Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
Klim, S.
Novel Biomarkers in Joint Infection Diagnosis
Doktoratsstudium der Medizinischen Wissenschaft; Humanmedizin; [ Dissertation ] Medizinische Universität Graz; 2022. pp. 89
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- Autor*innen der Med Uni Graz:
- Betreuer*innen:
- Glehr Mathias
- Stradner Martin Helmut
- Altmetrics:
- Abstract:
- IntroductionThe rapid and accurate diagnosis of septic arthritis (SA) and periprosthetic joint infection (PJI) is of central importance for the therapeutic outcome of these diseases. The use of biomarkers has brought significant advances in diagnosis, but current biomarkers do not have the diagnostic power to be used as the sole decision criterion. Therefore, the aim of this dissertation and the underlying study is to investigate the properties of nuclear magnetic resonance (NMR) metabolomics, soluble urokinase plasminogen activator receptor (suPAR) as potential new biomarkers, and the combination of different biomarkers in a multi-biomarker model in the diagnosis of SA and PJI. Methods All patients with a clinical suspicion of PJI or SA who underwent a diagnostic arthrocentesis at our institution within a 32-month period were prospectively evaluated for study enrolment. Group assignment (septic vs. aseptic) was performed according to the EBJIS criteria (PJI) and modified Newman criteria (SA). After synovial fluid and blood plasma collection, the samples were stored at -80°C. SuPAR levels were determined using a commercially available sandwich immunoassay (suPARnostic®, ViroGates A/S, Denmark). The NMR experiments were performed at 310 K on an AVANCE™ NeoBruker Ultrashield 600 MHz spectrometer. Bruker Topspin version 4.0.2 was used for NMR data acquisition. In total, 37 metabolites were analysed using a volume of 200 µl per synovial sample. The multi-biomarker model was calculated on a dataset including 124 knee or hip revision arthroplasty procedures. Logistic regression was used for the biomarkers and all their ratios. After a cross-validation using a training sample set (75% of all samples) for best performance estimates, we evaluated the final model on a separate set (25%). Results In total, 182 cases were included. Diagnostic properties were determined separately for SA and PJI cases. Plasma suPAR (AUC 0.74 in SA and 0.40 in PJI cases) and synovial suPAR (AUC 0.87 for SA and 0.76 for PJI cases) could not outperform serum CRP (AUC 0.81 in SA and 0.79) in PJI cases. NMR has shown the best diagnostic results when metabolite ratios were calculated: Isobutyric acid/Methionine (AUC 0.9462) in SA and Glucose/Glycogen (AUC 0.9073) in PJI. The best single metabolites were Mannose (AUC 0.8558) in SA and Taurine (AUC 0.8558) in PJI. The final multi-biomarker model for PJI included Fibrinogen, CRP, the ratio of Fibrinogen to CRP, and the ratio of serum Thrombocytes to CRP (AUC 0.92, accuracy 0.77, specificity 0.92, sensitivity 0.68). Conclusion The investigation of new biomarkers in the diagnosis of joint infections yielded both positive and negative results. Results indicate that NMR metabolome analysis is a promising method for diagnosing both septic arthritis and PJI. This analysis method consistently showed the best diagnostic performance. A limitation is the currently limited availability in clinical practice. The already commercially available synovial suPAR ELISA test did not provide any significant diagnostic value that would justify the more invasive sample collection of a joint puncture compared to venous blood sampling. The multi-biomarker model showed a good diagnostic performance. However, it must be considered that this model does not represent a significant improvement compared to the results of the individual biomarkers (CRP, fibrinogen) on the used dataset.