# Additional Erythrocyte Field Is Helpful for Graphic Type Differentiation of Cell Count Determination Between Acute Periprosthetic Joint Infection and Hematoma

## TL;DR

A new method using cell count analysis with an erythrocyte field helps distinguish between joint infections and hematomas after surgery.

## Contribution

The study introduces a new erythrocyte field in cell count analysis to improve differentiation between acute joint infection and hematoma.

## Key findings

- The LMNE graphical type differentiation achieved 98.7% accuracy in diagnosing acute periprosthetic joint infection.
- The erythrocyte field helped identify hematoma cases with a peak in the erythrocyte field (type V).
- Only one non-infectious hematoma was misclassified, showing high diagnostic reliability.

## Abstract

Background/Objectives: This study was designed to verify the hypothesis that graphical cell differentiation of synovial cell count analysis is helpful for diagnosis of acute periprosthetic joint infection (PJI) and that the additional erythrocyte field has advantages to differentiate PJI from hematoma. Methods: A total of 77 total knee arthroplasties and 31 total hip arthroplasties underwent aspiration within six weeks of primary implantation. The aspirate was analyzed with the cell counter Yumizen H500 and examined by cultivation. Serum CRP was also determined. A total of 43 patients underwent revision and microbiological and histological analysis of the periprosthetic tissue, according to Morowitz and Krenn, was performed. The ICM criteria for diagnosing PJI were used. Results: Thirty-two cases (29.6%) were classified as acute infection. The graphical type differentiation LMNE (leukocyte–monocyte–neutrophil–eosinophil) showed 28 cases with type II (infection type), 63 cases with type IV (indifferent type), 13 cases with type V (hematoma type with a peak in the erythrocyte field) and 4 cases with type VI (mixed infection and hematoma). The LMNE matrix assessment had an accuracy of 98.7%, sensitivity of 96.9%, specificity of 98.7%, positive predictive value of 96.9%, negative predictive value of 98.7%, a positive likelihood ratio of 73.62, and a negative likelihood ratio of 0.03. Only one single non-infectious hematoma sample was misclassified as type VI (mixed infection/hematoma). Conclusions: The graphical type differentiation of the cell count analysis of synovial aspirates is a helpful method for diagnosis of acute periprosthetic joint infection and differentiating between hematoma and real early periprosthetic infections. This report shows that the new erythrocyte field of the Yumizen H500 is a useful additional diagnostic tool.