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Background: High incidence of asymptomatic venous thromboembolism (VTE) has been observed in severe COVID-19 patients, but the characteristics of symptomatic VTE in general COVID-19 patients have not been described. Objectives: To comprehensively explore the prevalence and reliable risk prediction for VTE in COVID-19 patients. Methods/Results: This retrospective study enrolled all COVID-19 patients with a subsequent VTE in 16 centers in China from January 1 to March 31, 2020. A total of 2779 patients were confirmed with COVID-19. In comparison to 23,434 non-COVID-19 medical inpatients, the odds ratios (ORs) for developing symptomatic VTE in severe and non-severe hospitalized COVID-19 patients were 5.94 (95% confidence interval [CI] 3.91-10.09) and 2.79 (95% CI 1.43-5.60), respectively. When 104 VTE cases and 208 non-VTE cases were compared, pulmonary embolism cases had a higher rate for in-hospital death (OR 6.74, 95% CI 2.18-20.81). VTE developed at a median of 21 days (interquartile range 13.25-31) since onset. Independent factors for VTE were advancing age, cancer, longer interval from symptom onset to admission, lower fibrinogen and higher D-dimer on admission, and D-dimer increment (DI) ≥1.5-fold; of these, DI ≥1.5-fold had the most significant association (OR 14.18, 95% CI 6.25-32.18, p = 2.23 × 10 −10). A novel model consisting of three simple coagulation variables (fibrinogen and D-dimer levels on admission, and DI ≥1.5-fold) showed good prediction for symptomatic VTE (area under the curve 0.865, 95% CI 0.822-0.907, sensitivity 0.930, specificity 0.710). Conclusions: There is an excess risk of VTE in hospitalized COVID-19 patients. This novel model can aid early identification of patients who are at high risk for VTE.

Background: Since December 2019, the cumulative number of coronavirus disease 2019 (COVID-19) deaths worldwide has reached 1,013,100 and continues to increase as of writing. Of these deaths, more than 90% are people aged 60 and older. Therefore, there is a need for an easy-to-use clinically predictive tool for predicting mortality risk in older individuals with COVID-19. Objective: To explore an easy-to-use clinically predictive tool that may be utilized in predicting mortality risk in older patients with COVID-19. Methods: A retrospective analysis of 118 older patients with COVID-19 admitted to the

BackgroundThe prognostic role of programmed death-ligand 1 (PD-L1) in sarcoma remains controversial. We performed a meta-analysis so as to investigate the impact of PD-L1 on clinicopathlogical findings and survival outcomes in sarcoma.Materials and MethodsA comprehensive search in PubMed, Embase and the Cochrane Library was conducted for relevant studies. The odds ratios or hazard ratios, at 95% confidence intervals were used as measures for investigation of the correlation between PD-L1 expression and clinicopathlogical features or survival outcomes.ResultsFourteen eligible studies comprising 868 patients were selected for analysis. Pooled hazard ratios indicated that the association of PD-L1 expression with overall survival in bone sarcoma (osteosarcoma and chondrosarcoma) patients was statistically significant (1.987, 95% CI: 1.224–3.224, p = 0.005), as was its association with event-free survival in bone and soft-tissue sarcoma patients (3.868, 95% CI: 2.298–6.511, p = 0.000). Additionally, the expression of PD-L1 was positively correlated with the infiltration of programmed death 1 (PD-1) positive T-lymphocytes (OR: 4.012, 95% CI: 2.391–6.733, p = 0.000).ConclusionsOur meta-analysis indicated that high PD-L1 expression is likely to be a negative factor for patients with sarcomas and that it predicts worse survival outcomes.