Incidence, Etiology, and Environmental Risk Factors of Community-Acquired Pneumonia Requiring Hospitalization in China: A 3-Year, Prospective, Age-Stratified, Multicenter Case-Control Study

Plasma proteome analysis and validation of patients with community-acquired pneumonia: A cohort study

PURPOSE

This study aimed to investigate the diagnostic potential of plasma biomarkers of community-acquired pneumonia (CAP) and their severity grading.

EXPERIMENTAL DESIGN

Plasma proteomes from cohort I (n = 32) with CAP were analyzed by data-independent acquisition mass spectrometry (MS). MetaboAnalyst 5.0 was used to statistically evaluate significant differences in proteins from different samples, and demographic and clinical data were recorded for all enrolled patients. Cohort II (n = 80) was used to validate candidate biomarkers. Plasma protein levels were determined using quantitative enzyme-linked immunosorbent assay (ELISA). Correlations were assessed using Pearson's correlation coefficient. A receiver operating characteristic curve was used to verify the association between the variables, CAP diagnosis, and prognosis.

RESULTS

121 differentially expressed proteins (DEPs) were obtained between CAP and controls. These DEPs were mainly aggregated in pathways of phagosome(hsa04145) and complement and coagulation cascades (hsa04610). No significant differential proteins were detected in bacterial, viral, and mixed infection groups. The plasma levels of fetuin-A, alpha-1-antichymotrypsin (AACT), α1-acid glycoprotein (A1AG), and S100A8/S100A9 heterodimers detected by ELISA were consistent with those of MS. AACT, A1AG, S100A8/S100A9 heterodimer, and fetuin-A can potentially be used as diagnostic predictors, and fetuin-A and AACT are potential predictors of SCAP.

CONCLUSIONS AND CLINICAL RELEVANCE

Plasma protein profiling can successfully identify potential biomarkers for CAP diagnosis and disease severity assessment. These biomarkers should be further studied for their clinical application.

Risk factors analysis and prediction model construction for severe pneumonia in older adult patients

Objective

Pneumonia is a common and serious infectious disease that affects the older adult population. Severe pneumonia can lead to high mortality and morbidity in this group. Therefore, it is important to identify the risk factors and develop a prediction model for severe pneumonia in older adult patients.

Method

In this study, we collected data from 1,000 older adult patients who were diagnosed with pneumonia and admitted to the intensive care unit (ICU) in a tertiary hospital. We used logistic regression and machine learning methods to analyze the risk factors and construct a prediction model for severe pneumonia in older adult patients. We evaluated the performance of the model using accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and calibration plot.

Result

We found that age, comorbidities, vital signs, laboratory tests, and radiological findings were associated with severe pneumonia in older adult patients. The prediction model had an accuracy of 0.85, a sensitivity of 0.80, a specificity of 0.88, and an AUC of 0.90. The calibration plot showed good agreement between the predicted and observed probabilities of severe pneumonia.

Conclusion

The prediction model can help clinicians to stratify the risk of severe pneumonia in older adult patients and provide timely and appropriate interventions.

Impacts of environmental factors on the aetiological diagnosis and disease severity of community-acquired pneumonia in China: a multicentre, hospital-based, observational study

Environmental exposures are known to be associated with pathogen transmission and immune impairment, but the association of exposures with aetiology and severity of community-acquired pneumonia (CAP) are unclear. A retrospective observational study was conducted at nine hospitals in eight provinces in China from 2014 to 2019. CAP patients were recruited according to inclusion criteria, and respiratory samples were screened for 33 respiratory pathogens using molecular test methods. Sociodemographic, environmental and clinical factors were used to analyze the association with pathogen detection and disease severity by logistic regression models combined with distributed lag nonlinear models. A total of 3323 CAP patients were included, with 709 (21.3%) having severe illness. 2064 (62.1%) patients were positive for at least one pathogen. More severe patients were found in positive group. After adjusting for confounders, particulate matter (PM) 2.5 and 8-h ozone (O3-8h) were significant association at specific lag periods with detection of influenza viruses and Klebsiella pneumoniae respectively. PM10 and carbon monoxide (CO) showed cumulative effect with severe CAP. Pollutants exposures, especially PM, O3-8h, and CO should be considered in pathogen detection and severity of CAP to improve the clinical aetiological and disease severity diagnosis.

Comparison of next-generation sequencing with traditional methods for pathogen detection in cases of lower respiratory tract infection at a community hospital in Eastern China

Lower respiratory tract infection (LRTI) is still a threat to human health. Metagenomics next-generation sequencing (NGS) provides an efficient and unbiased way to identify LRTI pathogens, and has been shown to have several advantages over traditional methods. However, its application is currently limited in low-resource settings. Our aim was to collect and analyze data on LRTI cases at a county-level community hospital in Eastern China over one year, in order to compare the efficiency of NGS and traditional methods including culture, nucleic acid amplification and antibody techniques. We performed NGS of bronchoalveolar lavage fluid (BALF) for pathogen identification in 71 patients with LRTI. We compared the detection rates, identified pathogens, and turnaround time of NGS with traditional methods. Pathogens were detected using traditional methods in 19 cases, and the results were compared with those obtained with the NGS technique in 60 cases. The pathogen detection rate of NGS (84.5%) was much higher than that of the traditional methods (26.8%). Moreover, with the traditional methods considered the gold standard, the consistency rate between NGS and traditional methods was 68.4%. For the 19 cases in which the traditional method was used, the main pathogens included invasive Aspergillus (5 cases), Pseudomonas aeruginosa (3 cases), Candida albicans (3 cases), and Staphylococcus aureus (2 cases). Among the 60 cases detected by NGS, the main pathogens included Mycobacterium (12 cases), Streptococcus pneumoniae (5 cases), Klebsiella pneumoniae (3 cases), P. aeruginosa (3 cases), Haemophilus influenzae (3 cases), and S. aureus (3 cases), Aspergillus (9 cases), Pneumocystis jiroveci (5 cases), C. albicans (3 cases), Human Papilloma Virus (9 cases), Epstein-Barr virus (8 cases), and parvovirus (6 cases). In addition, 2 cases of chlamydia and 1 case of mycoplasma infection were detected by NGS. The time taken to perform the NGS tests was significantly shorter than that taken with the traditional method. NGS analysis of bronchoalveolar lavage fluid, in combination with traditional pathogen detection methods, can improve the efficiency of pathogen detection. More attention should be paid to the regional epidemic characteristics of infectious pathogens in LRTI.

Nasopharyngeal aspirates in children with severe community-acquired pneumonia collected within 3 days before bronchoscopy can partially reflect the pathogens in bronchoalveolar lavage fluids

BACKGROUND

There is little evidence about consistency between nasopharyngeal and pulmonary pathogens in children with severe pneumonia. This study aims to compare the difference of pathogens between nasopharyngeal aspirates (NPAs) collected before bronchoscopy and bronchoalveolar lavage fluids (BALFs) in children with severe community-acquired pneumonia (SCAP).

METHODS

NPAs and BALFs were collected form pediatric SCAP cases hospitalized from January 2018 to March 2019. NPAs were colleced within 3 days before bronchoscopy. Samples were detected by direct immunofluorescence assay (DFA) for seven respiratory viruses and by routine bacterial culture in the clinical microbiology laboratory. Respiratory syncytial virus (RSV), Adenovirus (ADV), Influenza virus types A, B (IV-A and IV-B), Parainfluenza virus 1-3 (PIV1-3) were detected with a commercial assay. The virological and bacteriological detention results of NPAs were compared with the results of BALFs.

RESULTS

In total 204 cases with mean age of 3.4 ± 2.8 years (IQR, 1 month-14 years) were included in the study. Both NPA and BALF were collected from those cases. The positive rates of pathogen in NPAs and BALFs were 25.0% (51/204) and 36.7% (75/204), respectively (x² = 6.614, P = 0.010). Respiratory viruses were found in 16.1% (33/204) from NPAs and 32.3% (66/204) from BALFs (x² = 14.524, P < 0.001). RSV and ADV were the two most frequent detected viruses in NPAs and BALFs. High consistentcy of pathogens between NPAs and BALFs was observed, and 96.9% (32/33) viruses detected in NPAs were also found in BALFs. While bacteria were isolated from 12.7% (26/204) and 10.7% (22/204) of the two kinds of samples, respectively (x² = 0.378, P = 0.539). In addition, Haemophilus influenzae (HI) was the dominant germ in both samples.

CONCLUSION

The DFA method used to detect seven respiratory viruses from NPAs collected within 3 days before bronchoscopy can partially reflect the pathogens in the lungs in children with SCAP.