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

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About: Etiological analysis and predictive diagnostic model building of community-acquired pneumonia in adult outpatients in Beijing, China Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Etiological analysis and predictive diagnostic model building of community-acquired pneumonia in adult outpatients in Beijing, China
Creator	Cao, Bin Wei, Lai Gao, Yan Chen, Mei-Fang Liu, Ya-Fen Yang, Xiao-Hua
source	Medline; PMC
abstract	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) × 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.
has issue date	2013-07-09(xsd:dateTime)
bibo:doi	10.1186/1471-2334-13-309
bibo:pmid	23834931
has license	cc-by
sha1sum (hex)	5d04b1e66045a858dd72847b88dcc6a280da3165
schema:url	https://doi.org/10.1186/1471-2334-13-309
resource representing a document's title	Etiological analysis and predictive diagnostic model building of community-acquired pneumonia in adult outpatients in Beijing, China
has PubMed Central identifier	PMC3728139
has PubMed identifier	23834931
schema:publication	BMC Infect Dis
resource representing a document's body	covid:5d04b1e66045a858dd72847b88dcc6a280da3165#body_text
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