AUTHOR=Wang Yung-Chih , Lin Sheng-Wen , Wang I-Jen , Yang Chung-Yao , Hong Chitsung , Sun Jun-Ren , Feng Po-Hao , Lee Mei-Hui , Shen Ching-Fen , Lee Yi-Tzu , Cheng Chao-Min TITLE=Interleukin-6 Test Strip Combined With a Spectrum-Based Optical Reader for Early Recognition of COVID-19 Patients With Risk of Respiratory Failure JOURNAL=Frontiers in Bioengineering and Biotechnology VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2022.796996 DOI=10.3389/fbioe.2022.796996 ISSN=2296-4185 ABSTRACT=

The COVID-19 pandemic has had a globally devastating impact. This highly contagious virus has significantly overburdened and undermined medical systems. While most infected patients experience only mild symptoms, those who are severely affect require urgent medical interventions and some develop acute respiratory failure and require mechanical ventilation. The broad and potentially deadly impact of infection underscores the critical need for early recognition, especially for those at risk for respiratory failure. Those who are severely impacted and at high risk for respiratory failure have been found to present high levels of serum cytokines, such as interleukin-6 (IL-6). Timely diagnosis and management of those at risk for respiratory failure is crucial. Measurement of IL-6 may provide a means for distinguishing such patients. Currently, most serum IL-6 detection relies on the use of laboratory-based conventional enzyme-linked immunosorbent assays. Although some rapid assays have been developed recently, they need to be conducted by specific technicians in central laboratory settings with advanced and expensive equipment. In this study, we propose an IL-6 test strip combined with a spectrum-based optical reader for early recognition of COVID-19-infected patients at imminent risk of acute respiratory failure requiring mechanical ventilator support. For our analyses, clinical demographic data and sera samples were obtained from three medical centers, and test strip specificity and detection performance were analyzed. This would help healthcare personnel stratify the risk of respiratory failure and provide prompt, and suitable management.