Cargando…
Classification and Drug Resistance Analysis of Pathogenic Bacteria in Patients with Bacterial Pneumonia in Emergency Intensive Care Unit
OBJECTIVE: This study aimed to compare the identification efficiency of metagenome next generation sequencing (mNGS) and traditional methods in detecting pathogens in patients with severe bacterial pneumonia (BP) and further analyze the drug resistance of common pathogens. METHODS: A total of 180 pa...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9546695/ https://www.ncbi.nlm.nih.gov/pubmed/36262997 http://dx.doi.org/10.1155/2022/6980091 |
_version_ | 1784805100605145088 |
---|---|
author | Yin, Kai Liu, Ling Fan, Guofeng |
author_facet | Yin, Kai Liu, Ling Fan, Guofeng |
author_sort | Yin, Kai |
collection | PubMed |
description | OBJECTIVE: This study aimed to compare the identification efficiency of metagenome next generation sequencing (mNGS) and traditional methods in detecting pathogens in patients with severe bacterial pneumonia (BP) and further analyze the drug resistance of common pathogens. METHODS: A total of 180 patients with severe BP who were admitted to our hospital from June 2017 to July 2020 were selected as the research objects. Alveolar lavage fluid from the patients were collected, and pathogens were detected by the mNGS technology and traditional etiological detection technology. Common pathogens detected by mNGS were tested for the drug sensitivity test. The difference between mNGS and traditional detection method in the identification of pathogenic bacteria in severe BP patients was compared, and the distribution characteristics and drug resistance of pathogenic bacteria were analyzed. RESULTS: The positive rate of mNGS detection was 92.22%, which was significantly higher than that of the traditional culture method (58.33%, P < 0.05). 347 strains of pathogenic bacteria were detected by mNGS, including 256 strains of Gram-negative bacteria (G(−)), 89 strains of Gram-positive bacteria (G(+)), and 2 strains of fungi. Among G(−) bacteria, Acinetobacter baumannii had higher resistance to piperacillin/tazobactam, ceftazidime, imipenem, levofloxacin, amikacin, ciprofloxacin, gentamicin, and the lowest resistance to tigecycline. The resistance of Klebsiella pneumoniae to piperacillin/tazobactam and ceftazidime was higher. Pseudomonas aeruginosa had low resistance to all the drugs. Escherichia coli had high drug resistance to most drugs, and the drug resistant rates to cefoperazone/sulbactam, piperacillin/tazobactam, ceftazidime, imipenem, and gentamicin were all more than 50.00%. G(+) bacteria had high resistance to penicillin, azithromycin, amoxicillin and levofloxacin, and amoxicillin and levofloxacin had high resistance, up to 100.00%. CONCLUSION: mNGS has high sensitivity for the identification of pathogenic bacteria in patients with BP. G(−) bacteria were the main pathogens of BP, but both G(−) and G(+) bacteria had high resistance to a variety of antibacterial drugs. |
format | Online Article Text |
id | pubmed-9546695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-95466952022-10-18 Classification and Drug Resistance Analysis of Pathogenic Bacteria in Patients with Bacterial Pneumonia in Emergency Intensive Care Unit Yin, Kai Liu, Ling Fan, Guofeng Contrast Media Mol Imaging Research Article OBJECTIVE: This study aimed to compare the identification efficiency of metagenome next generation sequencing (mNGS) and traditional methods in detecting pathogens in patients with severe bacterial pneumonia (BP) and further analyze the drug resistance of common pathogens. METHODS: A total of 180 patients with severe BP who were admitted to our hospital from June 2017 to July 2020 were selected as the research objects. Alveolar lavage fluid from the patients were collected, and pathogens were detected by the mNGS technology and traditional etiological detection technology. Common pathogens detected by mNGS were tested for the drug sensitivity test. The difference between mNGS and traditional detection method in the identification of pathogenic bacteria in severe BP patients was compared, and the distribution characteristics and drug resistance of pathogenic bacteria were analyzed. RESULTS: The positive rate of mNGS detection was 92.22%, which was significantly higher than that of the traditional culture method (58.33%, P < 0.05). 347 strains of pathogenic bacteria were detected by mNGS, including 256 strains of Gram-negative bacteria (G(−)), 89 strains of Gram-positive bacteria (G(+)), and 2 strains of fungi. Among G(−) bacteria, Acinetobacter baumannii had higher resistance to piperacillin/tazobactam, ceftazidime, imipenem, levofloxacin, amikacin, ciprofloxacin, gentamicin, and the lowest resistance to tigecycline. The resistance of Klebsiella pneumoniae to piperacillin/tazobactam and ceftazidime was higher. Pseudomonas aeruginosa had low resistance to all the drugs. Escherichia coli had high drug resistance to most drugs, and the drug resistant rates to cefoperazone/sulbactam, piperacillin/tazobactam, ceftazidime, imipenem, and gentamicin were all more than 50.00%. G(+) bacteria had high resistance to penicillin, azithromycin, amoxicillin and levofloxacin, and amoxicillin and levofloxacin had high resistance, up to 100.00%. CONCLUSION: mNGS has high sensitivity for the identification of pathogenic bacteria in patients with BP. G(−) bacteria were the main pathogens of BP, but both G(−) and G(+) bacteria had high resistance to a variety of antibacterial drugs. Hindawi 2022-09-30 /pmc/articles/PMC9546695/ /pubmed/36262997 http://dx.doi.org/10.1155/2022/6980091 Text en Copyright © 2022 Kai Yin et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Yin, Kai Liu, Ling Fan, Guofeng Classification and Drug Resistance Analysis of Pathogenic Bacteria in Patients with Bacterial Pneumonia in Emergency Intensive Care Unit |
title | Classification and Drug Resistance Analysis of Pathogenic Bacteria in Patients with Bacterial Pneumonia in Emergency Intensive Care Unit |
title_full | Classification and Drug Resistance Analysis of Pathogenic Bacteria in Patients with Bacterial Pneumonia in Emergency Intensive Care Unit |
title_fullStr | Classification and Drug Resistance Analysis of Pathogenic Bacteria in Patients with Bacterial Pneumonia in Emergency Intensive Care Unit |
title_full_unstemmed | Classification and Drug Resistance Analysis of Pathogenic Bacteria in Patients with Bacterial Pneumonia in Emergency Intensive Care Unit |
title_short | Classification and Drug Resistance Analysis of Pathogenic Bacteria in Patients with Bacterial Pneumonia in Emergency Intensive Care Unit |
title_sort | classification and drug resistance analysis of pathogenic bacteria in patients with bacterial pneumonia in emergency intensive care unit |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9546695/ https://www.ncbi.nlm.nih.gov/pubmed/36262997 http://dx.doi.org/10.1155/2022/6980091 |
work_keys_str_mv | AT yinkai classificationanddrugresistanceanalysisofpathogenicbacteriainpatientswithbacterialpneumoniainemergencyintensivecareunit AT liuling classificationanddrugresistanceanalysisofpathogenicbacteriainpatientswithbacterialpneumoniainemergencyintensivecareunit AT fanguofeng classificationanddrugresistanceanalysisofpathogenicbacteriainpatientswithbacterialpneumoniainemergencyintensivecareunit |