Unknown

Dataset Information

0

A simple and practical score model for predicting the mortality of severe fever with thrombocytopenia syndrome patients.


ABSTRACT: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging disease with a high fatality rate. The risk factors for death are not clearly identified, and there is no clinical score model to predict the prognosis. We retrospectively collected the clinical information of clinical symptoms and laboratory parameters of SFTS patients on admission. After analyzing the clinical characteristics of 179 SFTS patients, we found that an elevated level of neurologic symptoms, respiratory symptoms, viral load, and a lower level of monocyte percentage were the critical risk factors for mortality. We used the 4 variables to assemble a score formula named the SFTS index [SFTSI?=?5?×?Neurologic symptoms-level + 4?×?Respiratory symptoms-level + 3?×?LG10 Viral load - 2?×?LN Monocyte% - 7]. The AURC of this model was 0.964, which was higher than the AURC 0.913 of the viral load especially among the patients with higher viral loads (0.936 vs 0.821). We identified that the neurologic symptoms, respiratory symptoms, viral load, and monocyte percentage were the critical risk factors for SFTS mortality. The clinical score model of SFTSI provides a practical method for clinicians to stratify patients with SFTS and to adopt prompt effective treatment strategies.

SUBMITTER: Xiong S 

PROVIDER: S-EPMC5207567 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

A simple and practical score model for predicting the mortality of severe fever with thrombocytopenia syndrome patients.

Xiong Shue S   Zhang Wenjing W   Li Mingyue M   Xiong Yan Y   Li Mengmeng M   Wang Hua H   Yang Dongliang D   Peng Cheng C   Zheng Xin X  

Medicine 20161201 52


Severe fever with thrombocytopenia syndrome (SFTS) is an emerging disease with a high fatality rate. The risk factors for death are not clearly identified, and there is no clinical score model to predict the prognosis. We retrospectively collected the clinical information of clinical symptoms and laboratory parameters of SFTS patients on admission. After analyzing the clinical characteristics of 179 SFTS patients, we found that an elevated level of neurologic symptoms, respiratory symptoms, vira  ...[more]

Similar Datasets

| S-EPMC5626493 | biostudies-literature
2022-10-13 | PXD033989 | Pride
| S-EPMC6478219 | biostudies-literature
2018-10-30 | GSE121911 | GEO
| S-EPMC3837670 | biostudies-literature
| S-EPMC7101122 | biostudies-literature
| PRJNA732992 | ENA
| S-EPMC6457554 | biostudies-literature
| S-EPMC7595704 | biostudies-literature
| S-EPMC4214315 | biostudies-literature