BACKGROUND: The diagnosis of periprosthetic joint infection poses many challenges, one of which is the difficulty of isolating the infecting organism. Recently, a sophisticated modality (the Ibis Biosciences T5000 biosensor system) has been introduced that uses pan-domain primers in a series of polymerase chain reactions (PCRs) to identify and speciate essentially all bacteria and fungi as well as to identify key antibiotic resistance genes. We investigated the role of the Ibis in identifying infecting organisms in cases of known and suspected periprosthetic joint infection. METHODS: Synovial fluid specimens were collected prospectively from eighty-two patients undergoing eighty-seven arthroplasty procedures (sixty-five knee revisions, fifteen hip revisions, and seven primary knee arthroplasties) and were sent for both conventional culture and Ibis analysis. The surgeon's clinical determination of the cause for revision arthroplasty was failure due to infection in twenty-three cases and noninfectious failure in fifty-seven cases. RESULTS: In the twenty-three cases that were considered on clinical grounds to involve a periprosthetic joint infection, the Ibis detected the same pathogen isolated by conventional culture in seventeen of eighteen cases and also detected one or more organisms in four of the five culture-negative cases. In addition, the Ibis detected organisms in fifty (88%) of the fifty-seven cases in which revision arthroplasty was performed for a presumed noninfectious failure. CONCLUSIONS: The Ibis technology was not only effective at detecting organisms in cases of suspected periprosthetic joint infection in which cultures were negative, but it also suggested that many of the revision arthroplasty cases that have previously been considered to be purely aseptic may have a component of unrecognized, subclinical infection.
BACKGROUND: The diagnosis of periprosthetic joint infection poses many challenges, one of which is the difficulty of isolating the infecting organism. Recently, a sophisticated modality (the Ibis Biosciences T5000 biosensor system) has been introduced that uses pan-domain primers in a series of polymerase chain reactions (PCRs) to identify and speciate essentially all bacteria and fungi as well as to identify key antibiotic resistance genes. We investigated the role of the Ibis in identifying infecting organisms in cases of known and suspected periprosthetic joint infection. METHODS: Synovial fluid specimens were collected prospectively from eighty-two patients undergoing eighty-seven arthroplasty procedures (sixty-five knee revisions, fifteen hip revisions, and seven primary knee arthroplasties) and were sent for both conventional culture and Ibis analysis. The surgeon's clinical determination of the cause for revision arthroplasty was failure due to infection in twenty-three cases and noninfectious failure in fifty-seven cases. RESULTS: In the twenty-three cases that were considered on clinical grounds to involve a periprosthetic joint infection, the Ibis detected the same pathogen isolated by conventional culture in seventeen of eighteen cases and also detected one or more organisms in four of the five culture-negative cases. In addition, the Ibis detected organisms in fifty (88%) of the fifty-seven cases in which revision arthroplasty was performed for a presumed noninfectious failure. CONCLUSIONS: The Ibis technology was not only effective at detecting organisms in cases of suspected periprosthetic joint infection in which cultures were negative, but it also suggested that many of the revision arthroplasty cases that have previously been considered to be purely aseptic may have a component of unrecognized, subclinical infection.
Authors: Sana S Dastgheyb; Sommer Hammoud; Constantinos Ketonis; Andrew Yongkun Liu; Keith Fitzgerald; Javad Parvizi; James Purtill; Michael Ciccotti; Irving M Shapiro; Michael Otto; Noreen J Hickok Journal: Antimicrob Agents Chemother Date: 2015-01-26 Impact factor: 5.191
Authors: Kerryl E Greenwood-Quaintance; James R Uhl; Arlen D Hanssen; Rangarajan Sampath; Jayawant N Mandrekar; Robin Patel Journal: J Clin Microbiol Date: 2013-11-27 Impact factor: 5.948
Authors: Dante P Melendez; James R Uhl; Kerryl E Greenwood-Quaintance; Arlen D Hanssen; Rangarajan Sampath; Robin Patel Journal: J Clin Microbiol Date: 2014-04-09 Impact factor: 5.948
Authors: Matthew C Swearingen; Alex C DiBartola; Devendra Dusane; Jeffrey Granger; Paul Stoodley Journal: Pathog Dis Date: 2016-08-21 Impact factor: 3.166