Multiplex PCR in septic arthritis and periprosthetic joint infections microorganism identification: Results from the application of a new molecular testing diagnostic algorithm.

ABSTRACT

Purpose: Pathogen identification is key in the treatment of septic arthritis (SA) and periprosthetic joint infections (PJI). This study evaluates the outcome of the application of a new, score-based SA and PJI diagnostic algorithm, which includes the execution of molecular testing on synovial fluid. Methods: A score-based diagnostic algorithm, which includes serologic and synovial fluid markers determination using multiplex PCR (mPCR) and Next Generation Sequencing (NGS) molecular testing, has been applied to a consecutive series of patients with clinically suspected SA or PJI. Patients with a score ≥6 underwent synovial fluid molecular testing, together with traditional culture, to identify the pathogen and its genetically determined antibiotic resistance. Results: One hundred and seventeen joints in 117 patients (62.5% women; average age 73 years) met the criteria for possible SA/PJI. The affected joint was the knee in 87.5% (joint replacement 66.5%; native joint 21%) and the hip in 12.5% (all replaced joints). 43/117 patients (36.7%) were ultimately diagnosed with SA/PJI. Among the various testing technologies applied, mPCR was the main determinant for pathogen identification in 63%, standard culture in 26%, and mNGS in 11%. Staphylococcus aureus and Enterococcus faecalis were the top two microorganisms identified by mPCR, while Staphylococcus epidermidis was the prevalent organism identified by NGS. mPCR detected the presence/absence of the genetically determined antibiotic resistance of all identified microorganisms. The average timeframe for pathogen identification was 3.13 h for mPCR, 4.5 days for culture, and 3.2 days for NGS. Conclusions: Molecular diagnostic technologies represent an innovative screening for fast microorganism identification when a joint infection is clinically suspected. Level of Evidence Level IV, case series.