Viral Infections of the Upper Airway in the Setting of COVID-19: A Primer for Rhinologists

An Introduction to Engineering and Modeling the Lung

Over the last decade, the field of lung biology has evolved considerably due to many advancements, including the advent of single-cell RNA (scRNA) sequencing, induced pluripotent stem cell (iPSC) reprogramming, and 3D cell and tissue culture. Despite rigorous research and tireless efforts, chronic pulmonary diseases remain the third leading cause of death globally, with transplantation being the only option for treating end-stage disease. This chapter will introduce the broader impacts of understanding lung biology in health and disease, provide an overview of lung physiology and pathophysiology, and summarize the key takeaways from each chapter describing engineering translational models of lung homeostasis and disease. This book is divided into broad topic areas containing chapters covering basic biology, engineering approaches, and clinical perspectives related to (1) the developing lung, (2) the large airways, (3) the mesenchyme and parenchyma, (4) the pulmonary vasculature, and (5) the interface between lungs and medical devices. Each section highlights the underlying premise that engineering strategies, when applied in collaboration with cell biologists and pulmonary physicians, will address critical challenges in pulmonary health care.

Coinfection with severe acute respiratory syndrome coronavirus-2 and other respiratory viruses at a tertiary hospital in Korea

Background

Studies have reported coinfection of severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2), the cause of coronavirus disease‐2019 (COVID‐19), with other viruses that cause respiratory tract infections (RTIs). We investigated the coinfection rate of SARS‐CoV‐2 and other RTI‐causing viruses, and whether the cycle threshold (Ct) value of a real‐time reverse transcriptase PCR (RT‐PCR) differed when the coinfection occurred during the first wave of COVID‐19 in Daegu, Republic of Korea, in 2020.

Methods

After performing PCR for SARS‐CoV‐2, we additionally tested for the presence of RTI‐causing viruses to check for coinfection. Subsequently, we identified the specific coexisting respiratory viruses and calculated the coinfection rate. In addition, based on the coinfection status, we compared the Ct values obtained from RT‐PCR for SARS‐CoV‐2 in patients who tested positive for COVID‐19 PCR.

Results

Of 13,717 patients, 123 had positive results on COVID‐19 PCR testing and six tested positive for an RTI‐causing virus. Thus, the coinfection rate was 4.9%. There were no statistically significant differences in the mean Ct values of SARS‐CoV‐2 RT‐PCR between coinfected and non‐coinfected patients.

Conclusion

This study computed the coinfection rate of SARS‐CoV‐2 and RTI‐causing viruses and revealed that the mean Ct values in SARS‐CoV‐2 real‐time RT‐PCR did not differ according to the coinfection status.