Objective: To investigate the association of voice analysis with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.
Patients And Methods: A vocal biomarker, a unitless scalar with a value between 0 and 1, was developed based on 434 voice samples. The biomarker training was followed by a prospective, multicenter, observational study. All subjects were tested for SARS-CoV-2, had their voice recorded to a smartphone application, and gave their informed consent to participate in the study. The association of SARS-CoV-2 infection with the vocal biomarker was evaluated.
Results: The final study population included 80 subjects with a median age of 29 [range, 23 to 36] years, of whom 68% were men. Forty patients were positive for SARS-CoV-2. Infected patients were 12 times more likely to report at least one symptom (odds ratio, 11.8; <.001). The vocal biomarker was significantly higher among infected patients (OR, 0.11; 95% CI, 0.06 to 0.17 vs OR, 0.19; 95% CI, 0.12 to 0.3; =.001). The area under the receiver operating characteristic curve evaluating the association of the vocal biomarker with SARS-CoV-2 status was 72%. With a biomarker threshold of 0.115, the results translated to a sensitivity and specificity of 85% (95% CI, 70% to 94%) and 53% (95% CI, 36% to 69%), respectively. When added to a self-reported symptom classifier, the area under the curve significantly improved from 0.775 to 0.85.
Conclusion: Voice analysis is associated with SARS-CoV-2 status and holds the potential to improve the accuracy of self-reported symptom-based screening tools. This pilot study suggests a possible role for vocal biomarkers in screening for SARS-CoV-2-infected subjects.
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http://dx.doi.org/10.1016/j.mayocpiqo.2021.05.007 | DOI Listing |
Alzheimers Dement (Amst)
January 2025
Department of Psychiatry Rambam Health Care Campus Haifa Israel.
Background: Late-life depression (LLD) is a heterogenous disorder related to cognitive decline and neurodegenerative processes, raising a need for the development of novel biomarkers. We sought to provide preliminary evidence for acoustic speech signatures sensitive to LLD and their relationship to depressive dimensions.
Methods: Forty patients (24 female, aged 65-82 years) were assessed with the Geriatric Depression Scale (GDS).
JMIR Med Inform
January 2025
Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
Background: The two most commonly used methods to identify frailty are the frailty phenotype and the frailty index. However, both methods have limitations in clinical application. In addition, methods for measuring frailty have not yet been standardized.
View Article and Find Full Text PDFAnn Fam Med
January 2025
Departments of Psychiatry and Emergency Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
Purpose: Mental health screening is recommended by the US Preventive Services Task Force for all patients in areas where treatment options are available. Still, it is estimated that only 4% of primary care patients are screened for depression. The goal of this study was to evaluate the efficacy of machine learning technology (Kintsugi Voice, v1, Kintsugi Mindful Wellness, Inc) to detect and analyze voice biomarkers consistent with moderate to severe depression, potentially allowing for greater compliance with this critical primary care public health need.
View Article and Find Full Text PDFJ Neurochem
January 2025
Department of Pathology, School of Veterinary Medicine, University of São Paulo, Sao Paulo, Brazil.
Autism spectrum disorder (ASD) is a complex developmental disorder characterized by several behavioral impairments, especially in socialization, communication, and the occurrence of stereotyped behaviors. In rats, prenatal exposure to valproic acid (VPA) induces autistic-like behaviors. Previous studies by our group have suggested that the autistic-like phenotype is possibly related to dopaminergic system modulation because tyrosine hydroxylase (TH) expression was affected.
View Article and Find Full Text PDFMol Psychiatry
December 2024
Department of Psychiatry and Biobehavioral Sciences, Brain Research Institute, University of California Los Angeles, Los Angeles, CA, USA.
Major depressive disorder (MDD) often goes undiagnosed due to the absence of clear biomarkers. We sought to identify voice biomarkers for MDD and separate biomarkers indicative of MDD predisposition from biomarkers reflecting current depressive symptoms. Using a two-stage meta-analytic design to remove confounds, we tested the association between features representing vocal pitch and MDD in a multisite case-control cohort study of Chinese women with recurrent depression.
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