Yokoyama Taro, Nakahara Shinji, Kondo Hiroshi, Miyake Yasufumi, Sakamoto Tetsuya
Department of Emergency Medicine Teikyo University School of Medicine Tokyo Japan.
Graduate School of Health Innovation Kanagawa University of Human Services Kawasaki Japan.
Acute Med Surg. 2022 Aug 2;9(1):e774. doi: 10.1002/ams2.774. eCollection 2022 Jan-Dec.
To support decision-making for early interventional radiology, this study aimed to derive and validate a novel and simple scoring system for predicting the necessity of interventional radiology therapies in trauma patients.
This retrospective study used data derived from the medical records of patients with severe traumatic injuries treated at a tertiary-level emergency institution. The score was derived from 168 patients treated between April 2015 and October 2016 and validated using data from 68 patients treated between November 2016 and July 2017. Logistic "least absolute shrinkage and selection operator (LASSO)" regression was used to select predictors. In order to compose the score, odds ratios derived from the logistic model were simplified to integer score coefficients. The score was evaluated using the area under the receiver operating characteristic curve. The best cut-off point for the score was determined using Youden's index, and sensitivity and specificity were calculated.
The derived score comprised three predictors (systolic blood pressure, positive findings in abdominal ultrasound assessment, and pelvic fracture) and ranged from 0 to 30. On validation, the area under the receiver operating characteristic curve for the score was 0.86 (95% confidence interval, 0.64-1.00). The sensitivity and specificity were 80% and 89%, respectively, with a cut-off point of 3.
This simple score, requiring variables obtainable immediately after hospital arrival, could aid in facilitating early interventional radiology team activation.
为支持早期介入放射学的决策制定，本研究旨在推导并验证一种新颖且简单的评分系统，用于预测创伤患者介入放射学治疗的必要性。
这项回顾性研究使用了来自一家三级急诊机构治疗的严重创伤患者病历的数据。该评分源自2015年4月至2016年10月期间治疗的168例患者，并使用2016年11月至2017年7月期间治疗的68例患者的数据进行验证。采用逻辑“最小绝对收缩和选择算子（LASSO）”回归来选择预测因子。为了构成该评分，将逻辑模型得出的比值比简化为整数评分系数。使用受试者操作特征曲线下的面积来评估该评分。使用约登指数确定该评分的最佳临界点，并计算敏感性和特异性。
得出的评分包含三个预测因子（收缩压、腹部超声评估阳性结果和骨盆骨折），范围为0至30。在验证时，该评分的受试者操作特征曲线下面积为0.86（95%置信区间，0.64 - 1.00）。敏感性和特异性分别为80%和89%，临界点为3。
这个简单的评分，只需入院后即可立即获得的变量，有助于促进早期介入放射学团队的启动。
