Key result
AI-ECG-derived worse LV diastolic function grades in LBBB patients independently predicted higher all-cause mortality (G3 LVDF aHR 2.96, p<0.001) beyond LVEF and heart failure.
Why the study?
Assessing left ventricular diastolic function via echocardiography is challenging in left bundle branch block because intraventricular conduction delay disrupts tissue Doppler imaging reliability.
Does AI-ECG-derived left ventricular diastolic function grade predict all-cause mortality in patients with left bundle branch block?
Does AI-ECG-derived left ventricular diastolic function grade predict all-cause mortality in patients with left bundle branch block?
AI-ECG assessment of diastolic function provides independent prognostic value for all-cause mortality in patients with LBBB, overcoming the limitations of traditional echocardiography in this population.
Should not yet change LBBB management; hypothesis-generating for AI-ECG diastolic grading beyond LVEF.
Background Left ventricular diastolic function (LVDF) and left bundle branch block (LBBB) are both linked with increased risk of LV systolic dysfunction, heart failure, and mortality. Assessing LVDF, which is typically done through echocardiography, becomes challenging in the presence of LBBB due to the intraventricular conduction delay that disrupts the reliability of tissue Doppler imaging. Recently, we validated an artificial intelligence-enabled electrocardiogram (AI-ECG) model to assess LVDF and filling pressures. Methods We performed a retrospective study among patients with ECG-confirmed LBBB who also underwent comprehensive echocardiography within 14 days of the index ECG between September 2001 and June 2022. Using multivariable survival models, we assessed the risk of all-cause mortality across AI-ECG-derived LVDF grades. Results Of 2,554 patients with LBBB (mean age 72.0+12.6, 54.6% women), 252 (9.8%), 656 (25.7%), and 1,436 (56.2%), and 210 (8.2%) had normal LVDF, G1 LVDF, G2 LVDF, and G3 LVDF, respectively. The median LV ejection fraction (LVEF) was 54% and 49.3% of the patients had heart failure. Worse LVDF was associated with older age, lower LVEF, and higher rates of diabetes, hypertension, chronic pulmonary disease, renal failure, cardiovascular disease, and heart failure (p-of-trend<0.001 for all). During a median follow-up of 2.6 years (interquartile range 0.5-4.0 years), 847 (33.2%) patients died. In multivariable survival analysis, adjusted to multiple risk factors including baseline LVEF and heart failure, worse LVDF was independently associated with a higher risk of death [G1 LVDF: adjusted hazard ratio (aHR) 2.15 (95% confidence interval (95%CI) 0.75-1.77), G2 LVDF: aHR 2.25 (95%CI 1.50-3.38) G3 LVDF: aHR 2.96 (95%CI 1.88-4.65); p<0.001 for both)]. These findings were consistent also in a subgroup of patients with baseline LVEF > 50%. Conclusion Among patients with LBBB, worse LVDF, as derived by a dedicated AI-ECG algorithm is independently associated with all-cause mortality beyond baseline LVEF and clinical heart failure.survival across AI-ECG LVDF grades
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Tsaban et al. (2025) studied this question. AI-ECG-derived worse LV diastolic function grades in LBBB patients independently predicted higher all-cause mortality (G3 LVDF aHR 2.96, p<0.001) beyond LVEF and heart failure.
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