Analysis of postoperative and hematogenous prosthetic joint-infection microbiological patterns in a large cohort. Issue 4 (April 2018) - Zeller, Valérie; Kerroumi, Younes; Meyssonnier, Vanina; Heym, Beate; Metten, Marie-Astrid; Desplaces, Nicole; Marmor, Simon
Highlights: Specific microbiological patterns were identified according to PJI classification. Analysis of PJI classification can help to choose initial antibiotic therapy. Major microorganisms isolated in hematogenous PJIs were streptococci and staphylococci. Among streptococci, Streptococcus agalactiae (group B) was the most frequent. Abstract: Objectives: This study was undertaken to analyze prosthetic joint infection (PJI)-causing microorganisms and compare their distribution patterns according to PJI classification. Methods: Cohort study from a single referral center for bone-and-joint infections from January 2004 to December 2015. Results: Nine hundred and twenty-six patients, who developed 997 PJIs, involving the hip (62%), knee (35%) and/or shoulder (1%), were included. PJIs were classified as early postoperative (19%), late chronic (30%), hematogenous (35%) and undetermined (16%). Pathogens most frequently isolated from early-postoperative PJIs were staphylococci (57%), with 25% each Staphylococcus aureus or Staphylococcus epidermidis ; 21% were polymicrobial and 10% Gram-negative rods. For late-chronic PJIs, the most frequent microbes were staphylococci (61%), predominantly S. epidermidis (35%); anaerobic bacteria were isolated from 15%; 11% were polymicrobial. Hematogenous PJIs were 99% monomicrobial. Although S. aureus was the most frequently isolated species (28%), streptococci were isolated slightly more often than staphylococci (39% vs. 36%). Among streptococci, group B streptococci were the most frequent (15%). The portal of entry was identified for 52% of hematogenous PJIs: 15% cutaneous, 11% dental, 9% gastrointestinal, 6% urinary, and 11% miscellaneous. Conclusion: Although a wide variety of microorganisms was isolated from PJIs, specific microbiological patterns were observed according to infection classification.