Role of Serum Biomarkers in Differentiating Periprosthetic Joint Infections from Aseptic Failures after Total Hip Arthroplasties

血清生物标志物在鉴别全髋关节置换术后假体周围关节感染与无菌性失败中的作用

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Abstract

Background/Objectives: Periprosthetic joint infection (PJI) is a disastrous complication after joint replacement procedures as the diagnosis remains a significant challenge. The objective of this study is to assess the accuracy and test the interdependency of the proposed compound serum biomarkers for the diagnosis of PJI after total hip arthroplasties (THA). Methods: From January 2019 to December 2023, 77 consecutive cases that underwent revision total hip arthroplasties (rTHA) were included in a single-retrospective, observational cohort study. A total of 32 arthroplasties were classified as having septic complications using the European Bone and Joint Infection Society (EBJIS) definition from 2021, while the other 45 cases were assigned as aseptic failures (AF). Results: In the univariate analysis between the two groups created, statistically significant differences (p < 0.005) were found for the following variables: time from primary arthroplasty to symptom onset (Time PA-SO), neutrophil count, Lymphocyte count, haematocrit level (HCT) and haemoglobin level (HGB), C-reactive protein (CRP), the neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), monocyte lymphocyte ratio (MLR), systemic inflammation index (SII), systemic inflammation response index (SIRI), and aggregate inflammation systemic index (AISI). The ROC curve analysis showed that the SII (sensitivity 90.6% and specificity 62.2%) and the NLR (sensitivity 84.4% and specificity 64.4%) are the most accurate biomarkers. The multivariate analysis confirmed that NLR > 2.63 (p = 0.006), PLR > 147 (p = 0.021), MLR > 0.31 (p = 0.028), SII > 605.31 (p = 0.002), SIRI > 83.34 (p = 0.024), and AISI > 834.86 (p = 0.011) are all closely related to PJI diagnosis independently. Conclusions: The proposed serum biomarkers can be correlated with PJI diagnosis with the reserve of relatively low specificities.

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