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预防医学  2023, Vol. 35 Issue (2): 112-115,120    DOI: 10.19485/j.cnki.issn2096-5087.2023.02.005
  论著 本期目录 | 过刊浏览 | 高级检索 |
斑点热与发热伴血小板减少综合征早期鉴别模型研究
杨慧1,2, 孙婕2, 徐鹏鹏2, 张夏晴1, 胡颉颖2, 吕勇1,2
1.安徽医科大学公共卫生学院卫生检验与检疫系,安徽 合肥 230032;
2.六安市疾病预防控制中心,安徽 六安 237001
Construction of a model for early identification of spotted fever and severe fever with thrombocytopenia syndrome
YANG Hui1,2, SUN Jie2, XU Pengpeng2, ZHANG Xiaqing1, HU Jieying2, LÜ Yong1,2
1. Department of Health Inspection and Quarantine, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China;
2. Lu'an Center for Disease Control and Prevention, Lu'an, Anhui 237001, China
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摘要 目的 建立斑点热(SF)与发热伴血小板减少综合征(SFTS)临床鉴别模型,为早期鉴别SF和SFTS提供参考。方法 通过中国疾病预防控制信息系统收集2017年5月—2021年5月安徽省六安市二级及以上医院经实验室确诊的SF和SFTS病例临床资料;采用logistic回归模型分析SF的影响因素,建立SF与SFTS早期鉴别模型;采用Hosmer-Lemeshow检验评价模型拟合效果;采用受试者操作特征曲线下面积(AUC)评价模型鉴别价值。结果 纳入62例SF病例资料和115例SFTS病例资料。多因素logistic回归分析结果显示,SF与SFTS鉴别模型最终纳入皮疹(β=5.994)、C反应蛋白(β=4.409)、白细胞(β=-3.176)和血小板(β=-3.234)4个指标,分别赋值6、4、-3和-3分,总分为-6~10分;Hosmer-Lemeshow检验显示模型拟合效果较好(χ2=3.245,P=0.662)。模型AUC值为0.992,当截断值取1分时,灵敏度为0.935,特异度为0.991。结论 本研究建立的SF与SFTS鉴别模型包括皮疹、C反应蛋白、白细胞和血小板4个指标,早期鉴别的准确性较高。
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关键词 斑点热发热伴血小板减少综合征早期鉴别    
AbstractObjective 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.
Key wordsspotted fever    severe fever with thrombocytopenia syndrome    early identification
收稿日期: 2022-09-02      修回日期: 2022-11-23      出版日期: 2023-02-10
中图分类号:  R512.8  
  R513.3  
基金资助:安徽省卫生健康委科研一般项目(AHWJ2021b011)
通信作者: 吕勇,E-mail:lyong@lacdc.com.cn   
作者简介: 杨慧,硕士研究生在读,主要从事急性传染病研究工作
引用本文:   
杨慧, 孙婕, 徐鹏鹏, 张夏晴, 胡颉颖, 吕勇. 斑点热与发热伴血小板减少综合征早期鉴别模型研究[J]. 预防医学, 2023, 35(2): 112-115,120.
YANG Hui, SUN Jie, XU Pengpeng, ZHANG Xiaqing, HU Jieying, LÜ Yong. Construction of a model for early identification of spotted fever and severe fever with thrombocytopenia syndrome. Preventive Medicine, 2023, 35(2): 112-115,120.
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http://www.zjyfyxzz.com/CN/10.19485/j.cnki.issn2096-5087.2023.02.005      或      http://www.zjyfyxzz.com/CN/Y2023/V35/I2/112
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