Research culture methods detect more anaerobes compared to conventional clinical workflows in periprosthetic joint infection: a pilot study of 14 cases

INTRODUCTION: Periprosthetic joint infection (PJI) remains one of the most challenging complications of total joint arthroplasty, often complicated by limitations in diagnostic sensitivity. Standard clinical culture methods fail to identify pathogens in 20%-50% of cases, leading to potential under- or overtreatment. This pilot study aimed to compare the microbial detection capabilities of standard clinical culture methods with enhanced research laboratory techniques, and to explore whether additional microbial findings might have the potential to influence antibiotic treatment planning. MATERIALS AND METHODS: Thirteen patients undergoing surgery for PJI, as defined by the 2018 International Consensus Meeting (ICM) on Infection criteria, were prospectively enrolled at a single academic medical center between August 2023 and September 2024. Intraoperative synovial fluid, periprosthetic tissue, and implant swabs were collected and processed using both standard clinical workflows and optimized research protocols. Culture results and treatment decisions were reviewed in collaboration with Infectious Disease specialists. RESULTS: Both methods identified primary organisms. However, research techniques detected additional organisms not captured by clinical cultures (p = 0.013). Despite these differences, overall detection rates were comparable (57.1% vs. 59.5%; p = 0.963), with the research workflow achieving similar yield with fewer samples. The potential impact of additional isolate identification on antibiotic selection, if deemed clinically significant, did not appear to result in meaningful changes to antibiotic regimens, although this may have been influenced by the empiric use broad-spectrum antibiotics. CONCLUSIONS: Clinical culture methods may not detect all organisms in PJI, highlighting possible limitations in current diagnostic approaches. Although this pilot study did not directly assess the impact of enhanced microbial detection on antibiotic prescribing and treatment decisions were largely unchanged, these findings suggest that a more comprehensive microbial detection could potentially inform antibiotic selection and warrants further investigation.