Department of Trauma Surgery, Trauma Center, Chungbuk National University Hospital, Cheongju, Republic of Korea.
Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea; Trauma Training Center, Severance Hospital, Yonsei University Health System, Seoul, Republic of Korea.
Int J Surg. 2017 Nov;47:127-134. doi: 10.1016/j.ijsu.2017.09.063. Epub 2017 Sep 28.
Abdominal and pelvic computed tomography (APCT) has become the preferred means for the initial evaluation of blunt trauma patients. However, computed tomography examination has some disadvantages, such as radiation exposure, the requirement for intravenous iodinated contrast medium, high cost, and time. We aimed to develop a nomogram to predict the need for APCT scanning after the primary survey of blunt trauma patients.
We conducted a retrospective observational cohort study at a single-center and reviewed medical records of 972 trauma patients admitted between January 2013 and June 2016. We enrolled 786 blunt trauma patients who had undergone APCT and were 16 years of age or older. A multivariate logistic regression model was used to determine independent predictors for trauma-related findings on APCT scans. A nomogram was constructed to predict injury on APCT scans based on each predictive factor.
Of 786 patients, 355 (45%) patients had at least 1 injury on APCT scans. Results of multivariate logistic regression analysis showed that independent predictive factors of injuries on APCT scans were as follows: falls (≥3 m high); pain (abdominal, back, flank, or pelvic); positive peritoneal signs; abnormal findings on chest radiographs; abnormal findings on pelvic radiographs; and positive findings on focused assessment with ultrasonography for trauma. The nomogram was developed using these parameters. The area under a receiver operating characteristic curve of the multivariate model for discrimination was 0.865 (95% confidence interval, 0.840-0.892). The calibration plot showed good agreement between predicted and observed outcomes. The maximal Youden index was 0.59, corresponding to a cutoff value > 59 points, which was considered the optimal cutoff value for the probability that the injury would be detected on APCT scans.
The nomogram, based on initial clinical findings in blunt trauma patients, will help clinicians be more selective in their use of APCT evaluations.
腹部和骨盆计算机断层扫描(APCT)已成为钝性创伤患者初始评估的首选方法。然而,计算机断层扫描检查有一些缺点,如辐射暴露、需要静脉内碘造影剂、成本高和时间长。我们旨在开发一个列线图来预测钝性创伤患者初步检查后需要进行 APCT 扫描。
我们在一家单中心进行了回顾性观察队列研究,回顾了 2013 年 1 月至 2016 年 6 月期间收治的 972 例创伤患者的病历。我们纳入了 786 例年龄在 16 岁及以上且接受过 APCT 的钝性创伤患者。使用多变量逻辑回归模型确定 APCT 扫描上与创伤相关的发现的独立预测因子。根据每个预测因素构建了一个列线图来预测 APCT 扫描上的损伤。
在 786 例患者中,355 例(45%)患者的 APCT 扫描至少有 1 处损伤。多变量逻辑回归分析结果表明,APCT 扫描上损伤的独立预测因子如下:坠落(≥3 m 高);疼痛(腹部、背部、侧腹或骨盆);阳性腹膜征;胸部 X 线片异常;骨盆 X 线片异常;创伤的超声重点评估阳性发现。该列线图是使用这些参数开发的。多变量模型的鉴别诊断曲线下面积为 0.865(95%置信区间,0.840-0.892)。校准图显示预测结果与观察结果之间具有良好的一致性。最大 Youden 指数为 0.59,对应的截断值>59 分,被认为是 APCT 扫描检测到损伤的概率的最佳截断值。
基于钝性创伤患者的初始临床发现的列线图将有助于临床医生更有选择性地使用 APCT 评估。