A novel simple scoring model for predicting severity of patients with SARS‐CoV‐2 infection

• DOI: 10.1111/tbed.13651
• Publication Date: 2020-05-29T11:56:19Z
• Authors: Yalan Dong; Haifeng Zhou; Mingyue Li; Zili Zhang; Weina Guo; Ting Yu; Yang Gui; Quansheng Wang; Lei Zhao; Shanshan Luo; Heng Fan; Desheng Hu
• Keywords: Erythrocyte sedimentation rate; White blood cell; Pneumonia severity index; Stepwise regression; Univariate analysis; Aspartate transaminase

An outbreak of pneumonia caused by a novel coronavirus (COVID-19) began in Wuhan, China December 2019 and quickly spread throughout the country world. efficient convenient method based on clinical characteristics was needed to evaluate potential deterioration patients. We aimed develop simple practical risk scoring system predict severity COVID-19 patients admission. retrospectively investigated information confirmed from 10 February 2020 29 Wuhan Union Hospital. Predictors were identified univariate multivariate logistic regression analysis. A total 147 with SARS-CoV-2 infection grouped into non-severe (94 patients) severe (53 groups. found that an increased level white blood cells (WBC), neutrophils, D-dimer, fibrinogen (FIB), IL-6, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), alanine aminotransferase (ALT), aspartate (AST), α-hydroxybutyrate dehydrogenase (HBDH), serum amyloid (SAA) decreased lymphocytes important factors associated severity. Furthermore, three variables used formulate named index = 3 × D-dimer (µg/L) + 2 lgESR (mm/hr) - 4 lymphocyte (×10