BMC Musculoskeletal Disorders (Dec 2019)
Sonication of retrieved implants improves sensitivity in the diagnosis of periprosthetic joint infection
Abstract
Abstract Background Sonication is a valuable tool in the diagnosis of periprosthetic joint infections (PJI). However, conditions and definition criteria for PJI vary among studies. The aim of this study was to determine the diagnostic performance (i.e., specificity, sensitivity) of sonicate fluid culture (SFC) against periprosthetic tissue culture (PTC), when using European Bone and Joint Infection Society (EBJIS) criteria. Methods From March 2017 to April 2018, 257 implants were submitted for sonication. PJI was defined according to the EBJIS criteria as well as according to the International Consensus Meeting criteria of 2018 (ICM 2018). Only cases with at least one corresponding tissue sample were included. Samples were cultured using traditional microbiological plating techniques. Sensitivity and specificity were determined using two-by-two contingency tables. McNemar’s test was used to compare proportions among paired samples. Subgroup analysis was performed dividing the cohort according to the site of PJI, previous antibiotic treatment, and time of manifestation. Prevalence of pathogens was determined for all patients as well as for specific subgroups. Results Among the 257 cases, 145 and 112 were defined as PJI and aseptic failure, respectively. When using the EBJIS criteria, the sensitivity of SFC and PTC was 69.0 and 62.8%, respectively (p = .04). Meanwhile, the specificity was 90.2 and 92.9%, respectively (p = .65). When adopting ICM 2018 criteria, the sensitivity of SFC and PTC was 87.5 and 84.4% (p = .63) respectively, while the specificity was 85.1 and 92.5% (p = .05), respectively. The most commonly identified pathogens were coagulase-negative staphylococci (26% overall), while 31% of PJI were culture-negative and 9% polymicrobial. Conclusions SFC exhibited significantly greater sensitivity versus PTC when using the EBJIS criteria. Nevertheless, the diagnosis of PJI remains a difficult challenge and different diagnostic tools are necessary to optimize the outcome.
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