Voice-assisted Artificial Intelligence-enabled Screening for Severe Acute Respiratory Syndrome Coronavirus 2 Exposure in Cardiovascular Clinics: Primary Results of the VOICE-COVID-19-II Randomized Trial.

BACKGROUND: Voice-assisted artificial intelligence-based systems may streamline clinical care among patients with heart failure (HF) and caregivers; however, randomized clinical trials are needed. We evaluated the potential for Amazon Alexa (Alexa), a voice-assisted artificial intelligence-based system, to conduct screening for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a HF clinic. METHODS AND RESULTS: We enrolled 52 participants (patients and caregivers) from a HF clinic who were randomly assigned with a subsequent cross-over to receive a SARS-CoV-2 screening questionnaire via Alexa or health care personnel. The primary outcome was overall response concordance, as measured by the percentage of agreement and unweighted kappa scores between groups. A postscreening survey evaluated comfort with using the artificial intelligence-based device. In total, 36 participants (69%) were male, the median age was 51 years (range 34-65 years) years and 36 (69%) were English speaking. Twenty-one participants (40%) were patients with HF. For the primary outcome, there were no statistical differences between the groups: Alexa-research coordinator group 96.9% agreement and unweighted kappa score of 0.92 (95% confidence interval 0.84-1.00) vs research coordinator-Alexa group 98.5% agreement and unweighted kappa score of 0.95 (95% confidence interval 0.88-1.00) (P value for all comparisons > .05). Overall, 87% of participants rated their screening experience as good or outstanding. CONCLUSIONS: Alexa demonstrated comparable performance to a health care professional for SARS-CoV-2 screening in a group of patients with HF and caregivers and may represent an attractive approach to symptom screening in this population. Future studies evaluating such technologies for other uses among patients with HF and caregivers are warranted. NCT04508972.

Beads- and oil-free single molecule assay with immuno-rolling circle amplification for detection of SARS-CoV-2 from saliva.

Digital enzyme linked immunosorbent assays (ELISA) can be used to detect various antigens such as spike (S) or nucleocapsid (N) proteins of SARS-CoV-2, with much higher sensitivity compared to that achievable using conventional antigen tests. However, the use of microbeads and oil for compartmentalization in these assays limits their user-friendliness and causes loss of assay information due to the loss of beads during the process. To improve the sensitivity of antigen test, here, we developed an oil- and bead-free single molecule counting assay, with rolling circle amplification (RCA) on a substrate. With RCA, the signal is localized at the captured region of an antigen, and the signal from a single antigen molecule can be visualized using the same immune-reaction procedures as in the conventional ELISA. Substrate-based single molecule assay was theoretically evaluated for kd value, and the concentration of capture and detection antibodies. As a feasibility test, biotin-conjugated primer and mouse IgG conjugates were detected even at femto-molar concentrations with this digital immuno-RCA. Using this method, we detected the N protein of SARS-CoV-2 with a limit of detection less than 1 pg/mL more than 100-fold improvement compared to the detection using conventional ELISA. Furthermore, testing of saliva samples from COVID-19 patients and healthy controls (n = 50) indicated the applicability of the proposed method for detection of SARS-CoV-2 with 99.5% specificity and 90.9% sensitivity.

Corticosteroids reduce pathologic interferon responses by downregulating STAT1 in patients with high-risk COVID-19.

We do not yet understand exactly how corticosteroids attenuate hyperinflammatory responses and alleviate high-risk coronavirus disease 2019 (COVID-19). We aimed to reveal the molecular mechanisms of hyperinflammation in COVID-19 and the anti-inflammatory effects of corticosteroids in patients with high-risk COVID-19. We performed single-cell RNA sequencing of peripheral blood mononuclear cells (PBMCs) from three independent COVID-19 cohorts: cohort 1 was used for comparative analysis of high-risk and low-risk COVID-19 (47 PBMC samples from 28 patients), cohort 2 for longitudinal analysis during COVID-19 (57 PBMC samples from 15 patients), and cohort 3 for investigating the effects of corticosteroid treatment in patients with high-risk COVID-19 (55 PBMC samples from 13 patients). PBMC samples from healthy donors (12 PBMC samples from 12 donors) were also included. Cohort 1 revealed a significant increase in the proportion of monocytes expressing the long noncoding RNAs NEAT1 and MALAT1 in high-risk patients. Cohort 2 showed that genes encoding inflammatory chemokines and their receptors were upregulated during aggravation, whereas genes related to angiogenesis were upregulated during improvement. Cohort 3 demonstrated downregulation of interferon-stimulated genes (ISGs), including STAT1, in monocytes after corticosteroid treatment. In particular, unphosphorylated STAT-dependent ISGs enriched in monocytes from lupus patients were selectively downregulated by corticosteroid treatment in patients with high-risk COVID-19. Corticosteroid treatment suppresses pathologic interferon responses in monocytes by downregulating STAT1 in patients with high-risk COVID-19. Our study provides insights into the mechanisms underlying COVID-19 aggravation and improvement and the effects of corticosteroid treatment.

Voice-Based Screening for SARS-CoV-2 Exposure in Cardiovascular Clinics (VOICE-COVID-19-II): Protocol for a Randomized Controlled Trial.

BACKGROUND: The COVID-19 pandemic has disrupted the health care system, limiting health care resources such as the availability of health care professionals, patient monitoring, contact tracing, and continuous surveillance. As a result of this significant burden, digital tools have become an important asset in increasing the efficiency of patient care delivery. Digital tools can help support health care institutions by tracking transmission of the virus, aiding in the screening process, and providing telemedicine support. However, digital health tools face challenges associated with barriers to accessibility, efficiency, and privacy-related ethical issues. OBJECTIVE: This paper describes the study design of an open-label, noninterventional, crossover, randomized controlled trial aimed at assessing whether interactive voice response systems can screen for SARS-CoV-2 in patients as accurately as standard screening done by people. The study aims to assess the concordance and interrater reliability of symptom screening done by Amazon Alexa compared to manual screening done by research coordinators. The perceived level of comfort of patients when interacting with voice response systems and their personal experience will also be evaluated. METHODS: A total of 52 patients visiting the heart failure clinic at the Royal Victoria Hospital of the McGill University Health Center, in Montreal, Quebec, will be recruited. Patients will be randomly assigned to first be screened for symptoms of SARS-CoV-2 either digitally, by Amazon Alexa, or manually, by the research coordinator. Participants will subsequently be crossed over and screened either digitally or manually. The clinical setup includes an Amazon Echo Show, a tablet, and an uninterrupted power supply mounted on a mobile cart. The primary end point will be the interrater reliability on the accuracy of randomized screening data performed by Amazon Alexa versus research coordinators. The secondary end point will be the perceived level of comfort and app engagement of patients as assessed using 5-point Likert scales and binary mode responses. RESULTS: Data collection started in May 2021 and is expected to be completed in fall 2022. Data analysis is expected to be completed in early 2023. CONCLUSIONS: The use of voice-based assistants could improve the provision of health services and reduce the burden on health care personnel. Demonstrating a high interrater reliability between Amazon Alexa and health care coordinators may serve future digital tools to streamline the screening and delivery of care in the context of other conditions and clinical settings. The COVID-19 pandemic occurs during the first digital era using digital tools such as Amazon Alexa for disease screening, and it represents an opportunity to implement such technology in health care institutions in the long term. TRIAL REGISTRATION: ClinicalTrials.gov NCT04508972; https://clinicaltrials.gov/ct2/show/NCT04508972. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/41209.

Association of Alzheimer's Disease with COVID-19 Susceptibility and Severe Complications: A Nationwide Cohort Study.

BACKGROUND: Identification of patients at high susceptibility and high risk of developing serious complications related to coronavirus disease 2019 (COVID-19) infection is clinically important in the face of the COVID-19 pandemic. OBJECTIVE: To investigate whether patients with Alzheimer's disease (AD) are more susceptible to COVID-19 infection and whether they have a higher risk of developing serious complications. METHODS: We retrospectively reviewed the Korean nationwide population-based COVID-19 dataset for participants who underwent real-time reverse transcription polymerase chain reaction assays for COVID-19 between January 1 and June 4, 2020. A 1 : 3 ratio propensity score matching and binary logistic regression analysis were performed to investigate the association between AD and the susceptibility or severe complications (i.e., mechanical ventilation, intensive care unit admission, or death) of COVID-19. RESULTS: Among 195,643 study participants, 5,725 participants had AD and 7,334 participants were diagnosed with COVID-19. The prevalence of participants testing positive for COVID-19 did not differ according to the presence of AD (p = 0.234). Meanwhile, AD was associated with an increased risk of severe COVID-19 complications (OR 2.25 [95% CI 1.54-3.28]). Secondary outcome analyses showed that AD patients had an increased risk for mortality (OR 3.09 [95% CI 2.00-4.78]) but were less likely to receive mechanical ventilation (OR 0.42 [95% CI 0.20-0.87]). CONCLUSION: AD was not associated with increased susceptibility to COVID-19 infection, but was associated with severe COVID-19 complications, especially with mortality. Early diagnosis and active intervention are necessary for patients with AD suspected COVID-19 infection.

A rapid quantitative on-site coronavirus disease 19 serological test.

On-site severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) serological assays allow for timely in-field decisions to be made regarding patient status, also enabling population-wide screening to assist in controlling the coronavirus disease 2019 (COVID-19) pandemic. Here we propose a rapid microfluidic serological assay with two unique functions of nanointerstice filling and digitized flow control, which enable the fast/robust filling of the sample fluid as well as precise regulation of duration and volume of immune reaction. Developed microfluidic assay showed enhanced limit of detection, and 91.67% sensitivity and 100% specificity (n = 152) for clinical samples of SARS CoV-2 patients. The assay enables daily monitoring of IgM/IgG titers and patterns, which could be crucial parameters for convalescence from COVID-19 and provide important insight into how the immune system responds to SARS CoV-2. The developed on-site microfluidic assay presented the mean time for IgM and IgG seroconversions, indicating that these titers plateaued days after seroconversion. The mean duration from day 0 to PCR negativity was 19.4 days (median 20 d, IQR 16-21 d), with higher IgM/IgG titres being observed when PCR positive turns into negative. Simple monitoring of these titres promotes rapid on-site detection and comprehensive understanding of the immune response of COVID-19 patients.