Molecular diagnostics for perioperative microbial identification in periprosthetic joint infection: A scoping review and proposal of a diagnostic flow chart

分子诊断在假体周围关节感染围手术期微生物鉴定中的应用:范围界定综述及诊断流程图建议

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Abstract

PURPOSE: Periprosthetic joint infections (PJI) are among the most feared complications of joint reconstruction. Unfortunately, traditional cultures often fail to identify the aetiological agents of PJI. Molecular diagnostics can overcome the limitations of standard synovial fluid culture by utilising information from DNA/RNA samples to identify microbial species. The authors conducted a scoping review to evaluate the current state regarding the use of molecular diagnostics in the decision-making process for the surgical treatment of PJI and to create a flowchart based on molecular diagnostics. METHODS: A scoping review was conducted to provide an overview of the literature on molecular diagnostic techniques for detecting perioperative microbial infections in PJI. The population considered included patients undergoing total hip or knee arthroplasty or replacement, with a focus on molecular diagnostic methods within the perioperative period. The database search encompassed PubMed, Embase, Scopus and the Cochrane Library. RESULTS: Seventy-five articles were included after a preliminary review of 1315 records. Each article was assigned to one of four categories to fulfil the purpose of this review: (1) Polymerase chain reaction (PCR) related studies: n = 18; (2) Next-Generation-Sequencing (NGS) related studies: n = 40; (3) comparative studies, including systematic reviews and meta-analyses, between different molecular diagnostic methodologies: n = 7; and (4) general reviews on nucleic acid-based strategies to detect PJIs: n = 10. CONCLUSIONS: This review confirmed that molecular diagnostics are becoming extremely valuable tools in the decision-making process for PJI treatment. Culture-based techniques still represent the gold standard in PJI microorganism identification, but our review showed that standard culture, in 2025, could be integrated with newer nucleic acid-based strategies. LEVEL OF EVIDENCE: Level I.

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