ReviewDiagnostics (Basel, Switzerland)2022
Role of Biomarkers in Periprosthetic Joint Infections.
Review in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Metal-artefact-reduction MRI for diagnosing periprosthetic joint infection: a systematic review and meta-analysis.Skeletal radiology · 2026Pooled it
- Complement factors C3 and C5 as tissue biomarkers for differentiating periprosthetic joint infection from aseptic implant failure.European journal of microbiology & immunology · 2026Article
- Calprotectin identified as a key differentially expressed plasma biomarker in periprosthetic joint infection against aseptic failure: a precision health proteomics study.Arthroplasty (London, England) · 2026Article
- Metal artifact reduction sequence MRI in hip periprosthetic joint infection management : a noninvasive reference for infection control before two-stage reimplantation.Bone & joint research · 2026Article
- Synovial fluid proteomic biomarkers in periprosthetic joint infection: A systematic review with gene ontology and protein network analyses.Journal of experimental orthopaedics · 2026Review
- Clinical application of synovial fluid albumin-to-globulin ratio as a novel biomarker in diagnosing chronic periprosthetic joint infection.Frontiers in cellular and infection microbiology · 2026Article
- Application of autoantibody markers based on phage display immunoprecipitation sequencing technology in the diagnosis of periprosthetic joint infections.Frontiers in cellular and infection microbiology · 2026Article
- Evaluation of Heparin-Binding Protein as a novel biomarker for the detection of periprosthetic joint infection.Frontiers in cellular and infection microbiology · 2025Article
- The effect of different preventive strategies during total joint arthroplasty on periprosthetic joint infection: a network meta-analysis.Journal of orthopaedic surgery and research · 2024Article
- CanIndian journal of orthopaedics · 2024Article
- An overview of the current diagnostic approach to Periprosthetic Joint Infections.Orthopedic reviews · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Periprosthetic joint infection (PJI) is one of the most serious complications after joint arthroplasty. The incidence rate of PJI after total joint replacement is 1-3%. Although there are different guidelines and diagnostic criteria used to diagnose PJI, diagnosing PJI is a highly difficult process for orthopedists. The current Musculoskeletal Infection Society (MSIS) criteria are widely used for the diagnosis of PJI. These criteria include results from blood/synovial fluid tests, physical examination, and histological and microbiological analyses of intra-operative samples. However, there is currently no blood or synovial test that can definitively diagnose PJI. To make a more effective diagnosis of PJI, a large number of studies have explored and continue to investigate biomarkers. This review aims to provide general information about serum and synovial markers used for the diagnosis of PJI that may be used to create a database to guide researchers in new studies.
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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.