Am Heart J. 2025 Dec 31:107337. doi: 10.1016/j.ahj.2025.107337. Online ahead of print.
ABSTRACT
BACKGROUND: Early structural heart disease (SHD) detection is crucial for improving prognostic outcomes, but widely accessible screening methods are lacking. The advent of artificial intelligence-enabled electrocardiograms (AI-ECG) and point-of-care cardiac-ultrasonography (POCCUS) offers promising new approaches for patient screening. We explored the feasibility and potential of integrating these innovative technologies into a practical SHD screening framework.
METHODS: Outpatients undergoing ECG at the Mayo Clinic ECG laboratory between November 2023 and February 2024 were pragmatically offered POCCUS, performed by novice operators and reviewed by expert echocardiographers. AI-ECG and POCCUS findings were integrated to assess SHD, including reduced left ventricular systolic function (ejection-fraction<50%), aortic stenosis, and increased left ventricular wall thickness suggestive of cardiac amyloidosis or hypertrophic cardiomyopathy. Operators were blinded to patients' comorbidities and formal echocardiogram results.
RESULTS: Of 486 patients (median-age 64 years;49% women), 286 had available formal echocardiography, with 17.5% having SHD. AI-ECG had a 32% positive predictive value (PPV) and a 94% negative predictive value (NPV) to detect any SHD. Adding POCCUS increased the overall PPV to 64% with an NPV of 93%, with an increase in diagnostic accuracy from 67% to 88%. Notably, 89.5% (17/19) of the "false positives" by AI-ECG+POCCUS had less-than-moderate-SHD. Applying the AI-ECG+POCCUS screening workflow on the entire cohort resulted in a number-needed-to-screen of eight to identify one patient requiring formal echocardiography.
CONCLUSIONS: The integration of AI-ECG and POCCUS holds promise as a potentially effective screening method for SHD, facilitating improved patient selection for formal echocardiography.
PMID:41482060 | DOI:10.1016/j.ahj.2025.107337