Construction of a model for early identification of spotted fever and severe fever with thrombocytopenia syndrome
10.19485/j.cnki.issn2096-5087.2023.02.005
- Author:
Hui YANG
;
Jie SUN
;
Pengpeng XU
;
Xiaqing ZHANG
;
Jieying HU
;
Yong LÜ
- Publication Type:Journal Article
- Keywords:
spotted fever;
severe fever with thrombocytopenia syndrome;
early identification
- From:
Journal of Preventive Medicine
2023;35(2):112-115
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a model for clinical identification of spotted fever (SF) and severe fever with thrombocytopenia syndrome (SFTS), so as to provide insights into early identification of SF and SFTS.
Methods:The clinical data of laboratory-confirmed SF and SFTS patients in secondary and tertiary hospitals in Lu'an City, Anhui Province from May 2017 to May 2021 were retrieved from Chinese Disease Prevention and Control Information System. Factors affecting SF were identified using a logistic regression model, and the model for early identification of SF and SFTS was created. The model fitting effect was evaluated using Hosmer-Lemeshow test, and the value of the model for identification of SF and SFTS was evaluated using the area under the receiver operating characteristic curve (AUC).
Results:Data of 62 SF cases and 115 SFTS cases were included. Multivariable logistic regression analysis showed that rash (β=5.994), C-reactive protein (β=4.409), white blood cell (β=-3.176) and platelet (β=-3.234) were included in the model, which were scored 6, 4, -3 and -3, with a total score ranging from -5 to 10. Hosmer-Lemeshow test revealed a high model fitting effect (χ2=3.245, P=0.662). The AUC of the model was 0.992, and the sensitivity and specificity were 0.935 and 0.991 if the cutoff was 1.
Conclusion:A model for early identification of SF and SFTS that includes four variables of rash, C-reactive protein, white blood cell and platelet has been created, which has a high accuracy.
- Full text:斑点热与发热伴血小板减少综合征早期鉴别模型研究.pdf
