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A prospective study was performed to establish criteria for the microbiological diagnosis of prosthetic joint infection at elective revision arthroplasty. Patients were treated in a multidisciplinary unit dedicated to the management and study of musculoskeletal infection. Standard multiple samples of periprosthetic tissue were obtained at surgery, Gram stained, and cultured by direct and enrichment methods. With reference to histology as the criterion standard, sensitivities, specificities, and likelihood ratios (LRs) were calculated by using different cutoffs for the diagnosis of infection. We performed revisions on 334 patients over a 17-month period, of whom 297 were evaluable. The remaining 37 were excluded because histology results were unavailable or could not be interpreted due to underlying inflammatory joint disease. There were 41 infections, with only 65% of all samples sent from infected patients being culture positive, suggesting low numbers of bacteria in the samples taken. The isolation of an indistinguishable microorganism from three or more independent specimens was highly predictive of infection (sensitivity, 65%; specificity, 99.6%; LR, 168.6), while Gram staining was less useful (sensitivity, 12%; specificity, 98%; LR, 10). A simple mathematical model was developed to predict the performance of the diagnostic test. We recommend that five or six specimens be sent, that the cutoff for a definite diagnosis of infection be three or more operative specimens that yield an indistinguishable organism, and that because of its low level of sensitivity, Gram staining should be abandoned as a diagnostic tool at elective revision arthroplasty.

Original publication




Journal article


Journal of clinical microbiology

Publication Date





2932 - 2939


Public Health Laboratory, Nuffield Orthopaedic Centre, Oxford, United Kingdom.


Humans, Bacteria, Bacterial Infections, Surgical Wound Infection, False Positive Reactions, Arthroplasty, Replacement, Hip, Arthroplasty, Replacement, Knee, Likelihood Functions, Sensitivity and Specificity, Follow-Up Studies, Prospective Studies, Models, Theoretical