%0 Journal Article
%T Artificial intelligence-based screening for cardiomyopathy in an obstetric population: A pilot study.
%A Adedinsewo D
%A Morales-Lara AC
%A Hardway H
%A Johnson P
%A Young KA
%A Garzon-Siatoya WT
%A Butler Tobah YS
%A Rose CH
%A Burnette D
%A Seccombe K
%A Fussell M
%A Phillips S
%A Lopez-Jimenez F
%A Attia ZI
%A Friedman PA
%A Carter RE
%A Noseworthy PA
%J Cardiovasc Digit Health J
%V 5
%N 3
%D 2024 Jun
%M 38989045
暂无%R 10.1016/j.cvdhj.2024.03.005
%X UNASSIGNED: Cardiomyopathy is a leading cause of pregnancy-related mortality and the number one cause of death in the late postpartum period. Delay in diagnosis is associated with severe adverse outcomes.
UNASSIGNED: To evaluate the performance of an artificial intelligence-enhanced electrocardiogram (AI-ECG) and AI-enabled digital stethoscope to detect left ventricular systolic dysfunction in an obstetric population.
UNASSIGNED: We conducted a single-arm prospective study of pregnant and postpartum women enrolled at 3 sites between October 28, 2021, and October 27, 2022. Study participants completed a standard 12-lead ECG, digital stethoscope ECG and phonocardiogram recordings, and a transthoracic echocardiogram within 24 hours. Diagnostic performance was evaluated using the area under the curve (AUC).
UNASSIGNED: One hundred women were included in the final analysis. The median age was 31 years (Q1: 27, Q3: 34). Thirty-eight percent identified as non-Hispanic White, 32% as non-Hispanic Black, and 21% as Hispanic. Five percent and 6% had left ventricular ejection fraction (LVEF) <45% and <50%, respectively. The AI-ECG model had near-perfect classification performance (AUC: 1.0, 100% sensitivity; 99%-100% specificity) for detection of cardiomyopathy at both LVEF categories. The AI-enabled digital stethoscope had an AUC of 0.98 (95% CI: 0.95, 1.00) and 0.97 (95% CI: 0.93, 1.00), for detection of LVEF <45% and <50%, respectively, with 100% sensitivity and 90% specificity.
UNASSIGNED: We demonstrate an AI-ECG and AI-enabled digital stethoscope were effective for detecting cardiac dysfunction in an obstetric population. Larger studies, including an evaluation of the impact of screening on clinical outcomes, are essential next steps.