Background: Septic arthritis is an orthopedic emergency requiring immediate surgical intervention. Current diagnostic standard of care is an invasive joint aspiration. Aspirations provide information about the inflammatory cells in the sample within a few hours, but there is often ambiguity about whether the source is infectious (e.g. bacterial) or non-infectious (e.g. gout). Cultures can take days to result, so decisions about surgery are often made with incomplete data. Novel diagnostics are thus needed. The "Sepsis MetaScore" (SMS) is an 11-mRNA host immune blood signature that can distinguish between infectious and non-infectious acute inflammation. It has been validated in multiple cohorts across heterogeneous clinical settings.
Aim: To study whether the SMS holds diagnostic validity in determining the etiology of acute arthritis.
Methods: We conducted a blinded, prospective, non-interventional clinical study of the SMS. All patients undergoing work-up for a septic primary joint were enrolled. Patients proceeded through the normal standard-of-care pathway, including joint aspiration and inflammatory labs [white blood cell (WBC), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP)]. Venous blood was also drawn into PAX gene RNA-stabilizing tubes and mRNAs were measured using Nano String nCounter™. SMS was calculated blinded to clinical results.
Results: A total of 20 samples were included, of which 11 were infected based on aspiration or intra-operative cultures. The SMS had an area under the ROC curve (AUROC) of 0.87 for separating infectious from non-infectious conditions. For comparison, the AUROCs for ESR = 0.58, CRP = 0.6, and WBC = 0.59. At 100% sensitivity for infection, the specificity of the SMS was 40%, meaning nearly half of non-septic patients could have been ruled out for further intervention.
Conclusion: In this pilot study, SMS showed a high level of diagnostic accuracy in predicting septic joints compared to other diagnostic biomarkers. This quick blood test could be an important tool for early, accurate identification of acute septic joints and need for emergent surgery, improving clinical care and healthcare spending.
Keywords: Bioinformatics; Biomarkers; Diagnostics; Infection; Medical technology; Septic arthritis.
©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.