Clinical Research Directory

Preop Biomarkers as Outcome Predictors in 2 Stage Revision Surgery for PJI

Sponsor: Fondazione Policlinico Universitario Agostino Gemelli IRCCS

Summary

With the progressive ageing of the population, a significant increase in the incidence of skeletal fractures-particularly of the proximal femur-as well as degenerative conditions such as osteoarthritis has been observed, for which joint arthroplasty represents the treatment of choice. However, this procedure is not free from complications; beyond technical and mechanical issues related to potential implant malpositioning, one of the most feared is periprosthetic joint infection (PJI), which poses a major challenge in terms of clinical management and prognostic impact. Therapeutic strategies for PJI range from debridement with retention of the implant and exchange of modular components (DAIR/DAPRI) to complete implant removal with insertion of an articulating spacer, often followed by a subsequent reimplantation procedure. These approaches require prolonged antibiotic regimens, potentially exerting a negative effect on renal function, particularly in cases of extended exposure to nephrotoxic agents. Despite the clinical relevance of this issue, the current literature still provides limited evidence regarding the identification of inexpensive and readily available biomarkers capable of predicting treatment outcomes in PJI, especially in patients undergoing spacer implantation followed by reimplantation. Recent literature has increasingly explored the use of biomarkers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic inflammation response index (SIRI), and others to characterize inflammatory and nutritional status, and to investigate possible associations between these markers and the outcomes of selected surgical procedures. The availability of predictive markers could optimize therapeutic management by reducing the risk of infection recurrence and improving postoperative risk stratification.

Official title: Identification of Pre-prosthetic Revision Markers Predictive of Outcome in Patients With Periprosthetic Infection

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