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BMC Infect Dis ; 22(1): 790, 2022 Oct 17.
Artículo en Inglés | MEDLINE | ID: mdl-36253761

RESUMEN

BACKGROUND: In microbiological diagnosis of periprosthetic joint infection (PJI) there is no consensus regarding the most suitable and optimal number of specimens to be cultured or the most effective technique of tissue processing. This comparative study analysed the accuracy of two semi-automated homogenization methods with special focus on the volume and exact origin of each sample. METHODS: We investigated a total of 722 periprosthetic tissue samples. PJI was defined according to the new scoring system for preoperative and intraoperative criteria. We compared the performance of our routinely used single tissue processing by disposable high-frequency disperser with the bead milling method. RESULTS: Eighty patients were included. Among forty classified PJIs, 34 patients yielded positive culture results. In 23 cases (68%) exact concordant results were generated with both techniques. However, in seven cases (20%) processing by the disperser and in four cases (12%) by bead milling provided additional positive samples, but without significant difference since the major definition criteria were met in all cases. The percentage of positive results was influenced by the volume and origin of the tissue samples. Results for small tissue samples tended to be better using the bead milling method. This might lead to improved preoperative arthroscopic diagnosis, as the volume of biopsies is generally limited. Six patients had negative results due to previous antimicrobial therapy. Forty other patients were classified as aseptic failures. Neither procedure resulted in any contamination. CONCLUSION: Both methods enable reliable processing of tissue samples for diagnosis of PJI and are suitable for routine use.


Asunto(s)
Artritis Infecciosa , Artroplastia de Reemplazo de Cadera , Infecciones Relacionadas con Prótesis , Artritis Infecciosa/microbiología , Biopsia , Humanos , Infecciones Relacionadas con Prótesis/microbiología , Sensibilidad y Especificidad
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