Feasibility of remote screening for high risk valve disease using a new wearable cardiac monitoring patch with synchronized phonocardiogram and electrocardiogram in communities

医学 心音图 心脏病学 内科学 听诊器 听诊 狭窄 瓣膜性心脏病 放射科
作者
W L Zhang,Qingjie Huang,Jiayi Yu,Zhaohan Zhu,R Y Zhang
出处
期刊:European Heart Journal [Oxford University Press]
卷期号:44 (Supplement_2) 被引量:4
标识
DOI:10.1093/eurheartj/ehad655.2977
摘要

Abstract Background The 2010 census data showed that the weighted prevalence rate of valvular disease was 3.8% in China. For many elderly people, COVID-19 pandemic has caused the situation that they have not received medical examination for years. Since many patients with moderate aortic/mitral stenosis/regurgitation do not have significant symptoms, early detection of high-risk groups of valve disease is essential. A new wearable cardiac monitoring patch with synchronized phonocardiogram(PCG) and electrocardiogram(ECG) function is introduced in this study. Unlike handheld auscultation, it minimizes the interference of the environment and the operator, and is not demanding for the operator. Methods We enrolled 3170 patients of over 65 years old. Patients with diagnosed moderate or severe aortic/mitral stenosis/regurgitation, congenital heart disease, hypertrophic cardiomyopathy were excluded. Data acquisition was done by social workers following strict instructions. The patch was attached to the mitral and aortic auscultation area on the patients. ECG and PCG signals can be detected simultaneously and sent to a phone or tablet via Bluetooth. The data would then be auto-uploaded to a cloud-based center for further analysis. The end-to-end algorithm for S1 and S2 heart sounds detection involves a CNN-LSTM model for R-peak detection and a 1-D CNN-based U-Net model for fine-grained segmentation based on the detected heartbeat. The segmentation network takes multi-modal PCG and ECG signals as inputs and applies Contrastive Learning as a pretraining technique for enhancement to a real-world problem: detecting heart murmur from high-risk valve disease. If the results indicate positive, the patient is recommended by family doctors to do ultrasonic cardiogram (UCG) and seek further medical advice (Figure 1). Results 3170 participants were recruited from March 2022 to December 2022 in different communities of Huangpu District in Shanghai(Figure 2). In total, 43.98% were men, and 85.81% of age distribution were among 65-79 years. Among 3170 participants, 119(3.8%) were suspected positive by ECG and PCG. Among 119 patients, 65.55% were among 65-79 years. After telephone follow-up 29(24.3%) patients finished clinical visit and UCG. About 66% were diagnosed as mild aortic/mitral stenosis/regurgitation, 24% were diagnosed as moderate aortic/mitral stenosis/regurgitation, 10% were diagnosed as hypertrophic cardiomyopathy. Conclusions This study demonstrated the feasibility of remote screening for high risk valve disease using a new wearable cardiac monitoring patch in community visit by social workers with no medical background. This technology may improve the efficacy of clinical diagnosis and reduce unnecessary examination, particularly in the absence of doctors' auscultation and UCG. Unfortunately, three quarters of the suspected positive patients lost contact or refused to do UCG due to COVID-19 pandemic. Further investigations are necessary to increase accuracy.Flow chart of community screeningbaseline and disease distribution
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