Clinical features and potential risk factors for discerning the critical cases and predicting the outcome of patients with COVID‐19

Objective To investigate the clinical features and risk factors for discerning the critical and predicting the outcome of patients with COVID‐19. Methods Patients who were admitted to the intensive care unit (ICU) department and general infection department of TaiKang Tongji (Wuhan) Hospital from February 10 to March 27, 2020, were included. Data on clinical features, complications, laboratory parameters, chest CT, nutrient requirement, and electrolyte imbalance were analyzed retrospectively. Results A total of 123 (50 critical and 73 non‐critical) patients were enrolled. 65% of patients with comorbidities, hypertension (45.5%), diabetes (21.9%), 36.5% of patients had more than one comorbidity. The proportion of lymphocytes in critical patients was significantly lower than that of non‐critical patients. The proportion of patients with increased NLR, PLR, IL‐6, CRP levels, and chest CT score was significantly higher in the critical than that of non‐critical patients. The logistic regression analysis identified low lymphocyte count, high NLR, PLR, IL‐6, CRP levels, and CT score as independent factors for discerning critical cases and high NLR, PLR, IL‐6, and CT score could predict poor clinical outcome. Furthermore, we identified patients who needed nutrition support (HR 16.99) and with correction of electrolyte imbalance (HR 18.24) via intravenous injection were more likely to have a poor outcome. Conclusions The potential risk factors of lower lymphocyte count, high levels of NLR, PLR, IL‐6, CRP, chest CT score, and the statue of nutrient requirement or electrolyte imbalance could assist clinicians in discerning critical cases and predict the poor outcome in patients with COVID‐19. The potential risk factors of lower lymphocyte count, high levels of NLR, PLR, IL‐6, CRP, chest CT score, and the statue of nutrient requirement or electrolyte imbalance could assist clinicians in discerning critical cases and predict the poor outcome in patients with COVID‐19.