平扫CT联合临床指标对重症急性胰腺炎预测价值的探讨

Predictive value of non-enhanced CT combined with clinical indicators in severe acute pancreatitis

目的建立一个早期预测急性胰腺炎(AP)进展为重症胰腺炎(SAP)的Nomogram模型并进行验证。方法回顾性收集本院2016年1月至2022年7月收治的361例AP患者影像学与临床资料,男性221例(61.2%),女性140例(38.8%)。根据Atlantic评分,其中64例为SAP,297例为非SAP(NSAP)。通过单因素分析筛选差异有统计学意义的变量进行多因素Logistic回归分析,筛选出SAP的独立危险因素并建立Nomogram预测模型。运用受试者工作特征(ROC)曲线、校准曲线及决策曲线(DCA)分别评价模型的预测效能、准确性及临床实用性,运用Bootstrap法对模型进行内部验证。结果通过单因素分析和多因素Logistic回归分析,最终筛选出胸腔积液(OR=7.353,95%CI:3.344~16.170)、肾旁后间隙(PPS)受累(OR=3.149,95%CI:1.314~7.527)、血肌酐浓度(Cr)(OR=1.027,95%CI:1.017~1.038)、血清钙离子浓度(Ca^(2+))(OR=0.038,95%CI:0.009~0.166)为SAP发生的独立危险因素(P<0.05),以这四个因素建立Nomogram模型,该模型的ROC曲线下面积(AUC)为0.905(95%CI:0.869~0.933),模型的预测效能较好;校准曲线显示,模型对SAP的预测概率与实际概率相差较小,校准度高;内部验证结果显示,该模型预测SAP的区分度良好,C-index为0.90。DCA分析显示该模型的临床实用性较高。结论联合胸腔积液、PPS受累、Cr和Ca^(2+)构建的Nomogram模型对早期预测SAP有良好的效果,可为临床诊疗提供参考。

Objective To establish and validate a nomogram model for early prediction of the risk of acute pancreatitis(AP)progressing to severe acute pancreatitis(SAP).Methods CT signs and clinical laboratory parameters of 361 AP patients admitted to our Hospital from January 2016 to July 2022 were retrospectively collected.There were 221 males(61.2%)and 140 females(38.8%).According to the Atlantic score,all patients were divided into the SAP group(64 cases)and the non-SAP(NSAP)group(297 cases).Univariate analysis was used to screen out variables with statistically significant differences.Multivariate Logistic regression analysis was used to screen out the independent risk factors of SAP,and finally a nomogram prediction model was established.Receiver operating characteristic(ROC)curve,calibration curve and decision curve(DCA)were used to evaluate the predictive efficacy,accuracy and clinical practicability of the model,and Bootstrap method was used to verify the model internally.Results Univariate analysis and multivariate Logistic regression analysis showed that pleural effusion(OR=7.353,95%CI:3.344-16.170),posterior pararenal space(PPS)involvement(OR=3.149,95%CI:1.314-7.527),serum creatinine concentration(Cr)(OR=1.027,95%Cl:1.017-1.038)and serum calcium concentration(Ca^(2+))(OR=0.038,95%CI:0.009-0.166)were independent risk factors for SAP(P<0.05).A Nomogram model was established based on these four factors.The area under the ROC curve(AUC)of this model was 0.905(95%CI:0.869-0.933),indicating high predictive efficiency.Internal verification showed that the model had good accuracy in predicting SAP,and C-index was 0.90.DCA analysis showed that the model had high clinical practicability.Conclusions The Nomogram model combining pleural effusion,PPS involvement,Cr and Ca^(2+)had a good effect on early prediction of SAP,which could provide a new reference tool for clinical diagnosis and treatment.