Integrating AI-ECG and Point-of-Care Cardiac Ultrasound for Screening Structural Heart Disease: A Proof-of-Concept Study

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.

Outpatients who underwent ECG at the Mayo Clinic electrocardiogram-laboratory between November 2023 and February 2024 were randomly offered also to receive POCCUS, performed by a novice operator and reviewed by an expert echocardiologist. Impressions from AI-ECG and POCCUS were integrated to assess for SHD, including low left ventricular systolic function (ejection-fraction<50%), aortic stenosis, and increased left ventricular wall thickness indicative 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 eight to identify one patient requiring formal echocardiography (Central Figure).

The integration of AI-ECG and POCCUS holds promise as a potentially effective screening method for SHD, facilitating improved patient selection for formal echocardiography. Competing Interest Statement The authors have declared no competing interest. Funding Statement The authors declare that no external funding was received for any aspect of the work presented in this manuscript, including study design, data collection, analysis, interpretation, or manuscript preparation. Neither the authors nor their institutions received payment or services from a third party for any component of the submitted work. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Mayo Clinic institutional review board approved the project. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes Conflicts of Interest: None. Data Availability All data referred to in this manuscript are available from the corresponding author upon reasonable request.