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The Bone & Joint Journal
Vol. 103-B, Issue 1 | Pages 32 - 38
1 Jan 2021
Li R Li X Ni M Fu J Xu C Chai W Chen J

Aims. The aim of this study was to further evaluate the accuracy of ten promising synovial biomarkers (bactericidal/permeability-increasing protein (BPI), lactoferrin (LTF), neutrophil gelatinase-associated lipocalin (NGAL), neutrophil elastase 2 (ELA-2), α-defensin, cathelicidin LL-37 (LL-37), human β-defensin (HBD-2), human β-defensin 3 (HBD-3), D-dimer, and procalcitonin (PCT)) for the diagnosis of periprosthetic joint infection (PJI), and to investigate whether inflammatory joint disease (IJD) activity affects their concentration in synovial fluid. Methods. We included 50 synovial fluid samples from patients with (n = 25) and without (n = 25) confirmed PJI from an institutional tissue bank collected between May 2015 and December 2016. We also included 22 synovial fluid samples aspirated from patients with active IJD presenting to Department of Rheumatology, the first Medical Centre, Chinese PLA General Hospital. Concentrations of the ten candidate biomarkers were measured in the synovial fluid samples using standard enzyme-linked immunosorbent assays (ELISA). The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves. Results. BPI, LTF, NGAL, ELA-2, and α-defensin were well-performing biomarkers for detecting PJI, with areas under the curve (AUCs) of 1.000 (95% confidence interval, 1.000 to 1.000), 1.000 (1.000 to 1.000), 1.000 (1.000 to 1.000), 1.000 (1.000 to 1.000), and 0.998 (0.994 to 1.000), respectively. The other markers (LL-37, HBD-2, D-dimer, PCT, and HBD-3) had limited diagnostic value. For the five well-performing biomarkers, elevated concentrations were observed in patients with active IJD. The original best thresholds determined by the Youden index, which discriminated PJI cases from non-PJI cases could not discriminate PJI cases from active IJD cases, while elevated thresholds resulted in good performance. Conclusion. BPI, LTF, NGAL, ELA-2, and α-defensin demonstrated excellent performance for diagnosing PJI. However, all five markers showed elevated concentrations in patients with IJD activity. For patients with IJD, elevated thresholds should be considered to accurately diagnose PJI. Cite this article: Bone Joint J 2021;103-B(1):32–38


The Bone & Joint Journal
Vol. 103-B, Issue 1 | Pages 46 - 55
1 Jan 2021
Grzelecki D Walczak P Szostek M Grajek A Rak S Kowalczewski J

Aims

Calprotectin (CLP) is produced in neutrophils and monocytes and released into body fluids as a result of inflammation or infection. The aim of this study was to evaluate the utility of blood and synovial CLP in the diagnosis of chronic periprosthetic joint infection (PJI).

Methods

Blood and synovial fluid samples were collected prospectively from 195 patients undergoing primary or revision hip and knee arthroplasty. Patients were divided into five groups: 1) primary total hip and knee arthroplasty performed due to idiopathic osteoarthritis (OA; n = 60); 2) revision hip and knee arthroplasty performed due to aseptic failure of the implant (AR-TJR; n = 40); 3) patients with a confirmed diagnosis of chronic PJI awaiting surgery (n = 45); 4) patients who have finished the first stage of the PJI treatment with the use of cemented spacer and were qualified for replantation procedure (SR-TJR; n = 25), and 5) patients with rheumatoid arthritis undergoing primary total hip and knee arthroplasty (RA; n = 25). CLP concentrations were measured quantitatively in the blood and synovial fluid using an immunoturbidimetric assay. Additionally, blood and synovial CRP, blood interleukin-6 (IL-6), and ESR were measured, and a leucocyte esterase (LE) strip test was performed.


The Journal of Bone & Joint Surgery British Volume
Vol. 88-B, Issue 3 | Pages 366 - 373
1 Mar 2006
Baumann C Rat AC Osnowycz G Mainard D Delagoutte JP Cuny C Guillemin F

We conducted a multicentre cohort study of 228 patients with osteoarthritis followed up after total hip or knee replacement. Quality of life and patient satisfaction were assessed by self-administered questionnaires. Patient satisfaction was the dependent variable in a multivariate linear regression model. Independent variables included sociodemographic factors, pre- and post-operative clinical characteristics and the pre-operative and post-discharge health-related quality of life.

The mean age of the patients was 69 years (sd 9), and 43.8% were male. Pre- and postoperative clinical characteristics were not associated with satisfaction with health care. Only pre-operative bodily pain (p < 0.01) and pre-operative social functioning (p < 0.05) influenced patient satisfaction with care.

The pre-operative health-related quality of life and patient characteristics have little effect on inpatient satisfaction with care. This suggests that the impact of the care process on satisfaction may be independent of observed and perceived initial patient-related characteristics.