Etiological analysis and predictive diagnostic model building of community-acquired pneumonia in adult outpatients in Beijing, China

BMC Infectious Diseases

Lai Wei¹  Xiao-Hua Yang¹  Bin Cao²  Mei-Fang Chen¹  Yan Gao¹  Ya-Fen Liu¹ 

[1] Peking University People’s Hospital, Department of Infectious Disease, Peking University Hepatology Institute, No. 11, Xizhimen South Street, Beijing 100044, P. R. China;Department of Infectious Diseases and Clinical Microbiology, Beijing Chao-Yang Hospital, Capital Medical University, No. 8, Gongti South Road, Chaoyang District, Beijing 100020, P. R. China

关键词: ROC curve;    Polymerase chain reaction;    Virus;    Pneumonia;    Diagnosis;    Epidemiology;    Etiology;    Community-acquired pneumonia;   

Others  :  1147173
DOI  :  10.1186/1471-2334-13-309

 received in 2012-06-25, accepted in 2013-07-05,  发布年份 2013

【 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) × 10⁹/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.

【 授权许可】

   
2013 Liu et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

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