Integrating AI-ECG and point-of-care cardiac ultrasound for screening structural heart disease: A proof-of-concept...

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.

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.

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 8 to identify 1 patient requiring formal echocardiography.

The integration of AI-ECG and POCCUS holds promise as a potentially effective screening method for SHD, facilitating improved patient selection for formal echocardiography.