Evidence map›Paper›PMID 37891467›Full record

ArticleBMC microbiology2023

Composition of pathogenic microorganism in chronic osteomyelitis based on metagenomic sequencing and its application value in etiological diagnosis.

Kang Zhang, Yu-Zhe Bai, Chang Liu, Shan-Shan Liu, Xin-Xin Lu, Run-Gong Yang

Open access · goldAbstract read
In one paragraph

Article in BMC microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
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

6 citing papers in PubMed, 8 citations in OpenAlex.

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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

6 authors at 3 institutions in 1 country.

Kang Zhang *Laboratory Medicine of Beijing Tongren Hospital affiliated to Capital Medical University, Beijing, China.
Yu-Zhe Bai *Department of Tissue Repair and Regeneration, The First Medical Center of PLA General Hospital, Beijing, China.
Chang LiuClinical Laboratory of Tsinghua University Hospital, Beijing, China.
Shan-Shan LiuLaboratory Medicine of Beijing Tongren Hospital affiliated to Capital Medical University, Beijing, China.
Xin-Xin LuLaboratory Medicine of Beijing Tongren Hospital affiliated to Capital Medical University, Beijing, China. luxinxin2009@126.com.
Run-Gong YangDepartment of Tissue Repair and Regeneration, The First Medical Center of PLA General Hospital, Beijing, China.
Beijing Tongren Hospital · CNChinese PLA General Hospital · CNBeijing Hua Xin Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraditionally, conventional microbiological culture methods have been used to detect pathogenic microorganisms in chronic osteomyelitis. However, these methods have been found to have a low detection rate, complicating the precise guidance of infection treatment. This study employed metagenomic next-generation sequencing (mNGS) to detect these microorganisms in chronic osteomyelitis with three main objectives: 1). Gain a deeper understanding of the composition of pathogenic microorganisms in chronic osteomyelitis. 2). Compare the microbial detection rates between mNGS and the standard culture methods used in laboratories to enhance the effectiveness of the traditional culture methods. 3). Explore the potential of mNGS in etiological diagnosis.

methodsFifty clinically confirmed intraoperative bone tissue samples of chronic osteomyelitis from January 2021 to December 2021 were collected and subjected to mNGS and microbiological testing, respectively. The orthopaedic surgeon combined clinical manifestations and related examinations to determine the causative pathogens.

resultsThe culture method obtained 29 aerobic and parthenogenic anaerobic bacteria, 3 specific anaerobic bacteria, and 1 yeast-like fungus. Thirty-six aerobic and parthenogenic anaerobic bacteria, 11 specific anaerobic bacteria, and 1 yeast-like fungus were obtained by mNGS, and 2 Mycobacterium tuberculosis(MTB) strains were detected. However, there was no significant difference in the overall positive detection rate between mNGS and the culture method (P = 0.07), and the two were not statistically significant in detecting aerobic and partly anaerobic bacteria (P = 0.625). But, mNGS was significantly superior to culture in detecting anaerobic bacteria and Mycobacterium tuberculosis (P<0.05).

conclusionsThe mNGS method has enhanced our understanding of the distribution of pathogenic microorganisms in chronic osteomyelitis. Traditional culture methods help isolate and cultivate aerobic and facultative anaerobic bacteria, and fungi, and are also utilized for antibacterial drug sensitivity tests. However, mNGS has shown superior capabilities in detecting anaerobic bacteria, MTB, and mixed infection bacteria. This finding offers invaluable guidance for improving laboratory microbial culture and detection conditions. Hence, mNGS should be judiciously used for chronic osteomyelitis, and PCR can be implemented for certain difficult-to-culture microorganisms, such as MTB.

Indexed as

CoinfectionMycobacterium tuberculosisOsteomyelitisAnti-Bacterial AgentsHigh-Throughput Nucleotide SequencingHumansMetagenomicsSaccharomyces cerevisiaeSensitivity and SpecificityAnti-Bacterial AgentsApplication valueChronic osteomyelitisCulture methodMicroorganismmNGS

Identifiers

PMID37891467
PMCPMC10612345
OpenAlexW4387968968

What OpenQuestion holds

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Registered trials

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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.