Artificial Intelligence–Enabled Electrocardiogram for Atrial Fibrillation Identifies Cognitive Decline Risk and Cerebral Infarcts

Erika L. Weil, Peter A. Noseworthy, Camden L. Lopez, Alejandro A. Rabinstein, Paul A. Friedman, Zachi I. Attia, Xiaoxi Yao, Konstantinos C. Siontis, Walter K. Kremers, Georgios Christopoulos, Michelle M. Mielke, Prashanthi Vemuri, Clifford R. Jack, Bernard J. Gersh, Mary M. Machulda, David S. Knopman, Ronald C. Petersen, Jonathan Graff-Radford

Research output: Contribution to journalArticlepeer-review


Objective: To investigate whether artificial intelligence–enabled electrocardiogram (AI-ECG) assessment of atrial fibrillation (AF) risk predicts cognitive decline and cerebral infarcts. Patients and Methods: This population-based study included sinus-rhythm ECG participants seen from November 29, 2004 through July 13, 2020, and a subset with brain magnetic resonance imaging (MRI) (October 10, 2011, through November 2, 2017). The AI-ECG score of AF risk calculated for participants was 0-1. To determine the AI-ECG-AF relationship with baseline cognitive dysfunction, we compared linear mixed-effects models with global and domain-specific cognitive z-scores from longitudinal neuropsychological assessments. The AI-ECG-AF score was logit transformed and modeled with cubic splines. For the brain-MRI subset, logistic regression evaluated correlation of the AI-ECG-AF score and the high-threshold, dichotomized AI-ECG-AF score with infarcts. Results: Participants (N=3729; median age, 74.1 years) underwent cognitive analysis. Adjusting for age, sex, education, and APOE ɛ4-carrier status, the AI-ECG-AF score correlated with lower baseline and faster decline in global-cognitive z-scores (P=.009 and P=.01, respectively, non–linear-based spline-models tests) and attention z-scores (P<.001 and P=.01, respectively). Sinus-rhythm-ECG participants (n=1373) underwent MRI. As a continuous measure, the AI-ECG-AF score correlated with infarcts but not after age and sex adjustment (P=.52). For dichotomized analysis, an AI-ECG-AF score greater than 0.5 correlated with infarcts (OR, 4.61; 95% CI, 2.45-8.55; P<.001); even after age and sex adjustment (OR, 2.09; 95% CI, 1.06-4.07; P=.03). Conclusion: The AI-ECG-AF score correlated with worse baseline cognition and gradual global cognition and attention decline. High AF probability by AI-ECG-AF score correlated with MRI cerebral infarcts. However, most infarcts observed in our cohort were subcortical, suggesting that AI-ECG not only predicts AF but also detects other non-AF cardiac disease markers and correlates with small vessel cerebrovascular disease and cognitive decline.

Original languageEnglish (US)
Pages (from-to)871-880
Number of pages10
JournalMayo Clinic proceedings
Issue number5
StatePublished - May 2022

ASJC Scopus subject areas

  • General Medicine


Dive into the research topics of 'Artificial Intelligence–Enabled Electrocardiogram for Atrial Fibrillation Identifies Cognitive Decline Risk and Cerebral Infarcts'. Together they form a unique fingerprint.

Cite this