A scoring model for predicting prognosis of patients with severe fever with thrombocytopenia syndrome

作者
Bei Jia,Xiaomin Yan,Yuxin Chen,Guiyang Wang,Yong Liu,Biyun Xu,Peixin Song,Yang Li,Yali Xiong,Weihua Wu,Yingying Hao,Juan Xia,Zhaoping Zhang,Rui Huang,Chao Wu
出处
期刊:PLOS Neglected Tropical Diseases [Public Library of Science]
卷期号:11 (9): e0005909-e0005909 被引量:54
标识
DOI:10.1371/journal.pntd.0005909
摘要

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging epidemic infectious disease caused by the SFTS bunyavirus (SFTSV) with an estimated high case-fatality rate of 12.7% to 32.6%.Currently, the disease has been reported in mainland China, Japan, Korea, and the United States.At present, there is no specific antiviral therapy for SFTSV infection.Considering the higher mortality rate and rapid clinical progress of SFTS, supporting the appropriate treatment in time to SFTS patients is critical.Therefore, it is very important for clinicians to predict these SFTS cases who are more likely to have a poor prognosis or even more likely to decease.In the present study, we established a simple and feasible model for assessing the severity and predicting the prognosis of SFTS patients with high sensitivity and specificity.This model may aid the physicians to immediately initiate prompt treatment to block the rapid development of the illness and reduce the fatality of SFTS patients. Author summarySevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by a novel SFTS bunyavirus (SFTSV) with an estimated high case-fatality rate.However, there is no specific antiviral therapy for SFTSV infection.Symptomatic treatment and supportive therapy are the most essential part of case management.It is very important for clinicians to identify critical patients at admission.In this study, we established a simple and feasible scoring system for assessing the severity and predicting the prognosis of SFTS patients with objective parameters.This model may help the physicians to perform intervention measures in advance, control the disease progression and improve the prognosis.

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