Department of Surgery and Trauma, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands.
Ann Surg. 2010 Mar;251(3):512-20. doi: 10.1097/SLA.0b013e3181cfd342.
To select parameters that can predict which patients should receive abdominal computed tomography (CT) after high-energy blunt trauma.
Abdominal CT accurately detects injuries of the abdomen, pelvis, and lumbar spine, but has important disadvantages. More evidence for an appropriate patient selection for CT is required.
A prospective observational study was performed on consecutive adult high-energy blunt trauma patients. All patients received primary and secondary surveys according to the advanced trauma life support, sonography (focused assessment with sonography for trauma [FAST]), conventional radiography (CR) of the chest, pelvis, and spine and routine abdominal CT. Parameters from prehospital information, physical examination, laboratory investigations, FAST, and CR were prospectively recorded for all patients. Independent predictors for the presence of > or =1 injuries on abdominal CT were determined using a multivariate logistic regression analysis.
A total of 1040 patients were included, 309 had injuries on abdominal CT. Nine parameters were independent predictors for injuries on CT: abnormal CR of the pelvis (odds ratio [OR], 46.8), lumbar spine (OR, 16.2), and chest (OR, 2.37), abnormal FAST (OR, 26.7), abnormalities in physical examination of the abdomen/pelvis (OR, 2.41) or lumbar spine (OR 2.53), base excess <-3 (OR, 2.39), systolic blood pressure <90 mm Hg (OR, 3.81), and long bone fractures (OR, 1.61). The prediction model based on these predictors resulted in a R of 0.60, a sensitivity of 97%, and a specificity of 33%. A diagnostic algorithm was subsequently proposed, which could reduce CT usage with 22% as compared with a routine use.
Based on parameters from physical examination, laboratory, FAST, and CR, we created a prediction model with a high sensitivity to select patients for abdominal CT after blunt trauma. A diagnostic algorithm was proposed.
选择可预测哪些患者在遭受高能钝性外伤后需要接受腹部计算机断层扫描（CT）的参数。
腹部 CT 能准确检测腹部、骨盆和腰椎的损伤，但存在重要的缺点。需要更多证据来支持对 CT 进行适当的患者选择。
对连续的成年高能钝性创伤患者进行前瞻性观察性研究。所有患者均根据高级创伤生命支持（ATLS）进行初步和二次评估，包括超声检查（创伤重点评估超声检查[FAST]）、胸部、骨盆和脊柱的常规 X 线摄影（CR）以及常规腹部 CT。对所有患者前瞻性记录了院前信息、体格检查、实验室检查、FAST 和 CR 的参数。使用多元逻辑回归分析确定预测腹部 CT 上存在≥1 处损伤的独立预测因子。
共纳入 1040 例患者，其中 309 例患者的腹部 CT 有损伤。9 个参数是 CT 损伤的独立预测因子：骨盆（比值比[OR]，46.8）、腰椎（OR，16.2）和胸部（OR，2.37）CR 异常、FAST 异常（OR，26.7）、腹部/骨盆（OR，2.41）或腰椎（OR，2.53）体格检查异常、碱剩余（BE）<-3（OR，2.39）、收缩压（SBP）<90mmHg（OR，3.81）和长骨骨折（OR，1.61）。基于这些预测因子的预测模型得到的 R 为 0.60，敏感性为 97%，特异性为 33%。随后提出了一种诊断算法，与常规使用相比，该算法可将 CT 使用率降低 22%。
根据体格检查、实验室、FAST 和 CR 的参数，我们创建了一个具有高敏感性的预测模型，用于选择钝性外伤后进行腹部 CT 的患者。提出了一种诊断算法。
