JACC. Cardiovascular imaging · 2026
Left Ventricular Filling Pressure Classification by Electrocardiogram, Echocardiography, and Catheterization: Prognostic Implications.
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Tsaban Gal, Lee Eunjung, Lopez-Jimenez Francisco, Miranda William R, Kane Garvan C, Chen Horng H, Deshmukh Abhishek J, Asirvatham Samuel J, Noseworthy Peter A, Gulati Rajiv, Friedman Paul A, Attia Zachi, Oh Jae K
Аннотация
BACKGROUND: Left ventricular diastolic filling pressure (LVFP) is a hallmark of heart failure. Although pulmonary artery wedge pressure (PAWP) measured during right heart catheterization (RHC) is the reference standard, echocardiography is more commonly used in practice.
OBJECTIVES: The authors previously developed an artificial intelligence-enabled electrocardiographic (AI-ECG) algorithm, trained on echocardiographic assessment, to classify LVFP. The aim of this study was to evaluate the prognostic implications of LVFP classification by AI-ECG, echocardiography, and PAWP among patients undergoing temporally proximate testing.
METHODS: Adults who underwent echocardiography with electrocardiography within 14 days and RHC within 30 days were included. Elevated LVFP was defined as PAWP ≥15 mm Hg, grade 2 or 3 diastolic dysfunction by echocardiography, or elevated LVFP as classified by AI-ECG. Associations with all-cause mortality and major adverse cardiovascular events were assessed.
RESULTS: Among 4,168 patients (median age: 64 years; 47.7% women), elevated LVFP was classified by AI-ECG in 2,383 patients, by echocardiography in 1,643, and by PAWP in 1,841. AI-ECG showed good discrimination for echocardiographic LVFP (AUC: 0.879; 95% CI: 0.867-0.891) and moderate discrimination for PAWP (AUC: 0.711; 95% CI: 0.695-0.727). Over 7.7 years, 1,433 deaths occurred. Elevated LVFP classification by AI-ECG (adjusted HR [aHR]: 1.80; 95% CI: 1.55-2.09) and echocardiography (aHR: 1.74; 95% CI: 1.51-2.02) showed stronger associations with mortality than PAWP (aHR: 1.18; 95% CI: 1.05-1.31); in discordant cases, AI-ECG better predicted survival. Similar associations were observed for major adverse cardiovascular events.
CONCLUSIONS: Despite moderate agreement with PAWP, echocardiography and AI-ECG showed stronger associations with clinical outcomes, suggesting they capture prognostically relevant myocardial information beyond resting hemodynamic status.
OBJECTIVES: The authors previously developed an artificial intelligence-enabled electrocardiographic (AI-ECG) algorithm, trained on echocardiographic assessment, to classify LVFP. The aim of this study was to evaluate the prognostic implications of LVFP classification by AI-ECG, echocardiography, and PAWP among patients undergoing temporally proximate testing.
METHODS: Adults who underwent echocardiography with electrocardiography within 14 days and RHC within 30 days were included. Elevated LVFP was defined as PAWP ≥15 mm Hg, grade 2 or 3 diastolic dysfunction by echocardiography, or elevated LVFP as classified by AI-ECG. Associations with all-cause mortality and major adverse cardiovascular events were assessed.
RESULTS: Among 4,168 patients (median age: 64 years; 47.7% women), elevated LVFP was classified by AI-ECG in 2,383 patients, by echocardiography in 1,643, and by PAWP in 1,841. AI-ECG showed good discrimination for echocardiographic LVFP (AUC: 0.879; 95% CI: 0.867-0.891) and moderate discrimination for PAWP (AUC: 0.711; 95% CI: 0.695-0.727). Over 7.7 years, 1,433 deaths occurred. Elevated LVFP classification by AI-ECG (adjusted HR [aHR]: 1.80; 95% CI: 1.55-2.09) and echocardiography (aHR: 1.74; 95% CI: 1.51-2.02) showed stronger associations with mortality than PAWP (aHR: 1.18; 95% CI: 1.05-1.31); in discordant cases, AI-ECG better predicted survival. Similar associations were observed for major adverse cardiovascular events.
CONCLUSIONS: Despite moderate agreement with PAWP, echocardiography and AI-ECG showed stronger associations with clinical outcomes, suggesting they capture prognostically relevant myocardial information beyond resting hemodynamic status.