¹Klinik und Poliklinik für Orthopädie und Unfallchirurgie, Universitätsklinikum Bonn, Bonn, Deutschland
²University of St Andrews School of Medicine, St. Andrews, UK

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Objectives and questions: Bacterial antibiotic resistance is a key challenge and constant battle in modern medicine. Current methods to identify infective microbes and define antibiotic susceptibilities are culture based and thus require two to ten days. This prolonged diagnostic delays targeted treatment and potentially impacts patient outcome. In this exploratory prospective study, we strived to establish a faster sensitive method to characterize antibiotic activity against bacterial growth in patient material, using a Scattered Light Integrated Collector (SLIC).

Material and methods: SLIC detects refraction of light beamed through a particulate-containing solution. Bacteria in solution refract light and can be recorded in real-time with yet unmatched sensitivity (10² CFU/mL). As recently published, SLIC can monitor growth of bacteria isolated from patient material and its inhibition by antibiotics. We tailored antibiotic panels to determine the class of infective microbe and clinically relevant susceptibilities. In this follow-up study, we optimized our method for direct use of primary peri-operative synovial fluid and tissue from periprosthetic joint infection (PJI) patients. We implemented enzymatic and chemical treatments of these complex primary samples to reduce time to positivity for detection of microbial growth, without affecting the activity of our selected antibiotics. Finally, we tested our antibiotic panels (that cover most clinically used classes, allow MRSA- and MRGN-classification and classification of the virulent microbe) against PJI primary samples.

Results: As we have published, SLIC can accurately and reproducibly measure dose-dependent inhibitory or bacteriolytic antibiotic effects and thus provide an antibiotic susceptibility profile of an isolated and pre-cultured bacterium within 90 minutes. In the current follow-up study, we were able to transfer our findings to primary samples. We show that SLIC can reliably differentiate infected from uninfected samples within a few hours, allowing real-time detection of an infection without the need for prior microbial isolation and culture. Time to positivity could be further reduced by enzymatic and chemical pre-treatment. Strikingly, we could monitor antibiotic activity reliably and accurately in both infected joint fluid and periprosthetic tissue, rapidly providing antibiogram-like data.

Discussion and conclusions: This new approach could accelerate diagnostic procedures by avoiding the need for isolation and culture of the infecting microbe. The battle against multi-resistant bacteria calls for faster reliable means of diagnosis to reduce untargeted empirical antibiosis and thus improve patient outcome. Our SLIC-based method presents a strong option to target both of these aspects, delivering reliable antibiotic susceptibility statements in far shorter time than current microbiology standards.