Aim: This study was designed to answer the question whether a graphical representation increase the diagnostic value of automated leucocyte counting of the synovial fluid in the diagnosis of periprosthetic joint infections (PJI). Material and methods: Synovial aspirates from 322 patients (162 women, 160 men) with revisions of 192 total knee and 130 hip arthroplasties were analysed with microbiological cultivation, determination of cell counts and assay of the biomarker alpha-defensin (170 cases). In addition, microbiological and histological analysis of the periprosthetic tissue obtained during the revision surgery was carried out using the ICM classification and the histological classification of Morawietz and Krenn. The synovial aspirates were additionally analysed to produce dot plot representations (LMNE matrices) of the cells and particles in the aspirates using the hematology analyser ABX Pentra XL 80. Results: 112 patients (34.8%) had an infection according to the ICM criteria. When analysing the graphical LMNE matrices from synovia cell counting, four types could be differentiated: the type “wear particles” (I) in 28.3%, the type “infection” (II) in 24.8%, the “combined” type (III) in 15.5% and “indeterminate” type (IV) in 31.4%. There was a significant correlation between the graphical LMNE-types and the histological types of Morawietz and Krenn (p < 0.001 and Cramer test V value of 0.529). The addition of the LMNE-Matrix assessment increased the diagnostic value of the cell count and the cut-off value of the WBC count could be set lower by adding the LMNE-Matrix to the diagnostic procedure. Conclusion: The graphical representation of the cell count analysis of synovial aspirates is a new and helpful method for differentiating between real periprosthetic infections with an increased leukocyte count and false positive data resulting from wear particles. This new approach helps to increase the diagnostic value of cell count analysis in the diagnosis of PJI.

Aims: This study evaluates the value of a new graphic representation of cell count data of synovial fluid in the diagnosis of acute periprosthetic joint infection (PJI). Methods: A total of 75 patients with revisions of 48 primary total knee and 27 hip arthroplasties within the first six weeks after surgery were analyzed with cultivation of the synovial fluid and determination of its cell count as well as microbiological and histological analyses of the periprosthetic tissue obtained during the revision surgery using the ICM classification. The synovial fluid was additionally analyzed for graphic representation of the measured cells using LMNE-matrices. Results: A total of 38 patients (50.7%) had an infection. The following types of LMNE matrices could be differentiated: the indeterminate type (IV) in 14.7%, the infection type (II) in 5.3%, the hematoma type (V) in 33.3%, and the mixed type (VI; infection and hematoma) in 46.7%. Differentiation of LMNE types into infection (types II and VI) and non-infection (types IV and V) resulted in a sensitivity of 100%, a specificity of 97.3%, and a positive likelihood ratio of 37.0. The cell count measurement showed a sensitivity of 78.9%, a specificity of 89.2%, and a positive likelihood ratio of 7.3 at a cut-off of 10,000 cells. The percentage of polymorphonuclear leukocytes showed a sensitivity of 34.2%, a specificity of 100%, and a positive likelihood ratio of >200 at a cut-off of 90%. Conclusion: The graphic representation of the cell count analysis of synovial aspirates is a new and helpful method for differentiating between genuine early periprosthetic infections and postoperative hemarthrosis.

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.

The rising number of arthroplasties is combined with a rising number of periprosthetic joint infections, which leads to life-concerning consequences for the patients, including extended antibiotic treatment, further surgery and increased mortality. The heterogeneity of the symptoms and inflammatory response of the patients due to, e.g., age and comorbidities and the absence of a single diagnostic test with 100% accuracy make it very challenging to choose the right parameters to confirm or deny a periprosthetic joint infection and to establish a standardized definition. In recent years, additional diagnostic possibilities have emerged primarily through the increasing availability of new diagnostic methods, such as genetic techniques. The aim of the review is to provide an overview of the current state of knowledge about the various tests, including the latest developments. The combination of different tests increases the accuracy of the diagnosis. Each physician or clinical department must select the tests from the available methods that can be best implemented for them in organizational and technical terms. Serological parameters and the cultivation of the samples from aspiration or biopsy should be combined with additional synovial tests to create an accurate figure for the failure of the prosthesis, while imaging procedures are used to obtain additional information for the planned therapeutic procedure.

The Vancouver B3 type periprosthetic fracture is a rare but difficult-to-treat complication of hip arthroplasty. Various options for the treatment of Vancouver B3 periprosthetic fractures are described in the medical literature. The problem with many studies is the small number of cases, the fact that the results of Vancouver B2 and B3 fractures are only presented together, the lack of a clear definition of B3 fractures and the resulting subjective categorisation of fractures into the two groups (Vancouver B2 and B3). Therefore, the evidence in the literature for the recommendation of treatment strategies for Vancouver B3 fractures can be classified as poor. This review aims to analyse the various therapeutic options with regard to the current state of knowledge based on reports of case series.

Objectives: The aim of the study was to describe the graphical synovial cell distribution as LMNE matrix patterns in native knee aspirates and to explore their association with septic arthritis, crystal arthropathy, rheumatoid arthritis and haemarthrosis. Methods: In total, 117 patients with knee joint effusions of various origins underwent aspiration of the knee joint and the aspirate analysed using the Yumizen H500 automated cell counter. Microscopy of the aspirate was performed at the same time in cases with a cluster in the so-called noise field or previously unknown cell distribution. Results: The graphical type differentiation of automated synovial cell count analyses of native joints allowed 9 different types to be recognised: Type I as particle type, type II as infection type, type III as combination type of infection and particles, type IV as indifferent type, type V as haematoma type and type VI as combination type of infection and haematoma, type VII as particle type with haematoma, type VIII in rheumatoid arthritis and type IX as mixed type combining infection and rheumatoid arthritis. Differentiation of LMNE types into infection types (types II, III, VI and IX) and non-infection types (types I, IV, V, VII and VII) resulted in a sensitivity of 100%, a specificity of 93.9%, an accuracy of 96.6%, a positive predictive value (PPV) of 92.7%, a negative predictive value (NPV) of 100%, a positive likelihood ratio (LR+) of 16.5 and a negative likelihood ratio (LR−) of 0. Conclusions: Graphical LMNE matrix analysis of native knee aspirates identified reproducible patterns associated with septic arthritis, crystal arthropathy, rheumatoid arthritis, and haemarthrosis, which may be helpful in distinguishing these clinical entities, suggesting that graphical cell count interpretation may provide useful adjunctive information to the standard diagnostic work-up. The study is a preliminary descriptive study and requires validation using a larger number of patients.