Abstract
BackgroundEtiological 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.MethodsA 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.ResultsPathogens 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).ConclusionsGreater 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.
Highlights
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
Physical examinations and laboratory test results of monomicrobial infections, we found that CAP patients infected with M. pneumoniae were significantly younger than those with viruses or bacteria [M. pneumoniae CAP: 32 (18–75); viral CAP: 43 (18–94); bacterial CAP: 48 (18–84), P < 0.05]
We attempted to build viral and M. pneumoniae diagnostic models based on combinations of clinical characteristics from a study population in China
Summary
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. Large-scale epidemiological investigations of adult viral CAP in China are still lacking. We analyzed the etiology of adult CAP in Beijing, China and constructed diagnostic models based on combinations of patient clinical factors. Etiological epidemiology and diagnosis are important issues in adult CAP, with particular challenges in identifying the causative pathogens based on patient clinical features. Shin [8] pointed out that if clinicians do not consider a viral etiology in patients with CAP, they would be unlikely to consider investigations to diagnose respiratory viruses, which would result in the inappropriate use of antibiotics, missed opportunity to consider antiviral treatment and failure to institute appropriate infection control measures. Underestimation of the prevalence of viral CAP and utilization of inappropriate treatment may increase the spread of antibiotic resistance
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