α-defensin is a biomarker which has been described as having
a high degree of accuracy in the diagnosis of periprosthetic joint
infection (PJI). Current meta-analyses are based on the α-defensin
laboratory-based immunoassay rather than the quick on-table lateral
flow test kit. This study is the first meta-analysis to compare the
accuracy of the α-defensin laboratory-based immunoassay and the
lateral flow test kit for the diagnosis of PJI. A systematic review was performed according to the Preferred
Reporting Items for Systematic Reviews and Meta-Analyses guidelines.
Inclusion criteria were all clinical studies where the diagnosis
of PJI was uncertain. All studies selected used the Musculoskeletal
Infection Society (MSIS) or modified MSIS criteria. Two independent
reviewers reviewed the studies and extracted data. A meta-analysis
of results was carried out: pooled sensitivity, specificity, positive
and negative likelihood ratio, heterogeneity and areas under curves
are reported.Aims
Materials and Methods
Aims. The diagnosis of periprosthetic joint infection (PJI) remains
demanding due to limitations of all the available diagnostic tests.
The synovial fluid marker, α-defensin, is a promising adjunct for
the assessment of potential PJI. The purpose of this study was to
investigate the qualitative assessment of α-defensin, using Synovasure
to detect or exclude periprosthetic infection in total joint arthroplasty. Patients and Methods. We studied 50 patients (28 women, 22 men, mean age 65 years;
20 to 89) with a clinical indication for revision arthroplasty who
met the inclusion criteria of this prospective diagnostic study.
The presence of α-defensin was determined using the qualitative
Synovasure test and compared with standard diagnostic methods for
PJI. Based on modified Musculoskeletal Infection Society (MSIS)
criteria, 13 cases were categorised as septic and 36 as aseptic revisions.
One test was inconclusive. Results. The
Aims. The aim of this review was to evaluate the available literature
and to calculate the pooled sensitivity and specificity for the
different alpha-defensin test systems that may be used to diagnose
prosthetic joint infection (PJI). Materials and Methods. Studies using alpha-defensin or
Aims. The purpose of this current multicentre study is to analyse the
presence of alpha-defensin proteins in synovial fluid using the
Synovasure lateral flow device and to determine its diagnostic reliability
and accuracy compared with the prosthetic joint infection (PJI)
criteria produced by the Musculoskeletal Infection Society (MSIS). Patients and Methods. A cohort of 121 patients comprising 85 total knee arthroplasties
and 36 total hip arthroplasties was prospectively evaluated between
May 2015 and June 2016 in three different orthopaedic centres. The
tests were performed on patients with a chronically painful prosthesis
undergoing a joint aspiration in a diagnostic pathway or during revision
surgery. Results. Based on the MSIS criteria, 34 patients (28%) would have had
a PJI, and 87 patients had no PJI. Testing with the lateral flow
device had a sensitivity of 97.1% (95% confidence intervals (CI)
84.5 to 99.9) and a specificity of 96.6% (95% CI 90.3 to 99.2).
The positive predictive value was 91.7% (95% CI 77.7% to 98.3),
and the negative predictive value was 98.8% (95% CI 93.6 to 99.9).
Receiver operator characteristics analysis demonstrated an area
under the curve for the
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. 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.Aims
Methods
The aim of this study was to determine the diagnostic accuracy of α defensin (AD) lateral flow assay (LFA) and enzyme-linked immunosorbent assay (ELISA) tests for periprosthetic joint infection (PJI) in comparison to conventional synovial white blood cell (WBC) count and polymorphonuclear neutrophil percentage (PMN%) analysis. Patients undergoing joint aspiration for evaluation of pain after total knee arthroplasty (TKA) or total hip arthroplasty (THA) were considered for inclusion. Synovial fluids from 99 patients (25 THA and 74 TKA) were analyzed by WBC count and PMN% analysis, AD LFA, and AD ELISA. WBC and PMN% cutoffs of ≥ 1,700 cells/mm3 and ≥ 65% for TKA and ≥ 3,000 cells/mm3 and ≥ 80% for THA were used, respectively. A panel of three physicians, all with expertise in orthopaedic infections and who were blinded to the results of AD tests, independently reviewed patient data to diagnose subjects as with or without PJI. Consensus PJI classification was used as the reference standard to evaluate test performances. Results were compared using McNemar’s test and area under the receiver operating characteristic curve (AUC) analysis.Aims
Methods
The last decade has seen a considerable increase
in the use of in total ankle arthroplasty (TAA) to treat patients
with end-stage arthritis of the ankle. However, the longevity of
the implants is still far from that of total knee and hip arthroplasties. The aim of this review is to outline a diagnostic and treatment
algorithm for the painful TAA to be used when considering revision
surgery. Cite this article:
