University of Health Sciences, Antalya Education and Research Hospital, Department of Orthopedics and Traumatology, Antalya, Turkey.
University of Health Sciences, Antalya Education and Research Hospital, Department of Emergency Medicine, Antalya, Turkey.
Injury. 2020 Mar;51(3):651-655. doi: 10.1016/j.injury.2020.01.034. Epub 2020 Jan 27.
This study aimed to compare CT and XR images of patients admitted to the emergency department due to wrist injuries and to evaluate the accuracy of XR in the diagnosis of fractures.
Patients; who admitted to ED with injuries due to wrist trauma and who underwent XR imaging and CT scans in the period from 1 January 2017 to 1 January 2018, were included in the study. CT scan image interpretation reports recorded in the hospital automation system were considered eligible to be included in the study. XR images were interpreted by an orthopedics and traumatology specialist. The sensitivity (Sn), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV) and Kappa (κ) coefficient of XR were calculated according to CT. Inter-rater agreement was graded according to κ values.
A total of 274 patients were included in the study. Fractures were identified in the XR images in 180 (66%) patients and in the CT images in 196 (72%) patients. Compared to CT, the Sn, Sp, PPV, NPV and κ coefficient of XR were 89%, 92%, 97%, 77% and 0.764 respectively. Compared to CT, the highest sensitivity of XR was measured to detecting radius (Sn: 95%, κ: 0.896) and 5th metacarpal fractures (Sn: 77%, κ: 0.859), the lowest sensitivity of XR was calculated in detecting scaphoid, capitate, pisiform, trapezium hamate, and triquetrum fractures (Sn: 59-14%, κ: 0.619-0.240). The sensitivity and κ coefficient of XR were calculated 54% and 0.530 in the adjacent bone fracture, 83% and 0.830 in joint dislocation, 75% and 0.661 in the fractures extending to the joint space.
XR is the first-choice imaging modality in the evaluation of wrist injuries, but CT imaging should be preferred when fractures extending to the joint space, adjacent bone fracture and carpal bone fracture are being considered.
本研究旨在比较因腕部损伤而就诊于急诊科的患者的 CT 和 X 射线图像,并评估 X 射线在骨折诊断中的准确性。
本研究纳入了 2017 年 1 月 1 日至 2018 年 1 月 1 日期间因腕部创伤就诊于急诊科并接受 X 射线和 CT 扫描的患者。记录在医院自动化系统中的 CT 扫描图像解读报告被认为符合纳入研究的条件。X 射线图像由骨科和创伤科专家解读。根据 CT 计算 X 射线的灵敏度(Sn)、特异性(Sp)、阳性预测值(PPV)、阴性预测值(NPV)和 Kappa(κ)系数。根据κ 值对观察者间一致性进行分级。
本研究共纳入 274 例患者。X 射线图像显示 180 例(66%)患者存在骨折,CT 图像显示 196 例(72%)患者存在骨折。与 CT 相比,X 射线的 Sn、Sp、PPV、NPV 和 κ 系数分别为 89%、92%、97%、77%和 0.764。与 CT 相比,X 射线检测桡骨骨折的灵敏度最高(Sn:95%,κ:0.896)和第 5 掌骨骨折(Sn:77%,κ:0.859),检测舟状骨、头状骨、钩骨、大多角骨和小多角骨骨折的灵敏度最低(Sn:59%-14%,κ:0.619-0.240)。X 射线检测相邻骨骨折的灵敏度和 κ 系数为 54%和 0.530,关节脱位的灵敏度和 κ 系数为 83%和 0.830,骨折延伸至关节间隙的灵敏度和 κ 系数为 75%和 0.661。
在评估腕部损伤时,X 射线是首选的影像学检查方法,但当考虑骨折延伸至关节间隙、相邻骨骨折和腕骨骨折时,应首选 CT 成像。