Aims. The diagnosis of periprosthetic joint infection (PJI) continues to present a significant clinical challenge. New biomarkers have been proposed to support clinical decision-making; among them, synovial fluid alpha-defensin has gained interest. Current research methodology suggests reference methods are needed to establish solid evidence for use of the test. This prospective study aims to evaluate the diagnostic accuracy of high-performance liquid chromatography coupled with the mass spectrometry (LC-MS) method to detect alpha-defensin in synovial fluid. Methods. Between October 2017 and September 2019, we collected synovial fluid samples from patients scheduled to undergo revision surgery for painful total knee arthroplasty (TKA). The International Consensus Meeting criteria were used to classify 33 PJIs and 92 aseptic joints. LC-MS assay was performed to measure alpha-defensin in synovial fluid of all included patients. Sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristic curve (AUC) were calculated to define the test diagnostic accuracy. Results. The AUC was 0.99 (95% confidence interval (CI) 0.98 to 1.00). Receiver operating characteristic (ROC) analysis showed that the optimal cut-off value of synovial fluid alpha-defensin was 1.0 μg/l. The sensitivity of alpha-defensin was 100% (95% CI 96 to 100), the specificity was 97% (95% CI 90 to 98), the positive predictive value was 89.2% (95% CI 82 to 94), and negative predictive value was 100% (95% CI 96 to 100). ROC analysis demonstrated an AUC of 0.99 (95% CI 0.98 to 1.0). Conclusion. The present study confirms the utility of alpha-defensin in the synovial fluid in patients with painful TKA to select cases of PJI. Since LC-MS is still a time-consuming technology and is available in highly specialized laboratories, further translational research studies are needed to take this evidence into routine procedures and promote a new diagnostic approach. Cite this article: Bone Joint J 2022;104-B(9):1047–1051

Aims

With up to 40% of patients having patellofemoral joint osteoarthritis (PFJ OA), the two arthroplasty options are to replace solely the patellofemoral joint via patellofemoral arthroplasty (PFA), or the entire knee via total knee arthroplasty (TKA). The aim of this study was to assess postoperative success of second-generation PFAs compared to TKAs for patients treated for PFJ OA using patient-reported outcome measures (PROMs) and domains deemed important by patients following a patient and public involvement meeting.

Introduction. In 2015, the healthcare system transitioned from International Classification of Diseases, Ninth Revision (ICD-9) coding to the Tenth Revision (ICD-10). Given that administrative claims are used for quality initiatives, risk adjustment models and clinical research, we sought to determine the effect of new, more detailed coding on the incidence of complications following primary total knee arthroplasty (TKA). Methods. The Humana administrative claims database was queried from 2-years prior to October 1, 2015 (ICD-9 cohort) and for 1-year after this date (ICD-10 cohort) to identify all primary TKA procedures. Each TKA was then tracked for occurrence of an arthroplasty specific post-operative complication within 6 months of surgery using the respective coding systems. Laterality and joint specific codes were utilized for the ICD-10 cohort to ensure complications occurred on the same side and joint as the index procedure. Incidence of each complication was compared between cohorts using risk ratios (RR) and 95% confidence intervals. Results. There were 19,009 TKAs in the ICD-10 cohort and 38,172 TKAs in the ICD-9 cohort. The incidence of each post-operative complication analyzed was significantly higher in the ICD-9 cohort relative to the ICD-10 cohort (Figure 1). Comparing ICD-9 cohort to ICD-10 cohort, PJI occurred in 1.9% vs 1.3% (RR 1.5), loosening in 0.3% vs 0.1% (RR 2.7), periprosthetic fracture in 0.3% vs 0.1% (RR 3.0) and other mechanical complications in 0.7% vs 0.4% (RR 2.0), respectively (p < 0.05 for all). These findings remained significant when subgroup analyses were performed to control for seasonal variation between groups. Conclusion. The transition from ICD-9 to ICD-10 coding has dramatically altered the reported incidence of complications following TKA. These results are likely due to the added complexity of ICD-10 which is joint and laterality specific. It is important to quantify and understand the differences between coding systems as this data is used for quality initiatives, risk adjustment models and clinical research. Thoughtful methodology will be necessary for future research if both ICD-9 and ICD-10 data are being analyzed simultaneously. Furthermore, additional studies are needed to compare the hospital billing data for complex diagnoses or revision procedures to coding performed by skilled researchers in the field. For figures, tables, or references, please contact authors directly