AI-ECG-detected grade 3 left ventricular diastolic dysfunction was independently associated with a higher risk of new-onset atrial fibrillation (aHR 2.24; 95% CI 2.02-2.48).
Cohort (n=97,023)
Does AI-ECG-detected left ventricular diastolic dysfunction predict long-term risk of new-onset atrial fibrillation in patients without prior AF?
AI-ECG-detected grade 2 and 3 left ventricular diastolic dysfunction independently predicts long-term risk of new-onset atrial fibrillation, regardless of LVEF and clinical HF status.
Hazard Ratio: 2.24 (95% CI 2.02–2.48)
Abstract Background Heart failure (HF) and atrial fibrillation (AF) are intertwined, sharing common risk factors and influencing each other in a reciprocal manner. While left ventricular diastolic dysfunction (LVDD) stands as a hallmark of HF's hemodynamic profile, its direct correlation with heightened AF risk remains uncertain. Our recent validation of an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm for LVDD detection has opened new avenues. Yet, whether AI-ECG-detected LVDD correlates with long-term AF risk remains unexplored. Methods We performed a retrospective study among all patients with a comprehensive LVDD assessment from the test population of the AI-ECG LVDD study between September 2001 and June 2022. Patients with prior documented AF according to health records or previous ECG were excluded. Patients were classified by AI-ECG as normal diastolic function (DF), grade 1 (G1), grade 2 (G2), or grade 3 (G3) LVDD. We assessed the risk of AF across AI-ECG LVDD grade, with normal DF as reference, with competing risk models. Results Of 97,023 patients free of AF at baseline, 63,533 (65.4%), 10,776 (11.1%), 18,940 (19.5%), and 3,774 (3.9%) were classified as normal DF, G1-LVDD, G2-LVDD, and G3-LVDD, respectively. Worse AI-ECG LVDD was associated with older age, lower left ventricular ejection fraction (LVEF), and higher rates of HF, diabetes, hypertension, chronic pulmonary disease, renal failure, and cardiovascular disease (p-of-trend0.001 for all). Over a median follow-up of 4.8 years (interquartile range 1.8-9.2 years), new-onset AF occurred in 6,795 (7.0%) patients. In multivariable survival analysis, adjusted to multiple risk factors including LVEF and clinical HF, G2 and G3 LVDD, representing patients with high filling pressures, were independently associated with a higher AF-risk G2-LVDD: adjusted hazard ratio (aHR) 1.64 (95% confidence interval (95%CI) 1.52-1.73), G3-LVDD: aHR 2.24 (95%CI 2.02-2.48). Conclusion The AI-ECG LVDD algorithm independently predicts long-term AF risk, regardless of LVEF and clinical HF status, highlighting its potential for identifying high-risk populations and guiding proactive monitoring and management.
“Our findings suggest that a routine assessment of diastolic function can provide a powerful glimpse into a person's future heart health. Each worsening grade of diastolic dysfunction was associated with a progressively higher risk when compared with normal function. These findings highlight the critical role of diastolic function beyond heart failure diagnosis, supporting earlier testing and timely interventions aimed at reducing risk.”
Tsaban et al. (Tue,) conducted a cohort in Left ventricular diastolic dysfunction (n=97,023). AI-ECG-detected LVDD (Grade 3) vs. Normal diastolic function was evaluated on New-onset atrial fibrillation (aHR 2.24, 95% CI 2.02-2.48). AI-ECG-detected grade 3 left ventricular diastolic dysfunction was independently associated with a higher risk of new-onset atrial fibrillation (aHR 2.24; 95% CI 2.02-2.48).