创伤性胰腺炎预后早期危险因素分析及预测模型建立

Analysis of early risk factors and establishment of predictive model for prognosis of traumatic pancreatitis

目的探讨影响创伤性胰腺炎(traumatic pancreatitis,TP)患者的预后危险因素,并建立TP的多指标早期联合预测模型。方法回顾性收集2017年6月至2022年6月收治于郑州大学第一附属医院ICU的患者,根据TP患者的临床预后转归结局将其分为预后良好组和预后不良组。分别比较两组患者之间的性别、年龄、基础疾病及格拉斯哥昏迷评分(Glasgow Coma Scale,GCS)、急性生理与慢性健康评分Ⅱ(acute physiology and chronic health evaluationⅡ,APACHEⅡ)、损伤严重度评分(injury severity score,ISS)、急性胰腺炎严重程度床边指数(bedside index for severity in acute pancreatitis,BISAP)评分等一般资料,和患者入院时的血常规、血凝、血气分析、肝肾功等临床检验指标。分别采用单因素分析及多因素Logistic回归分析的统计学方法筛选得到TP预后不良的早期独立预测指标,并联合各独立指标建立联合预测模型。绘制上述各指标和预测模型的受试者工作特征曲线(ROC曲线),并分别检测其ROC曲线下面积(AUC)、敏感度、特异度和最佳预测临界值以分析诊断效果。结果精神障碍并发率、GCS、APACHEⅡ、合并颅脑损伤、合并胸部损伤、活化部分凝血活酶时间、纤维蛋白(原)降解产物、乳酸、谷草转氨酶、肾小球滤过率、淀粉酶、脂肪酶、N-末端脑利钠肽前体、肌红蛋白、降钙素原、ISS、BISAP在预后良好与预后不良组间的差异有统计学意义(均P<0.05)。多因素Logistic回归结果显示,乳酸(OR=1.636,95%CI:1.046~2.559)、脂肪酶(OR=1.005,95%CI:1.001~1.008)和ISS(OR=1.161,95%CI:1.064~1.266)是TP患者预后的独立影响因素。联合上述各独立危险因素建立联合预测模型Logit P=-9.260+0.492×乳酸+0.005×脂肪酶+0.149×ISS,并绘制ROC曲线,显示该预测模型的AUC为0.96(95%CI:0.91~1.00),表明其具有较好预测TP预后不良结局的能力。结论乳酸、脂肪酶、ISS为TP预后相关的早期独立危险因素,其联合预测模型具有良好的临床预测效果,可为TP的预后结局早期预测及诊治提供参考。

Objective To analyze the prognostic risk factors of patients with traumatic pancreatitis(TP)and establish an early combined prediction of multiple indicators model for TP.Methods Patients admitted to the ICU of the First Affiliated Hospital of Zhengzhou University from June 2017 to June 2022 were collected retrospectively.Based on their prognosis,the patients were divided into two groups:the good prognosis group and the poor prognosis group.The general data such as sex,age,underlying diseases,Glasgow Coma Scale(GCS),acute physiology and chronic health evaluationⅡ(APACHEⅡ),injury severity score(ISS),bedside index for severity in acute pancreatitis(BISAP),and clinical test indices such as blood routine,blood coagulation,blood gas analysis,and liver and kidney function at admission were compared between the two groups.Univariate analysis and multivariate logistic regression analysis were used to screen the early independent predictors of poor prognosis of TP,and the prediction model of TP was established by combining all of the independent indicators.The receiver operating characteristic(ROC)curve of each independent predictor and prediction model was drawn,and the area under the curve(AUC),sensitivity,specificity,and optimal cut-off value were calculated to examine the diagnostic impact of each independent predictor and the combined prediction model.Results There were statistically significant differences in the complication rate of mental disorders,GCS,APACHE II,combined craniocerebral injury,combined chest injury,activated partial thromboplastin time,fibrin(pro)degradation products,lactate,aspartate aminotransferase,glomerular filtration rate,amylase,lipase,NT-proBNP,myoglobin,procalcitonin,ISS,and BISAP between the good and poor prognosis groups(all P<0.05).Multivariate logistic regression analysis showed that lactate(OR=1.636,95%CI:1.046-2.559),lipase(OR=1.005,95%CI:1.001-1.008),and ISS(OR=1.161,95%CI:1.064-1.266)were independent risk factors influencing the prognosis of patients with TP.Based on the risk factors listed above,a prediction model was created:Logit P=-9.260+0.492×lactate+0.005×lipase+0.149×ISS,and the ROC curve was plotted.The AUC curve of the prediction model was 0.96(95%CI:0.91-1.00).Conclusions Lactate,lipase,and ISS are early independent risk factors associated with the prognosis of TP.Their combined multi-indicator prediction model has an excellent clinical prediction effect,which can provide a clinical reference for early prediction and treatment of TP.