in 5.0% of the <7.5% risk group, was 1.87 (95% CI 1.34-2.62), The HR for any minor ECG abnormalities, present in 38.6% was 1.13 ( 95% CI 0.93 - 1.37). CONCLUSION: ECG abnormalities were associated with risk of CVD events across PREVENT risk groups. A substantial proportion of low-risk participants (according to the PREVENT equation) had ECG abnormalities and associated elevated risk. This supports the potential for using ECG to identify a subgroup of low-risk patients who may benefit from more aggressive primary prevention especially with major ECG abnormalities. Addition of electrocardiographic evaluation to the PREVENT risk equations may improves cardiovascular risk discrimination.

publication date

  • March 31, 2026

Identity

PubMed Central ID

  • PMC13060395

Digital Object Identifier (DOI)

  • 10.64898/2026.03.28.26349408

PubMed ID

  • 41959784