Metagenomic Next-Generation Sequencing in the Diagnosis of HHV-1 Reactivation in a Critically Ill COVID-19 Patient: A Case Report.

Background: Secondary infections pose tremendous challenges in Coronavirus disease 2019 (COVID-19) treatment and are associated with higher mortality rates. Clinicians face of the challenge of diagnosing viral infections because of low sensitivity of available laboratory tests. Case Presentation: A 66-year-old woman initially manifested fever and shortness of breath. She was diagnosed as critically ill with COVID-19 using quantitative reverse transcription PCR (RT-qPCR) and treated with antiviral therapy, ventilator and extracorporeal membrane oxygenation (ECMO). However, after the condition was relatively stabled for a few days, the patient deteriorated with fever, frequent cough, increased airway secretions, and increased exudative lesions in the lower right lung on chest X-rays, showing the possibility of a newly acquired infection, though sputum bacterial and fungal cultures and smears showed negative results. Using metagenomic next-generation sequencing (mNGS), we identified a reactivation of latent human herpes virus type 1 (HHV-1) in the respiratory tract, blood and gastrointestinal tract, resulting in a worsened clinical course in a critically ill COVID-19 patient on ECMO. Anti-HHV-1 therapy guided by these sequencing results effectively decreased HHV-1 levels, and improved the patient's clinical condition. After 49 days on ECMO and 67 days on the ventilator, the 66-year-old patient recovered and was discharged. Conclusions: This case report demonstrates the potential value of mNGS for evidence-based treatment, and suggests that potential reactivation of latent viruses should be considered in critically ill COVID-19 patients.

Scores based on neutrophil percentage and lactate dehydrogenase with or without oxygen saturation predict hospital mortality risk in severe COVID-19 patients.

BACKGROUND: Risk scores are needed to predict the risk of death in severe coronavirus disease 2019 (COVID-19) patients in the context of rapid disease progression. METHODS: Using data from China (training dataset, n = 96), prediction models were developed by logistic regression and then risk scores were established. Leave-one-out cross validation was used for internal validation and data from Iran (test dataset, n = 43) was used for external validation. RESULTS: A NSL model (area under the curve (AUC) 0.932) and a NL model (AUC 0.903) were developed based on neutrophil percentage and lactate dehydrogenase with and without oxygen saturation (SaO2) using the training dataset. AUCs of the NSL and NL models in the test dataset were 0.910 and 0.871, respectively. The risk scoring systems corresponding to these two models were established. The AUCs of the NSL and NL scores in the training dataset were 0.928 and 0.901, respectively. At the optimal cut-off value of NSL score, the sensitivity and specificity were 94% and 82%, respectively. The sensitivity and specificity of NL score were 94% and 75%, respectively. CONCLUSIONS: These scores may be used to predict the risk of death in severe COVID-19 patients and the NL score could be used in regions where patients' SaO2 cannot be tested.

Quarantine at home may not enough!-from the epidemiological data in Shaanxi Province of China.

OBJECTIVES: A pneumonia associated with 2019 novel coronavirus (2019-nCoV, subsequently named SARS-CoV2) emerged worldwide since December, 2019. We aimed to describe the epidemiological characteristics of 2019 coronavirus disease (COVID-19) in Shaanxi province of China. RESULTS: 1. Among the 245 patients, 132 (53.9%) were males and 113 (46.1%) were females. The average age was 46.15 ± 16.43 years, ranging from 3 to 89 years. 2. For the clinical type, 1.63% (4/245) patients were mild type, 84.90% (208/245) were moderate type, 7.76% (19/245) were severe type, 5.31% (13/245) were critical type and only 0.41% (1/245) was asymptomatic. 3. Of the 245 patients, 116 (47.35%) were input case, 114 (46.53%) were non-input case, and 15 (6.12%) were unknown exposure. 4. 48.57% (119/245) cases were family cluster, involving 42 families. The most common pattern of COVID-19 family cluster was between husband and wife or between parents and children.

Advances in the use of chloroquine and hydroxychloroquine for the treatment of COVID-19.

Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is spreading worldwide. Antiviral therapy is the most important treatment for COVID-19. Among the drugs under investigation, anti-malarials, chloroquine (CQ) and hydroxychloroquine (HCQ), are being repurposed as treatment for COVID-19. CQ/HCQ were shown to prevent receptor recognition by coronaviruses, inhibit endosome acidification, which interferes with membrane fusion, and exhibit immunomodulatory activity. These multiple mechanisms may work together to exert a therapeutic effect on COVID-19. A number of in vitro studies revealed inhibitory effects of CQ/HCQ on various coronaviruses, including SARS-CoV-2 although conflicting results exist. Several clinical studies showed that CQ/HCQ alone or in combination with a macrolide may alleviate the clinical symptoms of COVID-19, promote viral conversion, and delay disease progression, with less serious adverse effects. However, recent studies indicated that the use of CQ/HCQ, alone or in combination with a macrolide, did not show any favorable effect on patients with COVID-19. Adverse effects, including prolonged QT interval after taking CQ/HCQ, may develop in COVID-19 patients. Therefore, current data are not sufficient enough to support the use of CQ/HCQ as therapies for COVID-19 and increasing caution should be taken about the application of CQ/HCQ in COVID-19 before conclusive findings are obtained by well-designed, multi-center, randomized, controlled studies.