Guess What We Can Hear – Novel Voice Biomarkers for the Remote Detection of Disease

The advancement of digital biomarkers and the provision of remote healthcare has greatly progressed during the coronavirus-19 global pandemic. Combining voice/speech data with artificial intelligence and machine-based learning offers a novel solution to the growing demand for telemedicine. Voice biomarkers, obtained from the extraction of characteristic acoustic and linguistic features, are associated with a variety of diseases and even coronavirus disease-2019. In the current review we i) describe the basis upon which digital voice biomarkers could facilitate "telemedicine,” ii) discuss potential mechanisms that may explain the association between voice biomarkers and disease, iii) offer a novel classification system to conceptualize voice biomarkers depending upon different methods for recording and analyzing voice/speech samples, iv) outline evidence demonstrating an association between voice biomarkers and a number of disease states, and v) describe the process of developing a voice biomarker from recording and storing voice samples and extracting relevant acoustic and linguistic features to training and testing deep and machine based learning algorithms to detect disease. We further explore several important future considerations in this area of research, including the necessity for clinical trials and importance of safeguarding data and individual privacy. To this end, we searched Pubmed and Google Scholar to identify studies evaluating the relationship between voice/speech features and biomarkers and various diseases. Search terms included "digital biomarker,” "telemedicine,” "voice features,” "voice biomarker,” "speech features,” "speech biomarkers,” "acoustics,” "linguistics,” "cardiovascular disease,” "neurologic disease,” "psychiatric disease,” and "infectious disease.” The search was limited to studies published in English in peer-reviewed journals between 1980 and the present day. To identify potential studies not captured by our database search strategy, we also searched studies listed in the bibliography of relevant publications and reviews.

Noninvasive Vocal Biomarker is Associated With Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

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; P<.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; P=.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.

Transcatheter Aortic Valve Implantation During the COVID-19 Pandemic.

Transcatheter aortic valve implantation (TAVI) outcomes during the coronavirus disease 2019 (COVID-19) pandemic have not been fully evaluated and some structural programs in the world have been suspended during this period. We sought to evaluate and compare clinical outcomes in patients undergoing TAVI in pandemic versus nonpandemic era. In a single center, we compared 198 TAVI patients performed during 2019 to 59 patients performed during the COVID-19 pandemic period (March 1st to June 30th, 2020). Primary outcome was procedural success according to VARC criteria and 30-day mortality rates. VARC-defined procedural success was high in both groups (93.3% vs 96.6%; p = 0.53). There were no differences in any vascular complications (26% vs 19%; p = 0.3), permanent pacemaker implantation (11.8% vs 15.3%; p = 0.63), and length of hospital stay (5.2 vs 4.2 days; p = 0.29). Thirty-day mortality was similar (3% vs 3.4%; p = 1.0). We had no documented COVID-19 disease in our patients during follow up. In conclusion, TAVI procedures can be performed effectively and safely during the COVID-9 pandemic, using a minimalist approach, early discharge, and by maintaining proper use of personal protective equipment.

Cardiovascular adverse events associated with hydroxychloroquine and chloroquine: A comprehensive pharmacovigilance analysis of pre-COVID-19 reports.

AIM: There is a clinical need for safety data regarding hydroxychloroquine (HCQ) and chloroquine (CQ) during the coronavirus (COVID-19) pandemic. We analysed real-world data using the U.S. Food and Drug Administration Adverse Events Reporting System (FAERS) database to assess HCQ/CQ-associated cardiovascular adverse events (CVAEs) in pre-COVID-19 reports. METHODS: We conducted disproportionality analysis of HCQ/CQ in the FAERS database (07/2014-9/2019), using reporting odds ratio (ROR) and the lower bound of the information component 95% credibility interval (IC025 ). RESULTS: The full database contained 6 677 225 reports with a mean (±SD) age of 53 (±17) years and 74% females. We identified 4895 reports of HCQ/CQ related adverse events, of which 696 (14.2%) were CVAEs. Compared with the full database, HCQ/CQ use was associated with a higher reporting rate of major CVAEs, including cardiomyopathy (n = 86 [1.8%], ROR = 29.0 [23.3-35.9]), QT prolongation (n = 43 [0.9%], ROR = 4.5 [3.3-6.1]), cardiac arrhythmias (n = 117 [2.4%], ROR = 2.2 [1.8-2.7]) and heart failure (n = 136 [2.8%], ROR = 2.2 [1.9-2.7], all IC025 > 0). No statistically significant differences were observed between sex and age groups. CVAEs were reported more often in patients with systemic lupus erythematosus and Sjogren's syndrome. HCQ/CQ-associated CVAEs demonstrated subsequent hospitalization and mortality rates of 39% and 8%, respectively. Overdose reports demonstrated an increased frequency of QT prolongation and ventricular arrhythmias (35% and 25%, respectively). CONCLUSION: In a real-world setting, HCQ/CQ treatment is associated with higher reporting rates of various CVAEs, particularly cardiomyopathy, QT prolongation, cardiac arrhythmias and heart failure. HCQ/CQ-associated CVAEs result in high rates of severe outcomes and should be carefully considered as an off-label indication, especially for patients with cardiac disorders.