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이은정Eunjung Lee
Mayo Clinic
npj Digit. Med., Jan 06 2024, 7 (1) 4 | https://doi.org/10.1038/s41746-023-00993-7
Artificial intelligence-enabled ECG for left ventricular diastolic function and filling pressure
Eunjung Lee1, Saki Ito1, William R. Miranda1, Francisco Lopez-Jimenez1, Garvan C. Kane1, Samuel J. Asirvatham1, Peter A. Noseworthy1, Paul A. Friedman1, Rickey E. Carter2, Barry A. Borlaug1, Zachi I. Attia1 and Jae K. Oh1
1Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
2Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA.
Corresponding author : Correspondence to Jae K. Oh.
Abstract
Assessment of left ventricular diastolic function plays a major role in the diagnosis and prognosis of cardiac diseases, including heart failure with preserved ejection fraction. We aimed to develop an artificial intelligence (AI)-enabled electrocardiogram (ECG) model to identify echocardiographically determined diastolic dysfunction and increased filling pressure. We trained, validated, and tested an AI-enabled ECG in 98,736, 21,963, and 98,763 patients, respectively, who had an ECG and echocardiographic diastolic function assessment within 14 days with no exclusion criteria. It was also tested in 55,248 patients with indeterminate diastolic function by echocardiography. The model was evaluated using the area under the curve (AUC) of the receiver operating characteristic curve, and its prognostic performance was compared to echocardiography. The AUC for detecting increased filling pressure was 0.911. The AUCs to identify diastolic dysfunction grades ≥1, ≥2, and 3 were 0.847, 0.911, and 0.943, respectively. During a median follow-up of 5.9 years, 20,223 (20.5%) died. Patients with increased filling pressure predicted by AI-ECG had higher mortality than those with normal filling pressure, after adjusting for age, sex, and comorbidities in the test group (hazard ratio (HR) 1.7, 95% CI 1.645-1.757) similar to echocardiography and in the indeterminate group (HR 1.34, 95% CI 1.298-1.383). An AI-enabled ECG identifies increased filling pressure and diastolic function grades with a good prognostic value similar to echocardiography. AI-ECG is a simple and promising tool to enhance the detection of diseases associated with diastolic dysfunction and increased diastolic filling pressure.
논문정보
- Research article
- 2024년 01월 (BRIC 등록일 2024-01-09)
- 국외 연구진
- 바이오·의료융합 > 다학제 융합/복합
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