Predicting the Exception-CRP and Primary Hip Arthroplasty

Abstract

Background: While primary hip arthroplasty is the most common operative procedure in orthopedic surgery, a periprosthetic joint infection is its most severe complication. Early detection and prediction are crucial. In this study, we aimed to determine the value of postoperative C-reactive protein (CRP) and develop a formula to predict this rare, but devastating complication.

Methods: We retrospectively evaluated 708 patients with primary hip arthroplasty. CRP, white blood cell count (WBC), and several patient characteristics were assessed for 20 days following the operative procedure.

Results: Eight patients suffered an early acute periprosthetic infection. The maximum CRP predicted an infection with a sensitivity and specificity of 75% and 56.9%, respectively, while a binary logistic regression reached values of 75% and 80%. A multinominal logistic regression, however, was able to predict an early infection with a sensitivity and specificity of 87.5% and 78.9%. With a one-phase decay, 71.6% of the postoperative CRP-variance could be predicted.

Conclusion: To predict early acute periprosthetic joint infection after primary hip arthroplasty, a multinominal logistic regression is the most promising approach. Including five parameters, an early infection can be predicted on day 5 after the operative procedure with 87.5% sensitivity, while it can be excluded with 78.9% specificity.

Keywords: C-reactive protein; CRP; orthopedic surgery; periprosthetic joint infection; primary hip arthroplasty; revision surgery.

Figure 1

The postoperative CRP course in patients with and without an infection. (A) Comparing the absolute CRP course in patients with (red) and without (blue) an infection demonstrates a significant difference on days 11 and 14 (FDR day 11: q-value = 0.0037, FDR day 14: q-value = 0.0019). (B) Comparing the anterolateral (green) with the posterior (orchid) approach, no statistically significant differences regarding daily CRP can be detected. (C) Comparing traumatic and nontraumatic hip arthroplasty, traumatic have significantly higher CRP values on days −1 (FDR q-value ˂ 0.0001) and 1 (FDR q-value < 0.0001). (D) The relative CRP kinetics after a maximum CRP value follows a one-phase exponential decay and can be predicted in a sufficient manner (R² no infection: 0.716, R² with an infection: 0.827). *** p < 0.001, ** p < 0.01. * means multiplication.

Figure 2

ROC analysis of a single value and two formulas for the prediction of an infection. (A) The ROC analysis shows the different performance of three infection prediction models. (B) The single parameter “CRP max” is able to predict an infection with a sensitivity of 75% and a specificity of 56.86%, if the cut-off is set above 91.20 mg/L (AUC: 0.7028). (C) A binary logistic regression with a cut-off above −4.725 leads to a sensitivity and specificity of 75% and 80.03%, respectively (AUC: 0.8297). (D) A multinominal logistic regression consisting of the five most important parameters leads to the development of an equation with the ability to predict an infectious complication with a sensitivity of 87.5% and an accompanying specificity of 78.85%, if the cut-off is set to >−8.566 (AUC: 0.8757). The mentioned “best” values are marked in red.