Advertisement for orthosearch.org.uk
Results 1 - 2 of 2
Results per page:
The Bone & Joint Journal
Vol. 103-B, Issue 1 | Pages 26 - 31
4 Jan 2021
Kildow BJ Ryan SP Danilkowicz R Lazarides AL Penrose C Bolognesi MP Jiranek W Seyler TM

Aims

Use of molecular sequencing methods in periprosthetic joint infection (PJI) diagnosis and organism identification have gained popularity. Next-generation sequencing (NGS) is a potentially powerful tool that is now commercially available. The purpose of this study was to compare the diagnostic accuracy of NGS, polymerase chain reaction (PCR), conventional culture, the Musculoskeletal Infection Society (MSIS) criteria, and the recently proposed criteria by Parvizi et al in the diagnosis of PJI.

Methods

In this retrospective study, aspirates or tissue samples were collected in 30 revision and 86 primary arthroplasties for routine diagnostic investigation for PJI and sent to the laboratory for NGS and PCR. Concordance along with statistical differences between diagnostic studies were calculated.


The Bone & Joint Journal
Vol. 102-B, Issue 4 | Pages 463 - 469
1 Apr 2020
Qin L Hu N Li X Chen Y Wang J Huang W

Aims

Prosthetic joint infection (PJI) remains a major clinical challenge. Neutrophil CD64 index, Fc-gamma receptor 1 (FcγR1), plays an important role in mediating inflammation of bacterial infections and therefore could be a valuable biomarker for PJI. The aim of this study is to compare the neutrophil CD64 index in synovial and blood diagnostic ability with the standard clinical tests for discrimination PJI and aseptic implant failure.

Methods

A total of 50 patients undergoing revision hip and knee arthroplasty were enrolled into a prospective study. According to Musculoskeletal Infection Society (MSIS) criteria, 25 patients were classified as infected and 25 as not infected. In all patients, neutrophil CD64 index and percentage of polymorphonuclear neutrophils (PMN%) in synovial fluid, serum CRP, ESR, and serum CD64 index levels were measured preoperatively. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were analyzed for each biomarker.