Development and Validation of a Nomogram for Assessing Survival in Patients With COVID-19 Pneumonia.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has spread worldwide and continues to threaten peoples' health as well as put pressure on the accessibility of medical systems. Early prediction of survival of hospitalized patients will help in the clinical management of COVID-19, but a prediction model that is reliable and valid is still lacking. METHODS: We retrospectively enrolled 628 confirmed cases of COVID-19 using positive RT-PCR tests for SARS-CoV-2 in Tongji Hospital, Wuhan, China. These patients were randomly grouped into a training (60%) and a validation (40%) cohort. In the training cohort, LASSO regression analysis and multivariate Cox regression analysis were utilized to identify prognostic factors for in-hospital survival of patients with COVID-19. A nomogram based on the 3 variables was built for clinical use. AUCs, concordance indexes (C-index), and calibration curves were used to evaluate the efficiency of the nomogram in both training and validation cohorts. RESULTS: Hypertension, higher neutrophil-to-lymphocyte ratio, and increased NT-proBNP values were found to be significantly associated with poorer prognosis in hospitalized patients with COVID-19. The 3 predictors were further used to build a prediction nomogram. The C-indexes of the nomogram in the training and validation cohorts were 0.901 and 0.892, respectively. The AUC in the training cohort was 0.922 for 14-day and 0.919 for 21-day probability of in-hospital survival, while in the validation cohort this was 0.922 and 0.881, respectively. Moreover, the calibration curve for 14- and 21-day survival also showed high coherence between the predicted and actual probability of survival. CONCLUSIONS: We built a predictive model and constructed a nomogram for predicting in-hospital survival of patients with COVID-19. This model has good performance and might be utilized clinically in management of COVID-19.

Targeting JAK-STAT Signaling to Control Cytokine Release Syndrome in COVID-19.

Recent advances in the pathophysiologic understanding of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has indicated that patients with severe coronavirus disease 2019 (COVID-19) might experience cytokine release syndrome (CRS), characterized by increased interleukin (IL)-6, IL-2, IL-7, IL-10, etc. Therefore, the treatment of cytokine storm has been proposed as a critical part of rescuing severe COVID-19. Several of the cytokines involved in COVID-19 employ a distinct intracellular signaling pathway mediated by Janus kinases (JAKs). JAK inhibition, therefore, presents an attractive therapeutic strategy for CRS, which is a common cause of adverse clinical outcomes in COVID-19. Below, we review the possibilities and challenges of targeting the pathway in COVID-19.