Evidence map›Paper›PMID 37349686›Full record

ArticleBMC infectious diseases2023

Characterization of periprosthetic environment microbiome in patients after total joint arthroplasty and its potential correlation with inflammation.

Hao Li, Jun Fu, Niu Erlong, Rui Li, Chi Xu, Libo Hao, Jiying Chen, Wei Chai

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
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

8 authors at 2 institutions in 1 country.

Hao LiMedical School of Chinese PLA, Beijing, People's Republic of China.ORCID http://orcid.org/0000-0003-4704-3174
Jun FuDepartment of Orthopedic Surgery, The First Medical Center, Chinese PLA General Hospital, 28 Fuxing Road, Beijing, People's Republic of China.ORCID http://orcid.org/0000-0002-8692-6810
Niu ErlongDepartment of Orthopedics, 305 Hospital of PLA, Beijing, People's Republic of China.
Rui LiSenior Department of Orthopedics, Fourth Medical Center, Chinese PLA General Hospital, Beijing, People's Republic of China.
Chi XuDepartment of Orthopedic Surgery, The First Medical Center, Chinese PLA General Hospital, 28 Fuxing Road, Beijing, People's Republic of China.ORCID http://orcid.org/0000-0003-4211-0657
Libo HaoDepartment of Orthopedic Surgery, The First Medical Center, Chinese PLA General Hospital, 28 Fuxing Road, Beijing, People's Republic of China.ORCID http://orcid.org/0000-0003-3052-8714
Jiying ChenDepartment of Orthopedic Surgery, The First Medical Center, Chinese PLA General Hospital, 28 Fuxing Road, Beijing, People's Republic of China. chenjiyingpla@sina.com.ORCID http://orcid.org/0000-0001-8166-4658
Wei ChaiDepartment of Orthopedic Surgery, The First Medical Center, Chinese PLA General Hospital, 28 Fuxing Road, Beijing, People's Republic of China. chenjiyingpla@sina.com.ORCID http://orcid.org/0000-0001-8781-9745
Chinese PLA General Hospital · CNPLA 306 Hospital · CN

Funding

National Key Research and Development Program of China No.2020YFC2004900Youth Project of National Natural Science Foundation of China No.82102585
6 · The paper itself

Abstract

aimsPeriprosthetic joint infection (PJI) is one of the most serious complications after total joint arthroplasty (TJA) but the characterization of the periprosthetic environment microbiome after TJA remains unknown. Here, we performed a prospective study based on metagenomic next-generation sequencing to explore the periprosthetic microbiota in patients with suspected PJI.

methodsWe recruited 28 patients with culture-positive PJI, 14 patients with culture-negative PJI, and 35 patients without PJI, which was followed by joint aspiration, untargeted metagenomic next-generation sequencing (mNGS), and bioinformatics analysis. Our results showed that the periprosthetic environment microbiome was significantly different between the PJI group and the non-PJI group. Then, we built a "typing system" for the periprosthetic microbiota based on the RandomForest Model. After that, the 'typing system' was verified externally.

resultsWe found the periprosthetic microbiota can be classified into four types generally: "Staphylococcus type," "Pseudomonas type," "Escherichia type," and "Cutibacterium type." Importantly, these four types of microbiotas had different clinical signatures, and the patients with the former two microbiota types showed obvious inflammatory responses compared to the latter ones. Based on the 2014 Musculoskeletal Infection Society (MSIS) criteria, clinical PJI was more likely to be confirmed when the former two types were encountered. In addition, the Staphylococcus spp. with compositional changes were correlated with C-reactive protein levels, the erythrocyte sedimentation rate, and the synovial fluid white blood cell count and granulocyte percentage.

conclusionsOur study shed light on the characterization of the periprosthetic environment microbiome in patients after TJA. Based on the RandomForest model, we established a basic "typing system" for the microbiota in the periprosthetic environment. This work can provide a reference for future studies about the characterization of periprosthetic microbiota in periprosthetic joint infection patients.

Indexed as

Arthritis, InfectiousArthroplasty, Replacement, HipMicrobiotaProsthesis-Related InfectionsArthroplastyHumansInflammationProspective StudiesRetrospective StudiesSensitivity and SpecificityStaphylococcusMetagenomic next generation sequencingMicrobiomeMicrobiotaPeriprosthetic joint infectionPolymicrobial infectionTotal joint arthroplasty

Identifiers

PMID37349686
PMCPMC10286366
OpenAlexW4381683535

What OpenQuestion holds

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LicenceCC BY
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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.