Coronavirus disease 2019 (COVID-19) has spread outside the initial epicenter of Wuhan. We compared cases in Guangzhou and Wuhan to illustrate potential changes in pathogenicity and epidemiological characteristics as the epidemic has progressed. We studied 20 patients admitted to the Third Affiliated Hospital of Sun Yat-Sen University in Guangzhou, China from January 22 to February 12, 2020. Data were extracted from medical records. These cases were compared with the 99 cases, previously published in Lancet, from Wuhan Jinyintan Hospital from January 1 to January 20, 2020. Guangzhou patients were younger and had better prognosis than Wuhan patients. The Wuhan patients were more likely to be admitted to the ICU (23% vs 5%) and had a higher mortality rate (11% vs 0%). Cases in Guangzhou tended to be more community clustered. Diarrhea and vomiting were more common among Guangzhou patients and SARS-CoV-2 RNA was found in feces. Fecal SARA-CoV-2 RNA remained positive when nasopharyngeal swabs turned negative in some patients. This study indicates possible diminishing virulence of the virus in the process of transmission. Yet persistent positive RNA in feces after negative nasopharyngeal swabs suggests a possible prolonged transmission period that challenges current quarantine practices.

Background: Due to no reliable risk stratification tool for severe corona virus disease 2019 (COVID-19) patients at admission, we aimed to construct an effective model for early identifying cases at high risk of progression to severe COVID-19. Methods: In this retrospective three-centers study, 372 non-severe COVID-19 patients during hospitalization were followed for more than 15 days after admission. Patients who deteriorated to severe or critical COVID-19 and patients who kept non-severe state were assigned to the severe and non-severe group, respectively. Based on baseline data of the two groups, we constructed a risk prediction nomogram for severe COVID-19 and evaluate its performance. Results: The train cohort consisted of 189 patients, while the two independent validation cohorts consisted of 165 and 18 patients. Among all cases, 72 (19.35%) patients developed severe COVID-19. We found that old age, and higher serum lactate dehydrogenase, C-reactive protein, the coefficient of variation of red blood cell distribution width, blood urea nitrogen, direct bilirubin, lower albumin, are associated with severe COVID-19. We generated the nomogram for early identifying severe COVID-19 in the train cohort (AUC 0.912 [95% CI 0.846-0.978], sensitivity 85.71%, specificity 87.58%); in validation cohort (0.853 [0.790-0.916], 77.5%, 78.4%). The calibration curve for probability of severe COVID-19 showed optimal agreement between prediction by nomogram and actual observation. Decision curve and clinical impact curve analysis indicated that nomogram conferred high clinical net benefit. Conclusion: Our nomogram could help clinicians to early identify patients who will exacerbate to severe COVID-19, which will enable better centralized management and early treatment of severe patients. Summary: Older age; higher LDH, CRP, RDW, DBIL, BUN; lower ALB on admission correlated with higher odds of severe COVID-19. An effective prognostic nomogram composed of 7 features could allow early identification of patients at risk of exacerbation to severe COVID-19.

Background. Platelet to white blood cell ratio (PWR) was an independent prognostic predictor for outcomes in some diseases. However, the prognostic role of PWR is still unclear in patients with hepatitis B related acute-on-chronic liver failure (ACLF). In this study, we evaluated the clinical performances of PWR in predicting prognosis in HBV-related ACLF. Methods. A total of 530 subjects were recruited, including 97 healthy controls and 433 with HBV-related ACLF. Liver function, prothrombin time activity (PTA), international normalized ratio (INR), HBV DNA measurement, and routine hematological testing were performed at admission. Results. At baseline, PWR in patients with HBV-related ACLF (14.03 ± 7.17) was significantly decreased compared to those in healthy controls (39.16 ± 9.80). Reduced PWR values were clinically associated with the severity of liver disease and the increased mortality rate. Furthermore, PWR may be an inexpensive, easily accessible, and significant independent prognostic index for mortality on multivariate analysis (HR = 0.660, 95% CI: 0.438–0.996, p=0.048) as well as model for end-stage liver disease (MELD) score. Conclusions. The PWR values were markedly decreased in ACLF patients compared with healthy controls and associated with severe liver disease. Moreover, PWR was an independent prognostic indicator for the mortality rate in patients with ACLF. This investigation highlights that PWR comprised a useful biomarker for prediction of liver severity.

Objectives: The pathogenesis of heterogeneity in gastric cancer (GC) is not clear and presents as a significant obstacle in providing effective drug treatment. We aimed to identify subtypes of GC and explore the underlying pathogenesis.Methods: We collected two microarray datasets from GEO (GSE84433 and GSE84426), performed an unsupervised cluster analysis based on gene expression patterns, and identified related immune and stromal cells. Then, we explored the possible molecular mechanisms of each subtype by functional enrichment analysis and identified related hub genes.Results: First, we identified three clusters of GC by unsupervised hierarchical clustering, with average silhouette width of 0.96, and also identified their related representative genes and immune cells. We validated our findings using dataset GSE84426. Subtypes associated with the highest mortality (subtype 2 in the training group and subtype C in the validation group) showed high expression of SPARC, COL3A1, and CCN. Both subtypes also showed high infiltration of fibroblasts, endothelial cells, hematopoietic stem cells, and a high stromal score. Furthermore, subtypes with the best prognosis (subtype 3 in the training group and subtype A in the validation group) showed high expression of FGL2, DLGAP1-AS5, and so on. Both subtypes also showed high infiltration of CD4⁺ T cells, CD8⁺ T cells, NK cells, pDC, macrophages, and CD4⁺ T effector memory cells.Conclusion: We found that GC can be classified into three subtypes based on gene expression patterns and cell composition. Findings of this study help us better understand the tumor microenvironment and immune milieu associated with heterogeneity in GC and provide practical information to guide personalized treatment.

Summary: Cryptococcal meningitis (CM) carries a high risk of mortality with increasing incidences in immune competent hosts. Current treatments are not well tolerated, and evaluation of other treatments is needed. Fluconazole and 5‐flucytosine in treating immune competent hosts have not been characterised. To evaluate the efficacy of fluconazole and 5‐flucytosine in treating non‐HIV‐ and non‐transplant‐associated CM. We performed a retrospective cohort study of the outcomes in immune competent patients with CM treated with fluconazole and 5‐flucytosine or deoxycholate‐amphotericin B and 5‐flucytosine. The primary outcome was treatment response evaluated at the 12th week after initiation of antifungal therapy. A total of 43 and 47 patients received amphotericin B deoxycholate and 5‐flucytosine or fluconazole and 5‐flucytosine, respectively. A total of 38 (88.4%) patients cannot tolerate recommended doses of amphotericin B deoxycholate and 5‐flucytosine (patients needed dose reduction during the treatment). Patients given fluconazole and 5‐flucytosine had higher baseline cryptococcal burdens (median 3632 versus 900 cryptococci/mL, P = 0.008). No significant differences were seen in cryptococcus clearance (74.4% vs 70.2%, P = 0.814), treatment time (39 days, 20‐69 days vs 21 days, 7‐63 days, P = 0.107) and successful response (including complete and partial responses) rates (69.7% vs 72.3%, P = 0.820). Fluconazole and 5‐flucytosine treatment had lower total adverse events (19.1% vs 90.7%, P < 0.001). Fluconazole and 5‐flucytosine had relatively high efficacy with few adverse events in treating CM. Fluconazole and 5‐flucytosine therapy is promising in patients that do not tolerate or are not suited for amphotericin B deoxycholate treatment.