Detection of SARS-CoV-2 RNA Using RT-qPCR in Saliva Samples and Nasopharyngeal, Lingual, and Buccal Mucosal Swabs.

Coronavirus disease 2019 is diagnosed based on the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in nasopharyngeal swabs or saliva samples using reverse-transcription quantitative polymerase chain reaction. Nasopharyngeal swabs should be collected by medical professionals who are covered with full personal protective equipment (PPE), while saliva samples can be collected by patients themselves without any PPE. However, collecting saliva is difficult for people who are unable to follow instructions, including infants or unconscious patients. Owing to the high viscosity of saliva, special attention is required to handle saliva samples in laboratories. To solve these problems, we compared lingual and buccal mucosal swabs (oral swabs) with nasopharyngeal swabs and saliva samples. Among 13 patients who had a positive result for SARS-CoV-2 RNA in their nasopharyngeal swabs, 8 and 10 patients had a positive result for SARS-CoV-2 RNA in their saliva (concordance rate, 61.5%) and oral swabs (76.9%), respectively. Among the eight patients with a positive result for SARS-CoV-2 RNA in saliva, seven (87.5%) had SARS-CoV-2 detected in their oral swabs. We could not obtain saliva samples from four patients, but we found perfect concordance of SARS-CoV-2 positivity between the nasopharyngeal and oral swabs. Therefore, oral swabs can be used for SARS-CoV-2 RNA detection.

Apparent Life-Threatening Event in an Infant with SARS-CoV-2 Infection.

The 2019 novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a global outbreak of infection. In general, children with coronavirus disease-2019 have been reported to show milder respiratory symptoms than adult patients. Here, we have described a case of a SARS-CoV-2-infected infant who presented to our hospital with a severe episode of an apparent life-threatening event (ALTE). An 8-month-old, otherwise healthy female infant presented to our hospital because of a sudden cardiopulmonary arrest. Approximately 1 h before this episode, the patient showed no symptoms, except a worse humor than usual. On arrival at our hospital, the patient had severe acidosis, but there were no clear signs of inflammatory response. Chest computed tomography showed weak consolidations in the upper right lung and atelectasis in the lower left lung. No signs of congenital heart disease or cardiomyopathy were observed on echocardiography, and no significant arrhythmia was observed during the clinical course. However, SARS-CoV-2 RNA was detected by real-time reverse transcription polymerase chain reaction in tracheal aspirate and urine samples. Although the assessment of further similar cases is indispensable, this case suggests that SARS-CoV-2 infection may be an underlying factor in the pathophysiology of ALTE.

A Study of the Patient Acceptance Capacity of the Yamanashi Prefecture Medical System amid the Coronavirus Disease 2019 Pandemic.

INTRODUCTION: Whether healthcare providers can secure the number of beds that may be required during the coronavirus disease 2019 (COVID-19) pandemic remains unclear. This study aimed to determine the sufficiency of the hospital beds available to the healthcare system of Yamanashi, Japan, in accommodating hospitalized and severely ill patients during the COVID-19 pandemic. METHODS: In total, 60 hospitals, with > 20 beds each, were included in this study (n = 10,684). However, beds in the psychiatric and tuberculosis wards (n = 2,295), nonoperational beds (n = 376), and beds for patients in the recovery and chronic phases (n = 3,494) were excluded. The projected occupancy rate was calculated based on the estimated number of patients, including severely ill patients requiring hospitalization during the COVID-19 pandemic. Based on the number of hospitalized patients, we created an adjusted model to calculate the mean occupancy rate of beds for each medical area in the prefecture (Model 1), which is free of areal occupancy rate biases. Moreover, we created an adjusted model that places severely ill patients in the two advanced acute hospitals in Yamanashi, thereby calculating the bed occupancy rates in other hospitals with > 200 beds (Model 2). RESULTS: A total of 4,519 beds were analyzed. Although the existing infectious disease beds may not be able to accommodate the projected number of severely ill patients, the existing capacity can accommodate all patients projected to require hospitalization during the pandemic. In Model 1, the mean bed occupancy rate was 50%. Conversely, in Model 2, advanced acute hospital beds were insufficient for the projected number of severely ill patients, and the mean bed occupancy rate was 72.5%. CONCLUSIONS: Adjustment of patients across the medical area borders enables the existing hospital beds to accommodate the estimated number of patients requiring hospitalization or those who are severely ill.