Metatranscriptomic Analysis Reveals Disordered Alterations in Oropharyngeal Microbiome during the Infection and Clearance Processes of SARS-CoV-2: A Warning for Secondary Infections.

This study was conducted to investigate oropharyngeal microbiota alterations during the progression of coronavirus disease 2019 (COVID-19) by analyzing these alterations during the infection and clearance processes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The diagnosis of COVID-19 was confirmed by using positive SARS-CoV-2 quantitative reverse transcription polymerase chain reaction (RT-qPCR). The alterations in abundance, diversity, and potential function of the oropharyngeal microbiome were identified using metatranscriptomic sequencing analyses of oropharyngeal swab specimens from 47 patients with COVID-19 (within a week after diagnosis and within two months after recovery from COVID-19) and 40 healthy individuals. As a result, in the infection process of SARS-CoV-2, compared to the healthy individuals, the relative abundances of Prevotella, Aspergillus, and Epstein-Barr virus were elevated; the alpha diversity was decreased; the beta diversity was disordered; the relative abundance of Gram-negative bacteria was increased; and the relative abundance of Gram-positive bacteria was decreased. After the clearance of SARS-CoV-2, compared to the healthy individuals and patients with COVID-19, the above disordered alterations persisted in the patients who had recovered from COVID-19 and did not return to the normal level observed in the healthy individuals. Additionally, the expressions of several antibiotic resistance genes (especially multi-drug resistance, glycopeptide, and tetracycline) in the patients with COVID-19 were higher than those in the healthy individuals. After SARS-CoV-2 was cleared, the expressions of these genes in the patients who had recovered from COVID-19 were lower than those in the patients with COVID-19, and they were different from those in the healthy individuals. In conclusion, our findings provide evidence that potential secondary infections with oropharyngeal bacteria, fungi, and viruses in patients who have recovered from COVID-19 should not be ignored; this evidence also highlights the clinical significance of the oropharyngeal microbiome in the early prevention of potential secondary infections of COVID-19 and suggests that it is imperative to choose appropriate antibiotics for subsequent bacterial secondary infection in patients with COVID-19.

Follow-Up Study of the Cardiopulmonary and Psychological Outcomes of COVID-19 Survivors Six Months After Discharge in Sichuan, China.

PURPOSE: Some studies have shown that patients with coronavirus disease 2019 (COVID-19) still have sequelae after discharge. However, little is known about the long-term physical and psychological sequelae of patients, especially factors that influenced the prognosis. PATIENTS AND METHODS: Patients with COVID-19 were followed up for 6 months. The psychological status of patients was evaluated by DASS-21 questionnaire, while physical functions were determined using medical history, laboratory examination, thoracic computed tomography (CT), and echocardiography. RESULTS: Fifty patients infected with COVID-19 were enrolled, and 11 (22%) patients still showed symptoms related to COVID-19. The mean contents (cells/ul) of CD3+ cells, CD4+ and CD8+ T, B lymphocytes and NK cells of the survivors elevated significantly after 6-month discharge (P < 0.001). The frequency of ground-glass opacities and consolidations decreased from 90% to 42% (P < 0.001), and 54% to 20%, (P = 0.001), respectively, while the changes of reticulation and bronchiectasis were insignificant (P > 0.05). The frequency of left ventricular diastolic dysfunction decreased from 40% to 15% (P = 0.002). Depression was observed in 5 (12.5%) participants, stress in 3 (7.5%), anxiety in 6 (15%), and among them 1 (2.5%) showed extremely severe anxiety. Covariation analysis elucidated age might be a risk factor (OR: 1.09, 95% CI: 1.01-1.18, P = 0.038), while NK cell was a good prognostic factor for pulmonary recovery. The comorbidities were significantly positive correlated with persist pulmonary damage (r = 0.33, P = 0.020). Compared with patients with antiviral therapy, patients without antiviral therapy had higher anxiety score (3 vs 0, P = 0.033). CONCLUSION: After 6-month discharge, the persisting cardiopulmonary damage was observed in recovery patients, and psychological implications should not be ignored. Age, comorbidities, NK cell and antiviral therapy might be associated with the prognosis of COVID-19.

Development and Validation of a Predictive Model for Severe COVID-19: A Case-Control Study in China.

Background: Predicting the risk of progression to severe coronavirus disease 2019 (COVID-19) could facilitate personalized diagnosis and treatment options, thus optimizing the use of medical resources. Methods: In this prospective study, 206 patients with COVID-19 were enrolled from regional medical institutions between December 20, 2019, and April 10, 2020. We collated a range of data to derive and validate a predictive model for COVID-19 progression, including demographics, clinical characteristics, laboratory findings, and cytokine levels. Variation analysis, along with the least absolute shrinkage and selection operator (LASSO) and Boruta algorithms, was used for modeling. The performance of the derived models was evaluated by specificity, sensitivity, area under the receiver operating characteristic (ROC) curve (AUC), Akaike information criterion (AIC), calibration plots, decision curve analysis (DCA), and Hosmer-Lemeshow test. Results: We used the LASSO algorithm and logistic regression to develop a model that can accurately predict the risk of progression to severe COVID-19. The model incorporated alanine aminotransferase (ALT), interleukin (IL)-6, expectoration, fatigue, lymphocyte ratio (LYMR), aspartate transaminase (AST), and creatinine (CREA). The model yielded a satisfactory predictive performance with an AUC of 0.9104 and 0.8792 in the derivation and validation cohorts, respectively. The final model was then used to create a nomogram that was packaged into an open-source and predictive calculator for clinical use. The model is freely available online at https://severeconid-19predction.shinyapps.io/SHINY/. Conclusion: In this study, we developed an open-source and free predictive calculator for COVID-19 progression based on ALT, IL-6, expectoration, fatigue, LYMR, AST, and CREA. The validated model can effectively predict progression to severe COVID-19, thus providing an efficient option for early and personalized management and the allocation of appropriate medical resources.

Genomic monitoring of SARS-CoV-2 uncovers an Nsp1 deletion variant that modulates type I interferon response.

The SARS-CoV-2 virus, the causative agent of COVID-19, is undergoing constant mutation. Here, we utilized an integrative approach combining epidemiology, virus genome sequencing, clinical phenotyping, and experimental validation to locate mutations of clinical importance. We identified 35 recurrent variants, some of which are associated with clinical phenotypes related to severity. One variant, containing a deletion in the Nsp1-coding region (Δ500-532), was found in more than 20% of our sequenced samples and associates with higher RT-PCR cycle thresholds and lower serum IFN-ß levels of infected patients. Deletion variants in this locus were found in 37 countries worldwide, and viruses isolated from clinical samples or engineered by reverse genetics with related deletions in Nsp1 also induce lower IFN-ß responses in infected Calu-3 cells. Taken together, our virologic surveillance characterizes recurrent genetic diversity and identified mutations in Nsp1 of biological and clinical importance, which collectively may aid molecular diagnostics and drug design.

How telemedicine integrated into China's anti-COVID-19 strategies: case from a National Referral Center.

INTRODUCTION: We present the integration of telemedicine into the healthcare system of West China Hospital of Sichuan University (WCH), one of the largest hospitals in the world with 4300 inpatient beds, as a means for maximising the efficiency of healthcare delivery during the COVID-19 pandemic. METHODS: Implemented on 22 January 2020, the telemedicine technology allowed WCH providers to conduct teleconsultations, telerounds, teleradiology and tele-intensive care unit, which in culmination provided screening, triage and treatment for COVID-19 and other illnesses. To encourage its adoption, the government and the hospital publicised the platform on social media and waived fees. DISCUSSION: From 1 February to 1 April 2020, 10557 online COVID-19 consultations were conducted for 6662 individuals; meanwhile, 32676 patients without COVID completed virtual follow-ups. We discuss that high-quality, secure, affordable and user-friendly telemedical platforms should be integrated into global healthcare systems to help decrease the transmission of the virus and protect healthcare providers from infection.