Key result
AI-ECG-detected elevated LV filling pressure is linked to ~80% higher all-cause mortality, outperforming invasive PAWP.
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Why the study?
Left ventricular diastolic filling pressure is a hallmark of heart failure, but the prognostic implications of its classification by AI-ECG, echocardiography, and catheterization were unclear.
Does LVFP classification by AI-ECG and echocardiography predict all-cause mortality and MACE better than the invasive reference standard (PAWP) in adults undergoing temporally proximate testing?
Observational (n=4,168)
Does LVFP classification by AI-ECG and echocardiography predict all-cause mortality and MACE better than the invasive reference standard (PAWP) in adults undergoing temporally proximate testing?
Hazard Ratio: 1.8 (95% CI 1.55–2.09)
Non-invasive classification of elevated left ventricular filling pressure using AI-ECG or echocardiography is more strongly associated with long-term mortality and MACE than the invasive hemodynamic gold standard (PAWP).
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.
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Tsaban et al. (2026) conducted an observational in Elevated left ventricular filling pressure (n=4,168). Elevated LVFP classification by AI-ECG vs. Normal LVFP classification was evaluated on All-cause mortality (aHR 1.80, 95% CI 1.55-2.09). Elevated left ventricular filling pressure classified by AI-ECG strongly predicted all-cause mortality (aHR 1.80; 95% CI 1.55-2.09), outperforming invasive right heart catheterization PAWP.
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