基于炎症因子、肺超声和CT评分系统的急性胰腺炎预后不良列线图预测模型的构建  

Establishment of a nomogram prediction model for poor prognosis of acute pancreatitis based on inflammatory factors,lung ultrasound,and CT scores

作　　者：任夏 叶叶 刘罗杰 徐晓丹 张岩 REN Xia;YE Ye;LIU Luojie;XU Xiaodan;ZHANG Yan(Department of Gastroenterology,Changshu Hospital Affiliated to Soochow University&Changshu First People’s Hospital,Changshu,Jiangsu 215500,China;Department of Critical Care Medicine,Changshu Hospital Affiliated to Soochow University&Changshu First People’s Hospital,Changshu,Jiangsu 215500,China)

机构地区：[1]苏州大学附属常熟医院(常熟市第一人民医院)消化内科,江苏常熟215500 [2]苏州大学附属常熟医院(常熟市第一人民医院)重症医学科,江苏常熟215500

出　　处：《临床肝胆病杂志》2025年第4期713-721,共9页Journal of Clinical Hepatology

基　　金：苏州市科技发展计划项目(SLT2023006);常熟市科技发展计划重点项目(CSWS202209);中华国际医学交流基金会呼吸疾病专项项目(Z-2014-08-2309-1)。

摘　　要：目的本研究旨在通过分析急性胰腺炎(AP)患者的炎症因子、肺超声评分及CT评分系统,识别AP预后不良的独立危险因素,并构建列线图预测模型,为临床早期干预提供依据。方法选取2021年1月—2023年10月苏州大学附属常熟医院收治的409例AP患者为研究对象,使用简单随机抽样法以7∶3分为建模组(n=288)和验证组(n=121)。各组依据转归情况分为预后不良组与预后良好组。于入院72 h内检测患者C反应蛋白(CRP)、降钙素原(PCT)、IL-6、IL-10、TNF-α水平,并在入院48~72 h评估肺超声(LUS)评分、改良CT严重指数(MCTSI)评分和胰腺外炎症CT(EPIC)评分。符合正态分布的计量资料组间比较采用成组t检验;非正态分布的计量资料组间比较采用Mann-Whitney U秩和检验。计数资料组间比较采用χ2检验。使用LASSO回归筛选变量并纳入多因素Logistic回归模型,分析AP预后不良的独立危险因素,构建列线图预测模型,采用受试者操作特征曲线(ROC曲线)和校准曲线评估列线图模型的区分度和拟合优度,决策曲线分析评价预测模型的临床适用性。结果288例建模组AP患者中,预后不良组33例(11.46%),预后良好组255例(88.54%);121例验证组AP患者中,预后不良组13例(10.74%),预后良好组108例(89.26%)。建模组中,与预后良好组相比,预后不良组CRP(Z=3.607)、IL-6(Z=4.189)、TNF-α(t=2.584)水平,以及LUS评分(t=8.075)、MCTSI评分(t=5.929)、EPIC评分(t=8.626)均较高(P值均<0.05);多因素Logistic回归分析显示,CRP(OR=3.592,95%CI:1.272~10.138)、IL-6(OR=4.225,95%CI:1.468~12.156)、TNF-α(OR=3.540,95%CI:1.205~10.401)、LUS评分(OR=7.094,95%CI:2.398~20.986)、MCTSI评分(OR=7.612,95%CI:2.832~20.462)及EPIC评分(OR=11.915,95%CI:4.007~35.432)是AP患者发生预后不良的独立危险因素(P值均<0.05)。依据以上6项,建立列线图预测模型,ROC曲线下面积(AUC)为0.924(95%CI:0.883~0.964);最佳截断值的约登指数为0.670,灵敏度为0.909,特异度�Objective To investigate the independent risk factors for poor prognosis in patients with acute pancreatitis(AP)by analyzing inflammatory factors,lung ultrasound(LUS)scores,and CT scores,to establish a nomogram prediction model,and to provide a basis for early clinical intervention.Methods A total of 409 patients with AP who were admitted to Changshu Hospital Affiliated to Soochow University from January 2021 to October 2023 were enrolled as subjects,and they were divided into modeling group with 288 patients and validation group with 121 patients using the simple random sampling method at a ratio of 7∶3.According to the prognosis,each group was further divided into poor prognosis group and good prognosis group.The levels of C-reactive protein(CRP),procalcitonin(PCT),interleukin-6(IL-6),interleukin-10(IL-10),and tumor necrosis factor-α(TNF-α)were measured for both groups within 72 hours after admission,and LUS scores,modified CT severity index(MCTSI),and extrapancreatic inflammation on computed tomography(EPIC)scores were assessed within 48-72 hours after admission.The independent-samples t test was used for comparison of normally distributed continuous data between groups,and the Mann-Whitney U rank sum test was used for comparison of non-normally distributed continuous data between groups;the chi-square test was used for comparison of categorical data between groups.A LASSO regression analysis was used to screen for the variables that were included in the multivariate logistic regression model to identify the independent risk factors for the poor prognosis of AP,and then a nomogram prediction model was established.The receiver operating characteristic(ROC)curve and the calibration curve were used to assess the discriminatory ability and goodness of fit of the nomogram model,and a decision curve analysis was used to assess the clinical applicability of the model.Results Among the 288 patients with AP in the modeling group,there were 33(11.46%)in the poor prognosis group and 255(88.54%)in the good prognosis g

关 键 词：胰腺炎 C反应蛋白质 白细胞介素类 肺超声 列线图 

分 类 号：R576[医药卫生—消化系统]