Application of a decision tree model in the early identification of severe patients with severe fever with thrombocytopenia syndrome.

ABSTRACT:

Background

Severe fever with thrombocytopenia syndrome (SFTS) is a serious infectious disease with a fatality of up to 30%. To identify the severity of SFTS precisely and quickly is important in clinical practice.

Methods

From June to July 2020, 71 patients admitted to the Infectious Department of Joint Logistics Support Force No. 990 Hospital were enrolled in this study. The most frequently observed symptoms and laboratory parameters on admission were collected by investigating patients' electronic records. Decision trees were built to identify the severity of SFTS. Accuracy and Youden's index were calculated to evaluate the identification capacity of the models.

Results

Clinical characteristics, including body temperature (p = 0.011), the size of the lymphadenectasi

SUBMITTER: Wang B 

PROVIDER: S-EPMC8324211 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature