高脂血症性重症急性胰腺炎早期预测模型的建立

Establishment of early prediction model for patients with hyperlipidemic severe acute pancreatitis

目的联合运用多个指标建立早期预测高脂血症性急性胰腺炎(hyperlipidemic acute pancreatitis,HLAP)进展为重症胰腺炎(severe acute pancreatitis,SAP)的风险模型。方法回顾性分析厦门大学附属第一医院急诊部2018年3月至2020年2月收治的92例HLAP患者临床资料。其中29例进展为SAP,63例未进展为SAP。应用单因素分析筛选高脂血症性重症急性胰腺炎(hyperlipidemic severe acute pancreatitis,HL-SAP)相关的指标,Logistic回归分析筛选HL-SAP独立预测指标,构建预测模型。通过受试者工作特性(ROC)曲线下面积(AUC)评估各个预测指标及模型对HL-SAP的预测能力。运用Bootstrap重抽样法对模型的预测能力进行内部验证。结果单因素分析发现降钙素原(procalcitonin,PCT)、D-二聚体、C反应蛋白(C-reactive protein,CRP)、白蛋白、胆固醇和CT分级等对HLAP是否进展为SAP有影响(P<0.05)。Logistic回归分析结果显示D-二聚体(OR=2.112;95%CI:1.022~4.366;P<0.05)、CT分级(OR=5.818;95%CI:2.481~13.643;P<0.01)、胆固醇(OR=1.146;95%CI:1.004~1.308;P<0.05)为HL-SAP发生的独立影响因素。D-二聚体、CT分级、胆固醇和三者联合预测模型的AUC分别为0.802、0.875、0.665和0.927。模型预测能力的内部验证表明,C指数为0.927。结论早期运用联合D-二聚体、CT分级及胆固醇的模型对HL-SAP有良好的预测效果。

Objective To establish an early prediction model with multiple indicators to predict the risk of severe acute pancreatitis(SAP)in hyperlipidemic acute pancreatitis(HLAP).Methods The clinical data of 92 patients with HLAP admitted to the Emergency Department of our hospital from March 2018 to February 2020 were analyzed retrospectively.Among them,29 cases deteriorated to SAP and 63 cases did not.Univariate analysis was used to screen predictive indicators related to hyperlipidemic severe acute pancreatitis(HL-SAP),and logistic regression analysis was used to screen independent predictive indicators related to HL-SAP.Then a prediction model was established.The area under(AUC)the receiver operating curve(ROC)was used to evaluate the predictive ability of each predictive indicator and the model for HL-SAP.Bootstrap resampling technology was used to validate the predictive ability of the model.Results Univariate analysis showed that procalcitonin,D-dimer,C-reactive protein,albumin,cholesterol and CT grade had influence on the progression of HLAP to SAP(P<0.05).Logistic regression analysis showed that D-dimer(OR=2.112,95%CI:1.022-4.366;P<0.05),CT grade(OR=5.818,95%CI:2.481-13.643;P<0.01)and cholesterol(OR=1.146,95%CI:1.004-1.308;P<0.05)were independent risk factor of HL-SAP.The AUC of D-dimer,CT grade,cholesterol and the model were 0.802,0.875,0.665 and 0.927,respectively.Internal validation of the predictive ability of the model showed that the C-index was 0.927.Conclusions In the early phase,application of the prediction model that composes D-dimer,CT grade and cholesterol has a good predictive effect on HL-SAP.