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Etiological analysis and predictive diagnostic model building of community-acquired pneumonia in adult outpatients in Beijing, China
Liu, Ya-Fen1; Gao, Yan1; Chen, Mei-Fang1; Cao, Bin2; Yang, Xiao-Hua1; Wei, Lai1
关键词Community-acquired Pneumonia Etiology Epidemiology Diagnosis Pneumonia Virus Polymerase Chain Reaction Roc Curve
刊名BMC INFECTIOUS DISEASES
2013-07-09
DOI10.1186/1471-2334-13-309
13
收录类别SCI
文章类型Article
WOS标题词Science & Technology
类目[WOS]Infectious Diseases
研究领域[WOS]Infectious Diseases
关键词[WOS]RESPIRATORY-TRACT INFECTION ; VIRAL-INFECTIONS ; PREVALENCE ; BACTEREMIA ; PATHOGENS ; MACROLIDE ; VIRUSES ; CULTURE ; RISK
英文摘要

Background: Etiological epidemiology and diagnosis are important issues in adult community-acquired pneumonia (CAP), and identifying pathogens based on patient clinical features is especially a challenge. CAP-associated main pathogens in adults include viruses as well as bacteria. However, large-scale epidemiological investigations of adult viral CAP in China are still lacking. In this study, we analyzed the etiology of adult CAP in Beijing, China and constructed diagnostic models based on combinations of patient clinical factors.

Methods: A multicenter cohort was established with 500 adult CAP outpatients enrolled in Beijing between November 2010 to October 2011. Multiplex and quantitative real-time fluorescence PCR were used to detect 15 respiratory viruses and mycoplasma pneumoniae, respectively. Bacteria were detected with culture and enzyme immunoassay of the Streptococcus pneumoniae urinary antigen. Univariate analysis, multivariate analysis, discriminatory analysis and Receiver Operating Characteristic (ROC) curves were used to build predictive models for etiological diagnosis of adult CAP.

Results: Pathogens were detected in 54.2% (271/500) of study patients. Viruses accounted for 36.4% (182/500), mycoplasma pneumoniae for 18.0% (90/500) and bacteria for 14.4% (72/500) of the cases. In 182 of the patients with viruses, 219 virus strains were detected, including 166 single and 53 mixed viral infections. Influenza A virus represented the greatest proportion with 42.0% (92/219) and 9.1% (20/219) in single and mixed viral infections, respectively. Factors selected for the predictive etiological diagnostic model of viral CAP included cough, dyspnea, absence of chest pain and white blood cell count (4.0-10.0) x 10(9)/L, and those of mycoplasma pneumoniae CAP were being younger than 45 years old and the absence of a coexisting disease. However, these models showed low accuracy levels for etiological diagnosis (areas under ROC curve for virus and mycoplasma pneumoniae were both 0.61, P < 0.05).

Conclusions: Greater consideration should be given to viral and mycoplasma pneumoniae infections in adult CAP outpatients. While predictive etiological diagnostic models of viral and mycoplasma pneumoniae based on combinations of demographic and clinical factors may provide indications of etiology, diagnostic confirmation of CAP remains dependent on laboratory pathogen test results.

语种英语
WOS记录号WOS:000322446100001
引用统计
被引频次:16[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.bjmu.edu.cn/handle/400002259/54645
专题北京大学第二临床医学院_感染科
北京大学第二临床医学院_北京大学肝病研究所
作者单位1.Peking Univ, Inst Hepatol, Dept Infect Dis, Peking Univ Peoples Hosp, Beijing 100044, Peoples R China
2.Capital Med Univ, Dept Infect Dis & Clin Microbiol, Beijing Chao Yang Hosp, Beijing 100020, Peoples R China
推荐引用方式
GB/T 7714
Liu, Ya-Fen,Gao, Yan,Chen, Mei-Fang,et al. Etiological analysis and predictive diagnostic model building of community-acquired pneumonia in adult outpatients in Beijing, China[J]. BMC INFECTIOUS DISEASES,2013,13.
APA Liu, Ya-Fen,Gao, Yan,Chen, Mei-Fang,Cao, Bin,Yang, Xiao-Hua,&Wei, Lai.(2013).Etiological analysis and predictive diagnostic model building of community-acquired pneumonia in adult outpatients in Beijing, China.BMC INFECTIOUS DISEASES,13.
MLA Liu, Ya-Fen,et al."Etiological analysis and predictive diagnostic model building of community-acquired pneumonia in adult outpatients in Beijing, China".BMC INFECTIOUS DISEASES 13(2013).
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