MICROBIOLOGICAL PATTERNS IN PERIPROSTHETIC JOINT INFECTIONS: SUBGROUPS OF MONOMICROBIAL AND POLYMICROBIAL INFECTIONS

Aim Current literature only divides monomicrobial and polymicrobial periprosthetic joint infections (PJI), although the definition of polymicrobial infections appears inconsistent. We aimed to analyse microbiological and clinical results in PJIs and propose a classification based on different microbiological patterns, which is currently lacking in the literature. Methods We retrospectively analysed 1725 culture-positive hip and knee revision arthroplasties performed at a single institution between 2008 and 2024. Only European Bone and Joint Infection Society (EBJIS) infection-confirmed revisions were included. Infections were classified into microbiological patterns based on the number of positive samples and the number of isolated microorganisms. The infections were separated into single positive (only one microorganism in one single sample), monomicrobial (one microorganism in two separate samples), monomicrobial plus (one microorganism in ≥2 samples and an additional microorganism in only one sample), multipositive (≥2 microorganisms isolated from ≥ one sample), polymicrobial (≥2 microorganisms in ≥2 separate samples) and polymicrobial plus (≥2 microorganisms identified in ≥2 samples with additional pathogens found in only a single sample). Microorganisms have been further classified into high (HV) and low virulent (LV) pathogens. Clinical outcomes were determined using the Tier classification by the Musculoskeletal Infection Society. Results Of 1725 culture-positive infections, 1015 PJIs were included. Monomicrobial infections were the most common (603, 59.4%), followed by single-positive PJIs (188, 18.5%). Multipositive infections accounted for 79 cases (7.8%) and monomicrobial plus for 78 (7.7%). Polymicrobial infections occurred in 49 (4.8%) cases and polymicrobial plus in 18 (1.8%) cases. Distinct differences in the prevalence of microorganisms across microbial groups were observed. LV microorganisms were mainly found in multipositive infections (83.5%), single-positive infections (77.1%) and monomicrobial plus (79%), whereas monomicrobial, polymicrobial and polymicrobial-plus infections showed a higher prevalence of HV microorganisms (p < 0.001). When comparing the clinical outcome of different microbiological groups, a significant difference was shown. Polymicrobial infections had the worst outcome (40.8%), whereas multipositive infections had the highest success rate (65.8%), indicating the difficulty in treating polymicrobial infections and the problems with the actual interpretation of only-one-sample isolates. Conclusion PJIs demonstrated distinct microbiological patterns with significant differences in clinical outcomes and variability in LV and HV microorganisms. Polymicrobial infections are a particularly challenging subgroup with poor outcomes, while clinical interpretation of isolates that appear only in one sample remains challenging, especially in the context of infections with other isolates and LV organisms. With this approach, PJIs can be classified more easily into clinically relevant subgroups.