中、重度脑外伤继发性急性肾损伤列线图预测模型的构建

Establishment of nomogram prediction model for acute kidney injury in patients with moderate and severe traumatic brain injury

目的构建中、重度脑外伤继发性急性肾损伤列线图预测模型以指导临床。方法回顾2017年2月至2020年3月浙江省人民医院收治的457例中、重度脑外伤患者临床资料,根据是否发生急性肾损伤(AKI)将患者分为AKI组与非AKI组,比较两组患者住院期间死亡、28 d病死率、肾脏替代治疗情况。采用多因素logistic回归分析筛选AKI危险因素,并使用筛选出的危险因素建立AKI列线图预测模型,应用AUC检验模型预测效果。结果 457例中、重度脑外伤患者中83例发生AKI,发生率为18.16%,AKI组住院期间死亡、28 d病死率、肾脏替代治疗发生率均高于非AKI组,差异均有统计学意义(均P<0.05);多因素logistic回归分析显示,年龄、基础肌酐(Scr)水平、急性生理与慢性健康评估Ⅱ(APACHEⅡ)评分、甘露醇使用量、急性呼吸衰竭是影响中、重度脑外伤继发性AKI发生的独立危险因素(均P<0.05);将独立危险因素构建列线图模型,AUC为0.799,校准曲线为斜率接近于1的直线,Hosmer-Lemeshow拟合优度检验χ2=7.982,P=0.435。结论基于影响中、重度脑外伤继发性AKI的危险因素即年龄、基础Scr水平、APACHEⅡ评分、甘露醇使用量、急性呼吸衰竭构建的列线图预测模型具有良好的区分度与准确度,对防治中、重度脑外伤患者继发性AKI的发生具有一定指导意义。

Objective To establish a nomogram prediction model of acute kidney injury in patients with moderate and severe traumatic brain injury. Methods The clinical data of 457 patients with moderate and severe traumatic brain injury admitted to Zhejiang Provincial Hospital from February 2017 to March 2020 were retrospectively analyzed, including 83 cases with acute kidney injury(AKI group) and 374 cases without AKI(non-AKI group). The risk factors of AKI were examined by multiple regression analysis and the AKI nomogram prediction model was established. The area under the ROC curve(AUC) was used to test the prediction effect of the model. Results The incidence of death during hospitalization, 28-day death and renal replacement therapy in AKI group were higher than those in non-AKI group(P<0.05). Multivariate logistic regression analysis showed that age, baseline Scr level, APACHE Ⅱ score, mannitol consumption and acute respiratory failure were independent risk factors of secondary AKI in patients with moderate and severe traumatic brain injury(P<0.05). The nomogram model was constructed using above independent risk factors with R software(R3.6.3). The AUC of nomogram model for diagnosis of AKI was 0.799, the calibration curve was a straight line with slope close to 1, the Hosmer-Lemeshow goodness-of-fit test showed χ^2= 7.982, P= 0.435.Conclus ion The established nomogram prediction model has good discrimination effect and accuracy for secondary AKI in patients with moderate and severe traumatic brain injury.