The Sound of Atherosclerosis: Voice Signal Characteristics are Independently Associated With Coronary Artery Disease
Maor, Elad; Sara, Jaskanwal D; Lerman, Lilach O; Lerman, Amir
Author Information
Div of Cardiovascular Diseases, Mayo Clinic Rochester, Rochester, MN
Author Disclosures: E. Maor: None. J.D. Sara: None. L.O. Lerman: None. A. Lerman: None.
Abstract
Background: There is a clinical need for remote, non-invasive, and objective tests for the presence of coronary artery disease (CAD). Voice signal analysis is an emerging non-invasive diagnostic tool that has been assessed and associated with several disease states. The current study tested the hypothesis that patient voice signal characteristics are associated with the presence of CAD.
Methods: The study population included 121 consecutive patients referred for elective coronary angiography, as well as 25 control patients referred for non-cardiac elective procedures. All subjects had their voice signal recorded using an application downloaded to their personal smartphone device prior to the coronary angiography. Voice was recorded, stored and analyzed for multiple features of voice intensity and frequency using “Beyond Verbal Communications” clinical trial application. Analysis was blinded with respect to patient data. CAD was defined as at least one angiographic stenosis > 70%.
Results: Mean age of the study population was 58±12 years and 51% were men. 42 (34%) patients had significant CAD. Compared with subjects with no coronary disease, patients with CAD were older (62±10 vs. 56±13 years, p=0.002). Univariate binary logistic regression analysis identified 11 voice features that were associated with CAD (p<0 .05="" 1.18-4.79="" 1622hz="" 2.4="" adjustment="" age="" all="" and="" around="" associated="" average="" band="" binary="" cad="" ci="" cycle="" every="" fluctuations="" for="" frequency="" gender="" in="" increase="" increased="" likelihood="" logistic="" of="" one="" p="0.015).</p" regression="" showed="" stepwise="" the="" time="" unit="" was="" with="">Conclusions: We identified abnormal voice characteristics that are independently associated with CAD. This study suggests a potential relationship between voice characteristics and CAD.
Maor, Elad; Sara, Jaskanwal D; Lerman, Lilach O; Lerman, Amir
Author Information
Div of Cardiovascular Diseases, Mayo Clinic Rochester, Rochester, MN
Author Disclosures: E. Maor: None. J.D. Sara: None. L.O. Lerman: None. A. Lerman: None.
Abstract
Background: There is a clinical need for remote, non-invasive, and objective tests for the presence of coronary artery disease (CAD). Voice signal analysis is an emerging non-invasive diagnostic tool that has been assessed and associated with several disease states. The current study tested the hypothesis that patient voice signal characteristics are associated with the presence of CAD.
Methods: The study population included 121 consecutive patients referred for elective coronary angiography, as well as 25 control patients referred for non-cardiac elective procedures. All subjects had their voice signal recorded using an application downloaded to their personal smartphone device prior to the coronary angiography. Voice was recorded, stored and analyzed for multiple features of voice intensity and frequency using “Beyond Verbal Communications” clinical trial application. Analysis was blinded with respect to patient data. CAD was defined as at least one angiographic stenosis > 70%.
Results: Mean age of the study population was 58±12 years and 51% were men. 42 (34%) patients had significant CAD. Compared with subjects with no coronary disease, patients with CAD were older (62±10 vs. 56±13 years, p=0.002). Univariate binary logistic regression analysis identified 11 voice features that were associated with CAD (p<0 .05="" 1.18-4.79="" 1622hz="" 2.4="" adjustment="" age="" all="" and="" around="" associated="" average="" band="" binary="" cad="" ci="" cycle="" every="" fluctuations="" for="" frequency="" gender="" in="" increase="" increased="" likelihood="" logistic="" of="" one="" p="0.015).</p" regression="" showed="" stepwise="" the="" time="" unit="" was="" with="">Conclusions: We identified abnormal voice characteristics that are independently associated with CAD. This study suggests a potential relationship between voice characteristics and CAD.
No comments:
Post a Comment