ABSTRACT
Despite coronavirus disease 2019, cardiovascular disease, the leading cause of global death, requires timely detection and treatment for a high survival rate, underscoring the 24 h monitoring of vital signs. Therefore, telehealth using wearable devices with vital sign sensors is not only a fundamental response against the pandemic but a solution to provide prompt healthcare for the patients in remote sites. Former technologies which measured a couple of vital signs had features that disturbed practical applications to wearable devices, such as heavy power consumption. Here, we suggest an ultralow power (100 µW) sensor that collects all cardiopulmonary vital signs, including blood pressure, heart rate, and the respiration signal. The small and lightweight (2 g) sensor designed to be easily embedded in the flexible wristband generates an electromagnetically reactive near field to monitor the contraction and relaxation of the radial artery. The proposed ultralow power sensor measuring noninvasively continuous and accurate cardiopulmonary vital signs at once will be one of the most promising sensors for wearable devices to bring telehealth to our lives.
ABSTRACT
OBJECTIVES: Real-time polymerase chain reaction is currently used as a confirmatory test for coronavirus disease 2019 (COVID-19). The test results are interpreted as positive, negative, or inconclusive, and are used only for a qualitative classification of patients. However, the test results can be quantitated using threshold count (Ct) values to determine the amount of virus present in the sample. Therefore, this study investigated the diagnostic usefulness of Ct results through various quantitative analyzes, along with an analysis of clinical and epidemiological characteristics. METHODS: Clinical and epidemiological data from 4,642 COVID-19 patients in April 2021 were analyzed, including the Ct values of the RNA-dependent RNA polymerase (RdRp), envelope (E), and nucleocapsid (N) genes. Clinical and epidemiological data (sex, age, underlying diseases, and early symptoms) were collected through a structured questionnaire. A correlation analysis was used to examine the relationships between variables. RESULTS: All 3 genes showed statistically significant relationships with symptoms and severity levels. The Ct values of the RdRp gene decreased as the severity of the patients increased. Moreover, statistical significance was observed for the presence of underlying diseases and dyspnea. CONCLUSION: Ct values were found to be related to patients' clinical and epidemiological characteristics. In particular, since these factors are closely related to symptoms and severity, Ct values can be used as primary data for predicting patients' disease prognosis despite the limitations of this method. Conducting follow-up studies to validate this approach might enable using the data from this study to establish policies for preventing COVID-19 infection and spread.
ABSTRACT
Early diagnosis increases the treatment success rate for active tuberculosis (ATB) and decreases mortality. MicroRNAs (miRNAs) have been studied as blood-based markers of several infectious diseases. We performed miRNA profiling to identify differentially expressed (DE) miRNAs using whole blood samples from 10 healthy controls (HCs), 15 subjects with latent tuberculosis infection (LTBI), and 12 patients with ATB, and investigated the expression of the top six miRNAs at diagnosis and over the treatment period in addition to performing miRNA-target gene network and gene ontology analyses. miRNA profiling identified 84 DE miRNAs in patients with ATB, including 80 upregulated and four downregulated miRNAs. Receiver operating characteristic curves of the top six miRNAs exhibited excellent distinguishing efficiency with an area under curve (AUC) value > 0.85. Among them, miR-199a-3p and miR-6886-3p can differentiate between ATB and LTBI. Anti-TB treatment restored the levels of miR-199b-3p, miR-199a-3p, miR-16-5p, and miR-374c-5p to HC levels. Furthermore, 108 predicted target genes were related to the regulation of cellular amide metabolism, intrinsic apoptotic signaling, translation, transforming growth factor beta receptor signaling, and cysteine-type endopeptidase activity. The DE miRNAs identified herein are potential biomarkers for diagnosis and therapeutic monitoring in ATB.
ABSTRACT
PURPOSE: Coronavirus disease-2019 (COVID-19) is a novel respiratory infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); there are few specific treatments. Convalescent plasma (CP), donated by people who have recovered from COVID-19, is an investigational therapy for severe or critically ill patients with COVID-19. MATERIALS AND METHODS: This retrospective cohort study evaluated the effectiveness of CP therapy in patients with severe or life-threatening cases of COVID-19 at two hospitals in Seoul, Korea, between May and September 2020. Clinical outcomes were evaluated in 20 patients with CP therapy in a descriptive manner. Additionally, the changes in cycle threshold (Ct) values of 10 patients with CP therapy were compared to those of 10 controls who had the same (±0.8) initial Ct values but did not receive CP. RESULTS: Of the 20 patients (mean age 66.6 years), 18 received high-dose oxygen therapy using mechanical ventilators or high-flow nasal cannulas. Systemic steroids were administered to 19 patients who received CP. The neutralizing antibody titers of the administered CP were between 1:80 and 1:10240. There were two ABO-mismatched transfusions. The World Health Organization ordinal scale score and National Institutes of Health severity score improved in half of the patients within 14 days. Those who received CP showed a higher increase in Ct values at 24 h and 72 h after CP therapy compared to controls with similar initial Ct values (p=0.002). No transfusion-related side effects were observed. CONCLUSION: CP therapy may be a potential therapeutic option in severe or critically ill patients with COVID-19.