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The Bone & Joint Journal
Vol. 103-B, Issue 5 | Pages 923 - 930
1 May 2021
He R Wang Q Wang J Tang J Shen H Zhang X

Aims

As a proven and comprehensive molecular technique, metagenomic next-generation sequencing (mNGS) has shown its potential in the diagnosis of pathogens in patients with periprosthetic joint infection (PJI), using a single type of specimen. However, the optimal use of mNGS in the management of PJI has not been explored. In this study, we evaluated the diagnostic value of mNGS using three types of specimen with the aim of achieving a better choice of specimen for mNGS in these patients.

Methods

In this prospective study, 177 specimens were collected from 59 revision arthroplasties, including periprosthetic tissues, synovial fluid, and prosthetic sonicate fluid. Each specimen was divided into two, one for mNGS and one for culture. The criteria of the Musculoskeletal Infection Society were used to define PJI (40 cases) and aseptic failure (19 cases).


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.