| Summary: | Abstract Purpose The optimal timing of reimplantation of two-stage exchange arthroplasty for periprosthetic joint infection remains unknown. The purpose of the study was to (1) evaluate performance of combination of serum erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and frozen section in predicting persistent infection at the time of second-stage hip reimplantation and (2) compare accuracies of 5 and 10 polymorphonuclear neutrophils (PMNs) per high power field (HPF) as the threshold of frozen section. Methods We retrospectively reviewed 97 two-stage exchange hip arthroplasties from 2012–2016. Persistent infection at time of reimplantation was diagnosed using the Musculoskeletal Infection Society (MSIS) criteria. Two diagnostic models were developed. Model 1 utilized ESR, CRP, and > 5 PMNs/HPF on frozen section. Model 2 utilized ESR, CRP, and > 10 PMNs/HPF. Receiver operating characteristic (ROC) curves of the two models were generated, and areas under the curves (AUCs) were compared. A set of sensitivity analysis, using the Delphi-based consensus criteria for treatment success, was conducted to verify the accuracy of our models. Results The overall rate of infection at reimplantation was 14.4%. AUCs for models 1 and 2 were 0.709 (95% confidence interval [CI], 0.557–0.852) and 0.697 (95% CI, 0.529–0.847), respectively. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 57.1%, 88.0%, 44.4%, and 92.4%, respectively, in model 1 and 42.9%, 96.4%, 66.7%, and 90.9%, respectively, in model 2. Models 1 and 2 had no significant difference in predictive values (p = 0.821). Results remained robust in the sensitivity analysis. Conclusions This study reveals that the combination of serum ESR, CRP, and frozen section has limited diagnostic value in predicting persistent infection at reimplantation. Additionally, no significant difference in accuracies between 5 and 10 PMNs/HPF as the threshold of frozen section were found. There is a need for timely biomarkers with higher accuracy in diagnosing infection before reimplantation.
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