Prognostic Value of C-Reactive Protein in Primary Total Hip Arthroplasty

<b>Background/Objectives</b>: Periprosthetic joint infections (PJIs) are feared complications in arthroplasty and are associated with an increased mortality rate. PJI prevention is of paramount importance since treatment is difficult. In case of an infection, it is crucial to diagnose it at an early stage in order to initiate adequate therapy. The Musculoskeletal Infection Society (MSIS) proposed a catalog of different major and minor diagnostic criteria in 2011 to define a PJI. They were adapted in the following years. One of these criteria is the blood level of C-reactive protein (CRP). CRP is a non-specific acute-phase protein that also increases in response to various non-infectious inflammatory responses. CRP is also routinely obtained prior to total hip arthroplasty (THA) to screen for possible contraindications for arthroplasty such as an acute infection. The validity of this approach has rarely been investigated. The aim of this study was to evaluate the diagnostic value of perioperative CRP in patients receiving a THA. <b>Methods</b>: A total of 239 patients were included in this study and retrospectively analyzed. CRP values were obtained preoperatively and three values postoperatively. Sensitivity, specificity, area under the curve (AUC) and optimal thresholds were calculated. <b>Results</b>: In the whole group, 10 patients developed a PJI. No significance was demonstrated between patients without and with later PJI in terms of preoperative CRP (<i>p</i> = 0.182), postoperative CRP (<i>p</i> = 0.167), relative CRP increase (<i>p</i> = 0.684) and respective CRP differences (<i>p</i> = 0.456). We were not able to find cut-off values with adequate sensitivity and specificity. <b>Conclusions</b>: Perioperative CRP values do not seem to be helpful in predicting further PJI. Rather, they should be used as a screening tool to detect ongoing infections in the individual patient prior to THA. This trial should encourage studies with more statistical power due to the small effect sizes.