Accuracy of Serological Markers, Synovial Fluid, Microbiological Culture, and Histopathological Examination for Diagnosing Periprosthetic Knee Infection

Abstract

Objective This study assessed the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of serological tests, synovial fluid markers, microbiological tissue culture, and histopathological examination of the periprosthetic membrane in diagnosing periprosthetic knee infection.

Methods This study is prospective, and it includes patients undergoing total knee arthroplasty revision surgery from November 2019 to December 2021. The analysis consisted of serological tests (erythrocyte sedimentation rate [ESR], C-reactive protein [CRP], and D-dimer), synovial fluid markers (leukocyte and polymorphonuclear cell counts), periprosthetic tissue culture, and histopathological examination of the periprosthetic membrane of all patients.

Results Sixty-two patients had periprosthetic joint infection (PJI) according to the 2018 International Consensus Meeting criteria (infection group), while 22 subjects had no infection. ESR sensitivity and specificity were 83.6% and 45.4%, respectively. CRP sensitivity and specificity were 64.5% and 100%, whereas D-dimer sensitivity and specificity were 78.9% and 25%, respectively. Leukocyte count sensitivity and specificity were 75.6% and 100%, polymorphonuclear cell count sensitivity and specificity were 33% and 100%, respectively. Periprosthetic tissue culture sensitivity and specificity culture were, respectively, 77.4% and 100%. Histopathological examination sensitivity and specificity were 43.7% and 100%, respectively.

Conclusions In our study, the total blood cell count in synovial fluid and microbiological cultures of periprosthetic tissues were the most accurate tests for PJI diagnosis. In contrast, polymorphonuclear cell percentage was the least accurate test for PJI diagnosis.

Keywords

arthroplasty, replacement, knee - postoperative complications - periprosthetic infection - biomarkers

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