Evidence map›Paper›PMID 39232674›Full record

ArticleBMC infectious diseases2024

The clinical application value of multi-site mNGS detection of patients with sepsis in intensive care units.

Ting-Jun Pan, Wei-Wen Luo, Song-Sheng Zhang, Jie-Yao Xie, Zhou Xu, Ying-Yu Zhong, Xiao-Fen Zou, Hui-Juan Gong, Mei-Ling Ye

Abstract read
In one paragraph

Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Ting-Jun PanThe Fourth Department of Intensive Care Medicine, Meizhou People's Hospital, Meizhou, Guangdong, 514031, China. 15820390121@163.com.
Wei-Wen LuoThe Fourth Department of Intensive Care Medicine, Meizhou People's Hospital, Meizhou, Guangdong, 514031, China.
Song-Sheng ZhangThe Fourth Department of Intensive Care Medicine, Meizhou People's Hospital, Meizhou, Guangdong, 514031, China.
Jie-Yao XieThe Fourth Department of Intensive Care Medicine, Meizhou People's Hospital, Meizhou, Guangdong, 514031, China.
Zhou XuThe Fourth Department of Intensive Care Medicine, Meizhou People's Hospital, Meizhou, Guangdong, 514031, China.
Ying-Yu ZhongThe First Department of Intensive Care Medicine, Meizhou People's Hospital, Meizhou People's Hospital, Meizhou, Guangdong, 514031, China.
Xiao-Fen ZouThe First Department of Intensive Care Medicine, Meizhou People's Hospital, Meizhou People's Hospital, Meizhou, Guangdong, 514031, China.
Hui-Juan GongThe Fourth Department of Intensive Care Medicine, Meizhou People's Hospital, Meizhou, Guangdong, 514031, China.
Mei-Ling YeThe First Department of Intensive Care Medicine, Meizhou People's Hospital, Meizhou People's Hospital, Meizhou, Guangdong, 514031, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis remains a leading cause of mortality in intensive care units, and rapid and accurate pathogen detection is crucial for effective treatment. This study evaluated the clinical application of multi-site metagenomic next-generation sequencing (mNGS) for the diagnosis of sepsis, comparing its performance against conventional methods.

methodsA retrospective analysis was conducted on 69 patients with sepsis consecutively admitted to the Department of Intensive Care Medicine, Meizhou People's Hospital. Samples of peripheral blood and infection sites were collected for mNGS and conventional method tests to compare the positive rate of mNGS and traditional pathogen detection methods and the distribution of pathogens. The methods used in this study included a comprehensive analysis of pathogen consistency between peripheral blood and infection site samples. Additionally, the correlation between the pathogens detected and clinical outcomes was investigated.

resultsOf the patients with sepsis, 57.97% experienced dyspnea, and 65.2% had underlying diseases, with hypertension being the most common. mNGS demonstrated a significantly higher pathogen detection rate (88%) compared to the conventional method tests (26%). The pathogen consistency rate was 60% between plasma and bronchoalveolar lavage fluid samples, and that of plasma and local body fluid samples was 63%. The most frequently detected pathogens were gram-negative bacteria, and Klebsiella pneumonia. There were no significant differences in the clinical features between the pathogens.

conclusionmNGS is significantly superior to conventional methods in pathogen detection. There was a notable high pathogen consistency detection between blood and local body fluid samples, supporting the clinical relevance of mNGS. This study highlights the superiority of mNGS in detecting a broad spectrum of pathogens quickly and accurately.

trial registrationNot applicable.

Indexed as

High-Throughput Nucleotide SequencingIntensive Care UnitsMetagenomicsSepsisAdultAgedAged, 80 and overBacteriaFemaleHumansMaleMiddle AgedRetrospective StudiesConventional method testDiagnoseMetagenomic next-generation sequencingSepsis

Identifiers

PMID39232674
PMCPMC11375821

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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.