ArticleTheScientificWorldJournal2013
Molecular diagnosis of periprosthetic joint infection by quantitative RT-PCR of bacterial 16S ribosomal RNA.
Article in TheScientificWorldJournal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 15 citations in OpenAlex.
- Review
- Next generation sequencing for pathogen detection in periprosthetic joint infections.EFORT open reviews · 2021Review
- Detecting the presence of bacterial RNA by polymerase chain reaction in low volumes of preoperatively aspirated synovial fluid from prosthetic joint infections.Bone & joint research · 2020Article
- Culture-Negative Periprosthetic Joint Infection: An Update on What to Expect.JB & JS open access · 2018Article
- Comparison of culture and broad-range polymerase chain reaction methods for diagnosing periprosthetic joint infection: analysis of joint fluid, periprosthetic tissue, and sonicated fluid.International orthopaedics · 2018Article
- Detecting the Presence of Bacterial DNA and RNA by Polymerase Chain Reaction to Diagnose Suspected Periprosthetic Joint Infection after Antibiotic Therapy.Orthopaedic surgery · 2018Article
- Wear Particles Impair Antimicrobial Activity Via Suppression of Reactive Oxygen Species Generation and ERK1/2 Phosphorylation in Activated Macrophages.Inflammation · 2015Article
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 at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The diagnosis of periprosthetic joint infection is sometimes straightforward with purulent discharge from the fistula tract communicating to the joint prosthesis. However it is often difficult to differentiate septic from aseptic loosening of prosthesis because of the high culture-negative rates in conventional microbiologic culture. This study used quantitative reverse transcription polymerase chain reaction (RT-qPCR) to amplify bacterial 16S ribosomal RNA in vitro and in 11 clinical samples. The in vitro analysis demonstrated that the RT-qPCR method was highly sensitive with the detection limit of bacterial 16S rRNA being 0.148 pg/ μ l. Clinical specimens were analyzed using the same protocol. The RT-qPCR was positive for bacterial detection in 8 culture-positive cases (including aerobic, anaerobic, and mycobacteria) and 2 culture-negative cases. It was negative in one case that the final diagnosis was confirmed without infection. The molecular diagnosis of bacterial infection using RT-qPCR to detect bacterial 16S rRNA around a prosthesis correlated well with the clinical findings. Based on the promising clinical results, we were attempting to differentiate bacterial species or drug-resistant strains by using species-specific primers and to detect the persistence of bacteria during the interim period before the second stage reimplantation in a larger scale of clinical subjects.
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.