Optimized decision algorithm for the microbiological diagnosis of osteoarticular infections in adults using synovial fluid samples: a prospective study in two French hospitals including 423 samples of synovial fluid

J Bone Jt Infect. 2024 Feb 6;9(1):37-48. doi: 10.5194/jbji-9-37-2024. eCollection 2024.

Abstract

No consensus exists about the techniques to use for microbiological diagnosis of bone and joint infections (BJIs). The objective herein was to define an algorithm to optimize BJI diagnosis in adults using various bacteriological methods on synovial fluid samples. This prospective multi-center study included 423 synovial fluids collected from adult patients with suspected BJIs. Culture (using five solid media, an enrichment broth, and blood culture bottles), universal 16S rRNA PCR followed by Sanger sequencing, and seven specific bacterial PCRs were systematically performed. Combinations of methods were compared to arrive at the optimized algorithm. Among 423 synovial fluids, 242 infections were diagnosed (57.2 %): 213 mono- and 29 poly-microbial for a total of 284 bacteria (staphylococci at 54.6 %, streptococci-enterococci at 16.5 %, Gram-negative bacilli at 15.5 %, anaerobic species at 8.8 %). Comparing culture techniques, blood culture bottles had the highest sensitivity (67.6 % for pediatric and 63.9 % for anaerobic bottles) but are not sufficient alone and require being combined with solid media. The 16S rDNA PCR detected only 52.3 % of the bacteria, whereas specific PCRs had a higher sensitivity (Staphylococcus spp. at 66.2 %, S. aureus at 85.2 %, Streptococcus spp. at 91.2 %). Based on these results, an algorithm was proposed associating three solid media; inoculation into blood culture bottles; and 16S, Staphylococcus spp., and Streptococcus spp. PCRs, which would have detected 90.5 % of bacteria in the present cohort versus 79.2 % using all culture techniques on synovial fluid. This prospective study shows that a combination of culture and molecular methods on synovial fluids allows the optimization of bacterial detection.