Voice Signal Characteristics Are Independently Associated With Coronary Artery Disease.
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Abstract
OBJECTIVE Voice signal analysis is an emerging noninvasive diagnostic tool The current study tested the hypothesis that patient voice signal characteristics are associated with the presence of coronary artery disease CAD METHODS The study population included 138 patients who were enrolled between January 1 2015 and February 28 2017 37 control subjects and 101 subjects who underwent planned coronary angiogram All subjects had their voice signal recorded to their smartphone 3 times reading a text describing a positive emotional experience and describing a negative emotional experience The Mel Frequency Cepstral Coefficients were used to extract prespecified voice features from all 3 recordings Voice was recorded before the angiogram and analysis was blinded with respect to patient data RESULTS Final study cohort included 101 patients of whom 71 71 had CAD Compared with subjects without CAD patients with CAD were older median 63 years interquartile range IQR 55 68 years vs median 53 years IQR 42 66 years P 003 and had a higher 10 year atherosclerotic cardiovascular disease ASCVD risk score 9 4 IQR 5 0 18 7 vs 2 7 IQR 1 6 11 8 P 005 Univariate binary logistic regression analysis identified 5 voice features that were associated with CAD PUnder 05 for all Multivariate binary logistic regression with adjustment for ASCVD risk score identified 2 voice features that were independently associated with CAD odds ratio OR 0 37 95 CI 0 18 0 79 and 4 01 95 CI 1 25 12 84 P 009 and P 02 respectively Both features were more strongly associated with CAD when patients were asked to describe an emotionally significant experience CONCLUSION This study suggests a potential relationship between voice characteristics and CAD with clinical implications for telemedicine when clinical health care is provided at a distance