The respiratory sound features of COVID-19 patients fill gaps between clinical data and screening methods

Ying hui Huang; Si jun Meng; Yi Zhang; Shui sheng Wu; Yu Zhang; Ya wei Zhang; Yi xiang Ye; Qi feng Wei; Nian gui Zhao; Jian ping Jiang; Xiao ying Ji; Chun xia Zhou; Chao Zheng; Wen Zhang; Li zhong Xie; Yong chao Hu; Jian quan He; Jian Chen; Wang yue Wang; Chang hua Zhang; Liming Cao; Wen Xu; Yunhong Lei; Zheng hua Jian; Wei ping Hu; Wen juan Qin; Wan yu Wang; Yu long He; Hang Xiao; Xiao fang Zheng; Yi Qun Hu; Wen Sheng Pan; Jian feng Cai

up the shortcomings of current screening methods so as to effectively improve the recognition rate of suspicious patients. At the same time, there are limitations in this study. Since the results of auscultation are mostly based on personal experience, we did not perform statistical analysis such as the sensitivity, specificity and other indicators of diagnostic test due to lacking effective gold standard. In addition, this is a small observed research, and only the lung breath sounds of the patients are collected at the time of admission. No follow-up research was conducted. This investigation complements the existing clinical data of COVID-19, which provides a convenient screening method. It is hoped that public health workers around the world will be able to use electronic stethoscope to increase the detection rate of mild and asymptomatic patients, reduce their own infection risk, and allow remote treatment to help fight the epidemic.