甘肃省2009-2015年发热呼吸道症候群主要病原的Bayes判别分析法分类研究

李学朝; 李娟生; 孟蕾; 白亚娜; 于德山; 刘小宁; 刘新凤; 蒋小娟; 任晓卫; 杨筱婷; 申希平; 张继巍

Abstract

李学朝,李娟生,孟蕾,白亚娜,于德山,刘小宁,刘新凤,蒋小娟,任晓卫,杨筱婷,申希平,张继巍.甘肃省2009-2015年发热呼吸道症候群主要病原的Bayes判别分析法分类研究[J].Chinese journal of Epidemiology,2017,38(8):1094-1097

甘肃省2009-2015年发热呼吸道症候群主要病原的Bayes判别分析法分类研究

Study on the classification of dominant pathogens related to febrile respiratory syndrome,based on the method of Bayes discriminant analysis

Received:December 21, 2016

DOI：10.3760/cma.j.issn.0254-6450.2017.08.019

KeyWord: 发热呼吸道症候群 Bayes判别分析病原体

English Key Word: Febrile respiratory syndrome Bayes discriminate analysis Pathogeny

FundProject:国家科技重大专项（2012ZX10004-208）

Author Name	Affiliation	E-mail
Li Xuechao	Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou 730000, China
Li Juansheng	Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou 730000, China	lijsh16@163.com
Meng Lei	Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China	mleicdc@163.com
Bai Yana	Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou 730000, China
Yu Deshan	Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China
Liu Xiaoning	Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou 730000, China
Liu Xinfeng	Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China
Jiang Xiaojuan	Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China
Ren Xiaowei	Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou 730000, China
Yang Xiaoting	Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China
Shen Xiping	Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou 730000, China
Zhang Jiwei	Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou 730000, China

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Abstract:

目的了解甘肃省发热呼吸道症候群主要病原体，构建区分主要病原感染病例的Bayes判别函数。方法以2009-2015年甘肃省各哨点医院监测的发热呼吸道症候群病例为样本，描述其病原谱构成，确定主要病原；并在样本病例中筛选有意义的临床指标进行Bayes判别分析。结果在发热呼吸道症候群病毒检测中，流感病毒和鼻病毒检测阳性率较高（13.79%和8.63%），分别占病毒总阳性例数的54.38%和13.73%；细菌中以肺炎链球菌和流感嗜血杆菌检测阳性率较高（44.41%和18.07%），分别占细菌总阳性例数的66.21%和24.55%。运用筛选后的11个临床指标建立判别函数，其初始验证正确率为73.1%、交叉验证为70.6%。结论甘肃省发热呼吸道症候群主要病原体为流感病毒、鼻病毒、肺炎链球菌及流感嗜血杆菌；Bayes判别分析在主要病原感染的分类诊断中有较高的正确率，具有一定的应用价值。

English Abstract:

Objective To understand the dominant pathogens of febrile respiratory syndrome (FRS) patients in Gansu province and to establish the Bayes discriminant function in order to identify the patients infected with the dominant pathogens. Methods FRS patients were collected in various sentinel hospitals of Gansu province from 2009 to 2015 and the dominant pathogens were determined by describing the composition of pathogenic profile. Significant clinical variables were selected by stepwise discriminant analysis to establish the Bayes discriminant function. Results In the detection of pathogens for FRS, both influenza virus and rhinovirus showed higher positive rates than those caused by other viruses (13.79%, 8.63%), that accounting for 54.38%, 13.73% of total viral positive patients. Most frequently detected bacteria would include Streptococcus pneumoniae, and haemophilus influenza (44.41%, 18.07%) that accounting for 66.21% and 24.55% among the bacterial positive patients. The original-validated rate of discriminant function, established by 11 clinical variables, was 73.1%, with the cross-validated rate as 70.6%. Conclusion Influenza virus, Rhinovirus, Streptococcus pneumoniae and Haemophilus influenzae were the dominant pathogens of FRS in Gansu province. Results from the Bayes discriminant analysis showed both higher accuracy in the classification of dominant pathogens, and applicative value for FRS.

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