Simple nomogram based on initial laboratory data for predicting the probability of ICU transfer of COVID‐19 patients: Multicenter retrospective study

Abstract

ABSTRACT This retrospective, multicenter study investigated risk factors associated with intensive care unit (ICU) admission and transfer in 461 adult patients with confirmed coronavirus disease 2019 (COVID‐19) hospitalized from January 22 to March 14, 2020 in Hunan Province, China. Outcomes of ICU and non‐ICU patients were compared, and a simple nomogram for predicting the probability of ICU transfer after hospital admission was developed based on initial laboratory data using a Cox proportional hazards regression model. Differences in laboratory indices were observed between patients admitted to the ICU and those who were not admitted. Several independent predictors of ICU transfer in COVID‐19 patients were identified including older age (≥65 years) (hazard ratio [HR]=4.02), hypertension (HR=2.65), neutrophil count (HR=1.11), procalcitonin level (HR=3.67), prothrombin time (HR=1.28), and d‐dimer level (HR=1.25). Lymphocyte count and albumin level were negatively associated with mortality (HR=0.08 and 0.86, respectively). The developed model provides a means for identifying, at hospital admission, the subset of patients with COVID‐19 who are at high risk of progression and would require transfer to the ICU within 3 and 7 days after hospitalization. This method of early patient triage allows more effective allocation of limited medical resources. This article is protected by copyright. All rights reserved.