Association Between Electrocardiographic Age and Cardiovascular Events in Community Settings: The Framingham Heart Study

Author:

Brant Luisa C.C.12ORCID,Ribeiro Antônio H.3ORCID,Pinto-Filho Marcelo M.2ORCID,Kornej Jelena4ORCID,Preis Sarah R.5ORCID,Fetterman Jessica L.6ORCID,Eromosele Oseiwe B.7,Magnani Jared W.8ORCID,Murabito Joanne M.910ORCID,Larson Martin G.59ORCID,Benjamin Emelia J.1194ORCID,Ribeiro Antonio L.P.12ORCID,Lin Honghuang12ORCID

Affiliation:

1. Faculty of Medicine (L.C.C.B., A.L.P.R.), Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.

2. Telehealth Center, Hospital das Clínicas (L.C.C.B., M.M.P.-F., A.L.P.R.), Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.

3. Department of Information Technology, Uppsala University, Sweden (A.H.R.).

4. Section of Cardiovascular Medicine, Boston Medical Center (J.K., E.J.B.)

5. Department of Biostatistics (S.R.P., M.G.L.), Boston University School of Public Health, MA.

6. Evans Department of Medicine and Whitaker Cardiovascular Institute (J.L.F.)

7. Boston University Chobanian and Avedisian School of Medicine, MA (O.B.E.).

8. Department of Medicine, Center for Research on Health Care, University of Pittsburgh, PA (J.W.M.).

9. Framingham Heart Study, Framingham, MA (J.M.M., M.G.L., E.J.B.).

10. Section of General Internal Medicine, Boston Medical Center (J.M.M.)

11. Department of Epidemiology (E.J.B.), Boston University School of Public Health, MA.

12. Department of Medicine, University of Massachusetts Chan Medical School, Worcester (H.L.).

Abstract

BACKGROUND: Deep neural networks have been used to estimate age from ECGs, the electrocardiographic age (ECG-age), which predicts adverse outcomes. However, this prediction ability has been restricted to clinical settings or relatively short periods. We hypothesized that ECG-age is associated with death and cardiovascular outcomes in the long-standing community-based FHS (Framingham Heart Study). METHODS: We tested the association of ECG-age with chronological age in the FHS cohorts in ECGs from 1986 to 2021. We calculated the gap between chronological and ECG-age (Δage) and classified individuals as having normal, accelerated, or decelerated aging, if Δage was within, higher, or lower than the mean absolute error of the model, respectively. We assessed the associations of Δage, accelerated and decelerated aging with death or cardiovascular outcomes (atrial fibrillation, myocardial infarction, and heart failure) using Cox proportional hazards models adjusted for age, sex, and clinical factors. RESULTS: The study population included 9877 FHS participants (mean age, 55±13 years; 54.9% women) with 34 948 ECGs. ECG-age was correlated to chronological age (r=0.81; mean absolute error, 9±7 years). After 17±8 years of follow-up, every 10-year increase of Δage was associated with 18% increase in all-cause mortality (hazard ratio [HR], 1.18 [95% CI, 1.12–1.23]), 23% increase in atrial fibrillation risk (HR, 1.23 [95% CI, 1.17–1.29]), 14% increase in myocardial infarction risk (HR, 1.14 [95% CI, 1.05–1.23]), and 40% increase in heart failure risk (HR, 1.40 [95% CI, 1.30–1.52]), in multivariable models. In addition, accelerated aging was associated with a 28% increase in all-cause mortality (HR, 1.28 [95% CI, 1.14–1.45]), whereas decelerated aging was associated with a 16% decrease (HR, 0.84 [95% CI, 0.74–0.95]). CONCLUSIONS: ECG-age was highly correlated with chronological age in FHS. The difference between ECG-age and chronological age was associated with death, myocardial infarction, atrial fibrillation, and heart failure. Given the wide availability and low cost of ECG, ECG-age could be a scalable biomarker of cardiovascular risk.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine

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