ArticlePeerJ2025
Diagnostic accuracy of fat pad sign, X-ray, and computed tomography in elbow trauma: implications for treatment choices-a retrospective study.
Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Identifying skeletal injuries significantly impacts patient outcomes in trauma cases. This study aims to compare the diagnostic accuracy of X-ray (XR) and computed tomography (CT) in detecting elbow fractures among patients presenting at the emergency department (ED). Additionally, the study assesses the potential contribution of the fat pad sign to enhancing the diagnostic accuracy of XR images in identifying elbow fractures. The secondary aim focused on evaluating the precision of XR imaging in determining the necessity for surgical intervention among patients presenting with elbow trauma. Methods: Conducted retrospectively at an ED within a secondary hospital, this study included patients with elbow trauma between January 1, 2017, and January 1, 2020, who underwent both XR and CT imaging of the elbow joint. Following the application of exclusion criteria, the analysis comprised 183 patients based on remaining image data. Results: When comparing XR to CT for fracture detection, XR exhibited a sensitivity of 46.9%, specificity of 85.9%, positive predictive value (PPV) of 79.3%, negative predictive value (NPV) of 58.4%, area under the curve (AUC) of 0.664. Considering the fat pad sign in XR as a fracture indicator, the sensitivity is 60.2%, specificity is 81.2%, PPV is 78.7%, NPV is 63.9% and AUC is 0.707. A significant difference was found when comparing the AUCs obtained with and without considering the fat pad sign ( Conclusion: The findings indicate that XR alone is insufficient for detecting elbow fractures and determining the need for surgical treatment. Incorporating the fat pad sign improves the diagnostic accuracy of XR. In cases where suspicion of fracture is high, considering CT imaging is crucial to avoid missed diagnoses, prevent complications, and guide treatment decisions effectively.
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