Histological score for degrees of severity in an implant-associated infection model in mice.

Arch Orthop Trauma Surg

Department for Trauma- and Hand Surgery, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany.

Published: September 2019

Introduction: Several scores were introduced to diagnose and to classify osteomyelitis in practice. Mouse models are often used to study the pathophysiology of bone infection and to test therapeutic strategies. Aim of the present study was to design a score to diagnose and quantify implant-associated infection in a murine experimental model.

Materials And Methods: Four independent parameters were developed: existence of callus, consolidation of the fracture, structural changes of the medullary cavity and number of bacteria. The score was assessed in a standardized implant-associated mouse model with 35 BALB/c-mice. The left femur was osteotomized, fixed by a titanium locking plate and infection was induced by inoculation of Staphylococcus aureus into the fracture gap. For the sham group, the procedure was performed without inoculation of bacteria. The score was assessed on days 7, 14 and 28. Each item of the score showed lower values for the infection group compared to the controls after 4 weeks.

Results: Regardless of the assessed time point, the overall total score was significantly higher in the control group compared to the infection group (p < 0.0001). Analysis revealed a sensitivity of 0.85, specificity of 1.0, negative predictive value of 0.67 and positive predictive value of 1.0.

Conclusion: The proposed score assessing severity of fracture-related infection in an implant-associated murine model was easy to access, feasible to diagnose and estimate bone healing and infection in a murine bone infection with a high sensitivity. Therefore, this score might be a useful tool to quantify infection-related changes after fracture in further future preclinical studies.

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Source
http://dx.doi.org/10.1007/s00402-019-03188-6DOI Listing

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