Diagnosis of Periprosthetic Joint Infection Using Polymerase Chain Reaction: An Updated Systematic Review and Meta-Analysis

Surg Infect (Larchmt). 2018 Aug/Sep;19(6):555-565. doi: 10.1089/sur.2018.014. Epub 2018 Jun 19.

Abstract

Background: We aim to update a meta-analysis to evaluate the efficiency of polymerase chain reaction (PCR) for diagnosis of periprosthetic joint infection (PJI) because different types of PCR assays have yielded variable diagnostic efficiency from 2013.

Methods: We conducted our systematic review by searching for keywords in online databases from 2013 to May 2017. Studies were chosen based on inclusion and exclusion criteria and the quality of included studies was assessed. Pooled sensitivity and specificity were compared with other synovial fluid biomarkers. A total of 20 studies, comprising 2,526 participants were assessed.

Results: The pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were 0.76 (95% confidence interval [CI]: 0.65-0.85), 0.94 (95% CI: 0.92-0.95), and 0.94 (95% CI: 0.92-0.96), respectively. Meta-regression analysis indicated that use of specific genes, fresh samples, and more than one sample per patient may improve sensitivity.

Conclusions: Although novel PCR assays have been developed, the sensitivity of PCR for the diagnosis of PJI had decreased compared with the previous meta-analysis (0.86, 95% CI: 0.77-0.92), whereas the high specificity is reliable for excluding PJI. Novel synovial fluid biomarker such as α-defensin, which possesses pooled sensitivity between 0.96 and 1.00, might be more efficient than PCR in PJI diagnosis.

Keywords: meta-analysis; polymerase chain reaction; prosthetic joint infection; synovial fluid biomarkers.

Publication types

  • Meta-Analysis
  • Review
  • Systematic Review

MeSH terms

  • Biomarkers / analysis
  • Humans
  • Joint Prosthesis / adverse effects*
  • Polymerase Chain Reaction*
  • Prosthesis-Related Infections / diagnosis*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Synovial Fluid / chemistry

Substances

  • Biomarkers