Evidence map›Paper›PMID 36386420›Full record

ArticleInfection and drug resistance2022

Analysis of Metagenomic Next-Generation Sequencing Results of 25 Pus Samples.

Yuru Shi, Jing Wu, Ting Liu, Li Yue, Yang Liu, Yan Gu, Yingjie Qi

Abstract read
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Article in Infection and drug resistance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yuru ShiDepartment of Clinical Laboratory, Infection Hospital Area of the First Affiliated Hospital of University of Science and Technology of China (Hefei Infectious Disease Hospital), Hefei, 230022, People's Republic of China.
Jing WuDepartment of Clinical Laboratory, Infection Hospital Area of the First Affiliated Hospital of University of Science and Technology of China (Hefei Infectious Disease Hospital), Hefei, 230022, People's Republic of China.ORCID 0000-0003-1931-4678
Ting LiuDepartment of Clinical Laboratory, Infection Hospital Area of the First Affiliated Hospital of University of Science and Technology of China (Hefei Infectious Disease Hospital), Hefei, 230022, People's Republic of China.
Li YueDepartment of Clinical Laboratory, Infection Hospital Area of the First Affiliated Hospital of University of Science and Technology of China (Hefei Infectious Disease Hospital), Hefei, 230022, People's Republic of China.
Yang LiuDepartment of Clinical Laboratory, Infection Hospital Area of the First Affiliated Hospital of University of Science and Technology of China (Hefei Infectious Disease Hospital), Hefei, 230022, People's Republic of China.
Yan GuDepartment of Clinical Laboratory, Infection Hospital Area of the First Affiliated Hospital of University of Science and Technology of China (Hefei Infectious Disease Hospital), Hefei, 230022, People's Republic of China.
Yingjie QiDepartment of Clinical Laboratory, Infection Hospital Area of the First Affiliated Hospital of University of Science and Technology of China (Hefei Infectious Disease Hospital), Hefei, 230022, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To explore the clinical value of detecting pathogens in pus samples by metagenomic next-generation sequencing (mNGS). Methods: The 25 pus samples from infected patients were collected in this research. The positive rate and consistency of pathogenic bacteria detected by mNGS and conventional methods were compared. The pathogen types detected by the two methods were analyzed. Furthermore, the modifications of antibiotic treatment therapy were also evaluated based on mNGS results. Results: The sensitivity of mNGS method in detecting pathogenic bacteria in pus samples was better than that of conventional method (96% vs 40%; P < 0.01). Only 10 samples were detected pathogens by conventional methods, but 24 samples were detected by mNGS method. In specific, the results of conventional methods showed 10 samples had 11 kinds of pathogenic bacteria, of which 9 samples were single pathogen and 1 sample had two kinds of pathogenic bacteria. The results of mNGS method showed 24 samples were detected with 54 kinds of pathogenic bacteria, of which 15 samples were detected with single pathogen, and 9 samples were detected with two or more kinds of pathogenic bacteria. The two methods had 9(36%) consistent results, 14 (56%) completely different results, and 2 (8%) partially consistent results, and the kappa value was 0.19. Notably, mNGS could detect viruses, anaerobic bacteria, and other uncommon pathogens simultaneously. Conclusion: The application of mNGS in the detection of pus specimens from different parts not only have high accuracy rate and also reduce the turnaround time of diagnosis. In addition, the performance of mNGS detection of anaerobic bacteria and caustic bacteria is better than conventional methods. The mNGS diagnosis in pus sample may play an important role in clinical diagnosis and treatment strategy decisions.

Indexed as

mNGSpathogenpus specimens

Identifiers

PMID36386420
PMCPMC9653029

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.