Cargando…

Combined Radiographic Features and Age Can Distinguish Mycoplasma pneumoniae Pneumonia from Other Bacterial Pneumonias: Analysis Using the 16S rRNA Gene Sequencing Data

The study objective was to evaluate chest radiographic features that distinguish Mycoplasma pneumoniae pneumonia (MPP) from other bacterial pneumonias diagnosed based on the bacterial floral analysis with 16S rRNA gene sequencing, using bronchoalveolar lavage fluid samples directly obtained from pne...

Descripción completa

Detalles Bibliográficos
Autores principales: Iwanaga, Yuto, Yamasaki, Kei, Nemoto, Kazuki, Akata, Kentaro, Ikegami, Hiroaki, Uchimura, Keigo, Noguchi, Shingo, Nishida, Chinatsu, Kawanami, Toshinori, Fukuda, Kazumasa, Mukae, Hiroshi, Yatera, Kazuhiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9032927/
https://www.ncbi.nlm.nih.gov/pubmed/35456296
http://dx.doi.org/10.3390/jcm11082201
_version_ 1784692765207035904
author Iwanaga, Yuto
Yamasaki, Kei
Nemoto, Kazuki
Akata, Kentaro
Ikegami, Hiroaki
Uchimura, Keigo
Noguchi, Shingo
Nishida, Chinatsu
Kawanami, Toshinori
Fukuda, Kazumasa
Mukae, Hiroshi
Yatera, Kazuhiro
author_facet Iwanaga, Yuto
Yamasaki, Kei
Nemoto, Kazuki
Akata, Kentaro
Ikegami, Hiroaki
Uchimura, Keigo
Noguchi, Shingo
Nishida, Chinatsu
Kawanami, Toshinori
Fukuda, Kazumasa
Mukae, Hiroshi
Yatera, Kazuhiro
author_sort Iwanaga, Yuto
collection PubMed
description The study objective was to evaluate chest radiographic features that distinguish Mycoplasma pneumoniae pneumonia (MPP) from other bacterial pneumonias diagnosed based on the bacterial floral analysis with 16S rRNA gene sequencing, using bronchoalveolar lavage fluid samples directly obtained from pneumonia lesions. Patients were grouped according to the dominant bacterial phenotype; among 120 enrolled patients with CAP, chest CT findings were evaluated in 55 patients diagnosed with a mono-bacterial infection (one bacterial phylotype occupies more than 80% of all phylotypes in a sample) by three authorized respiratory physicians. Among this relatively small sample size of 55 patients with CAP, 10 had MPP, and 45 had other bacterial pneumonia and were categorized into four groups according to their predominant bacterial phylotypes. We created a new scoring system to discriminate MPP from other pneumonias, using a combination of significant CT findings that were observed in the M. pneumoniae group, and age (<60 years) (MPP–CTA scoring system). When the cutoff value was set to 1, this scoring system had a sensitivity of 80%, a specificity of 93%, a positive predictive value of 73%, and a negative predictive value of 95%. Among the CT findings, centrilobular nodules were characteristic findings in patients with MPP, and a combination of chest CT findings and age might distinguish MPP from other bacterial pneumonias.
format Online
Article
Text
id pubmed-9032927
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-90329272022-04-23 Combined Radiographic Features and Age Can Distinguish Mycoplasma pneumoniae Pneumonia from Other Bacterial Pneumonias: Analysis Using the 16S rRNA Gene Sequencing Data Iwanaga, Yuto Yamasaki, Kei Nemoto, Kazuki Akata, Kentaro Ikegami, Hiroaki Uchimura, Keigo Noguchi, Shingo Nishida, Chinatsu Kawanami, Toshinori Fukuda, Kazumasa Mukae, Hiroshi Yatera, Kazuhiro J Clin Med Article The study objective was to evaluate chest radiographic features that distinguish Mycoplasma pneumoniae pneumonia (MPP) from other bacterial pneumonias diagnosed based on the bacterial floral analysis with 16S rRNA gene sequencing, using bronchoalveolar lavage fluid samples directly obtained from pneumonia lesions. Patients were grouped according to the dominant bacterial phenotype; among 120 enrolled patients with CAP, chest CT findings were evaluated in 55 patients diagnosed with a mono-bacterial infection (one bacterial phylotype occupies more than 80% of all phylotypes in a sample) by three authorized respiratory physicians. Among this relatively small sample size of 55 patients with CAP, 10 had MPP, and 45 had other bacterial pneumonia and were categorized into four groups according to their predominant bacterial phylotypes. We created a new scoring system to discriminate MPP from other pneumonias, using a combination of significant CT findings that were observed in the M. pneumoniae group, and age (<60 years) (MPP–CTA scoring system). When the cutoff value was set to 1, this scoring system had a sensitivity of 80%, a specificity of 93%, a positive predictive value of 73%, and a negative predictive value of 95%. Among the CT findings, centrilobular nodules were characteristic findings in patients with MPP, and a combination of chest CT findings and age might distinguish MPP from other bacterial pneumonias. MDPI 2022-04-14 /pmc/articles/PMC9032927/ /pubmed/35456296 http://dx.doi.org/10.3390/jcm11082201 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Iwanaga, Yuto
Yamasaki, Kei
Nemoto, Kazuki
Akata, Kentaro
Ikegami, Hiroaki
Uchimura, Keigo
Noguchi, Shingo
Nishida, Chinatsu
Kawanami, Toshinori
Fukuda, Kazumasa
Mukae, Hiroshi
Yatera, Kazuhiro
Combined Radiographic Features and Age Can Distinguish Mycoplasma pneumoniae Pneumonia from Other Bacterial Pneumonias: Analysis Using the 16S rRNA Gene Sequencing Data
title Combined Radiographic Features and Age Can Distinguish Mycoplasma pneumoniae Pneumonia from Other Bacterial Pneumonias: Analysis Using the 16S rRNA Gene Sequencing Data
title_full Combined Radiographic Features and Age Can Distinguish Mycoplasma pneumoniae Pneumonia from Other Bacterial Pneumonias: Analysis Using the 16S rRNA Gene Sequencing Data
title_fullStr Combined Radiographic Features and Age Can Distinguish Mycoplasma pneumoniae Pneumonia from Other Bacterial Pneumonias: Analysis Using the 16S rRNA Gene Sequencing Data
title_full_unstemmed Combined Radiographic Features and Age Can Distinguish Mycoplasma pneumoniae Pneumonia from Other Bacterial Pneumonias: Analysis Using the 16S rRNA Gene Sequencing Data
title_short Combined Radiographic Features and Age Can Distinguish Mycoplasma pneumoniae Pneumonia from Other Bacterial Pneumonias: Analysis Using the 16S rRNA Gene Sequencing Data
title_sort combined radiographic features and age can distinguish mycoplasma pneumoniae pneumonia from other bacterial pneumonias: analysis using the 16s rrna gene sequencing data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9032927/
https://www.ncbi.nlm.nih.gov/pubmed/35456296
http://dx.doi.org/10.3390/jcm11082201
work_keys_str_mv AT iwanagayuto combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata
AT yamasakikei combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata
AT nemotokazuki combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata
AT akatakentaro combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata
AT ikegamihiroaki combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata
AT uchimurakeigo combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata
AT noguchishingo combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata
AT nishidachinatsu combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata
AT kawanamitoshinori combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata
AT fukudakazumasa combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata
AT mukaehiroshi combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata
AT yaterakazuhiro combinedradiographicfeaturesandagecandistinguishmycoplasmapneumoniaepneumoniafromotherbacterialpneumoniasanalysisusingthe16srrnagenesequencingdata