Research project

Introduction of Hyaluronidase into routine prosthetic joint fluid processing to reduce sample viscosity and facilitate microscopic analysis

Programme
HSST
Specialty
Microbiology
Project published
25/05/2024

Introduction

According to UK SMI, diagnosis of prosthetic joint infection should include total/differential synovial fluid cell count. Viscous samples can impede the ability to perform cell count. On review of EBJIS guidelines (2021), hyaluronidase is suggested as a pre-treatment method to reduce viscosity of synovial fluid and increase the accuracy of optical microscopy.

Aims

The aim of this research was to develop a protocol utilising hyaluronidase, with 2 main objectives:

  1. Establish the efficacy of hyaluronidase in reducing viscosity and facilitating a cell count
  2. Establish the optimal conditions for sample treatment, including enzyme quantity, and incubation time

Methods and results

Samples were analysed before and after treatment with hyaluronidase, using increasing enzyme quantities to establish the optimal reaction conditions. Data were collected to determine the effect of treatment on macroscopic appearance, number of samples on which cell count could be performed, and the quantitative cell count. Optimal reduction in viscosity was achieved by the addition of 10μg hyaluronidase per 50μl of sample, incubated for 5 minutes. Under these conditions, in viscous samples, the percentage on which cell counts could be performed increased from 28% to 100%.

Conclusions

We have shown that the addition of hyaluronidase can improve the microscopic analysis of prosthetic joint fluid, by facilitating a cell count. Further work is required to improve the processing of blood-stained samples, for example, by addition of acetic acid. The final step is to streamline this into the diagnostic pathway.

Outputs

  • ePoster at ECCMID 2022 with results of local audit of compliance to EBJIS guidance
  • Poster at BIA Spring Meeting 2023 with preliminary results from pilot of hyaluronidase treatment

Last updated on 3rd December 2025