ArticleBone & joint research2019
Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing.
Article in Bone & joint research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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.
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.
Who cites it
26 citing papers in PubMed.
- Pathogen Detection in Spinal Infections: Next-Generation Sequencing Versus Conventional Microbiological Methods.Current medical science · 2025Article
- Evaluation of High-Throughput Gene Chip Array for Enhanced Diagnosis of Bone and Joint Infections: A Comparative Analysis with mNGS and Conventional Culture Methods.Infection and drug resistance · 2025Article
- Are Red Blood Cell Distribution Width and Platelet Count Useful for Diagnosing Periprosthetic Joint Infection in Patients Undergoing Re-Revision Arthroplasty.Orthopaedic surgery · 2024Article
- Potentially pathogenic culturable bacteria in hemodialysis waters.BMC microbiology · 2024Article
- Enhancing Pathogen Detection in Implant-Related Infections through Chemical Antibiofilm Strategies: A Comprehensive Review.Antibiotics (Basel, Switzerland) · 2024Review
- Exploring the Microbial Landscape of Bone and Joint Infections: An Analysis Using 16S rRNA Metagenome Sequencing.Infection and drug resistance · 2024Article
- Promising applications of D-amino acids in periprosthetic joint infection.Bone research · 2023Review
- Serum procalcitonin has no significance in the diagnosis of periprosthesis joint infection before total hip and knee replacement.Frontiers in surgery · 2023Article
- Polymicrobial Infections and Biofilms: Clinical Significance and Eradication Strategies.Antibiotics (Basel, Switzerland) · 2022Review
- The Screening of Fixation-Related Infection in Patients Undergoing Conversion Total Hip Arthroplasty after Failed Internal Fixation of Hip Fractures: A Single-Central Retrospective Study.Orthopaedic surgery · 2022Article
- A Journey into Animal Models of Human Osteomyelitis: A Review.Microorganisms · 2022Review
- Potential Blood Biomarkers for Diagnosing Periprosthetic Joint Infection: A Single-Center, Retrospective Study.Antibiotics (Basel, Switzerland) · 2022Article
- Nanopore 16S sequencing enhances the detection of bacterial meningitis after neurosurgery.Annals of clinical and translational neurology · 2022Article
- Diagnosing Fracture-Related Infections: Where Are We Now?Journal of clinical microbiology · 2022Article
- Plasma levels of D-dimer and fibrin degradation product are unreliable for diagnosing periprosthetic joint infection in patients undergoing re-revision arthroplasty.Journal of orthopaedic surgery and research · 2021Article
- An update about molecular biology techniques to detect orthopaedic implant-related infections.EFORT open reviews · 2021Review
- Think Twice before Prescribing Antibiotics for That Swollen Knee: The Influence of Antibiotics on the Diagnosis of Periprosthetic Joint Infection.Antibiotics (Basel, Switzerland) · 2021Review
- Article
- Optimal concentration of ethylenediaminetetraacetic acid as an irrigation solution additive to reduce infection rates in rat models of contaminated wound.Bone & joint research · 2021Article
- Clinical Pathogen Genomics.Clinics in laboratory medicine · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesProsthetic joint infection (PJI) is the most common cause of arthroplasty failure. However, infection is often difficult to detect by conventional bacterial cultures, for which false-negative rates are 23% to 35%. In contrast, 16S rRNA metagenomics has been shown to quantitatively detect unculturable, unsuspected, and unviable pathogens. In this study, we investigated the use of 16S rRNA metagenomics for detection of bacterial pathogens in synovial fluid (SF) from patients with hip or knee PJI.
methodsWe analyzed the bacterial composition of 22 SF samples collected from 11 patients with PJIs (first- and second-stage surgery). The V3 and V4 region of bacteria was assessed by comparing the taxonomic distribution of the 16S rDNA amplicons with microbiome sequencing analysis. We also compared the results of bacterial detection from different methods including 16S metagenomics, traditional cultures, and targeted Sanger sequencing.
resultsPolymicrobial infections were not only detected, but also characterized at different timepoints corresponding to first- and second-stage exchange arthroplasty. Similar taxonomic distributions were obtained by matching sequence data against SILVA, Greengenes, and The National Center for Biotechnology Information (NCBI). All bacteria isolated from the traditional culture could be further identified by 16S metagenomics and targeted Sanger sequencing.
conclusionThe data highlight 16S rRNA metagenomics as a suitable and promising method to detect and identify infecting bacteria, most of which may be uncultivable. Importantly, the method dramatically reduces turnaround time to two days rather than approximately one week for conventional cultures.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.