急性胰腺炎继发脾大的影响因素分析及列线图预测模型构建  

Analysis of influencing factors for splenomegaly secondary to acute pancreatitis and construction of nomogram prediction model

作　　者：黄铂涵 曹锋[1] 丁乙轩 李昂[1] 罗涛[1] 王晓辉[1] 高崇崇[1] 王喆[1] 张超[1] 李非[1] Huang Bohan;Cao Feng;Ding Yixuan;Li Ang;Luo Tao;Wang Xiaohui;Gao Chongchong;Wang Zhe;Zhang Chao;Li Fei(Department of General Surgery,Clinical Center for Acute Pancreatitis,Xuanwu Hospital,Capital Medical University,Beijing 100053,China)

机构地区：[1]首都医科大学宣武医院普通外科、首都医科大学急性胰腺炎临床诊疗与研究中心,北京100053

出　　处：《中华消化外科杂志》2024年第5期712-719,共8页Chinese Journal of Digestive Surgery

基　　金：首都医学发展科研专项项目(2020⁃1⁃2012);首都临床诊疗技术研究(Z201100005520090);北京市属医院科研培育计划(PX2022035)。

摘　　要：目的探讨急性胰腺炎(AP)继发脾大的影响因素及列线图预测模型构建。方法采用回顾性病例对照研究方法。收集2017年12月至2021年12月首都医科大学宣武医院收治的180例AP患者的临床病理资料;男124例,女56例;年龄为(49±15)岁。180例患者中,60例AP继发脾大患者设为病例组;男48例,女12例;年龄为(47±13)岁。120例AP未继发脾大患者设为对照组;男76例,女44例;年龄为(50±16)岁。观察指标:(1)AP继发脾大的发生情况和临床特征。(2)AP继发脾大的影响因素分析。(3)AP继发脾大列线图预测模型的构建及评价。正态分布的计量资料以x±s表示,组间比较采用t检验;偏态分布的计量资料以M(Q1,Q3)表示,组间比较采用秩和检验。计数资料以绝对数表示,组间比较采用χ^(2)检验或Fisher确切概率法。单因素分析根据资料类型选择对应的统计学方法。采用受试者工作特征曲线判断最佳截断值。多因素分析采用Logistic向前逐步回归模型。根据多因素分析结果构建列线图预测模型,绘制受试者工作特征曲线,以曲线下面积评价列线图预测模型的区分度。以校准曲线评价列线图预测模型的一致性,以决策曲线评价其临床获益度。结果(1)AP继发脾大的发生情况及临床特征。60例AP患者继发脾大的首次发现时间为AP发病后60(30,120)d。60例AP继发脾大患者持续呼吸功能障碍,多器官功能衰竭,疾病严重程度(轻症、中度重症及重症),胰腺和(或)胰周感染、手术治疗分别为19例,17例,4、56例,37例,32例;120例AP未继发脾大患者上述指标分别为16例,19例,43、77例,39例,29例;两组患者上述指标比较,差异均有统计学意义(χ^(2)=8.58,3.91,17.64,13.95,15.19,P<0.05)。(2)AP继发脾大的影响因素分析。多因素分析结果显示:AP发病24 h内白细胞计数<5.775×10^(9)/L、AP发病3~7 d修订版CT严重程度指数>7、有局部并发症是影响AP继发脾大的独立危险因素(Objective To investigate the influencing factors for splenomegaly secondary to acute pancreatitis(AP)and construction of a nomogram prediction model.Methods The retro‑spective case‑control study was conducted.The clinicopathological data of 180 patients with AP who were admitted to Xuanwu Hospital of Capital Medical University from December 2017 to December 2021 were collected.There were 124 males and 56 females,aged(49±15)years.Among them,60 AP patients who developed secondary splenomegaly were taken as the case group,including 48 males and 12 females,aged(47±13)years,and the rest of 120 cases of AP without secondary splenomegaly were taken as the control group,including 76 males and 44 females,aged(50±16)years.Observation indicators:(1)occurrence and clinical characteristics of splenomegaly secondary to AP;(2)influenc‑ing factors for splenomegaly secondary to AP;(3)construction and evaluation of a nomogram predic‑tion model for splenomegaly secondary to AP.Measurement data with normal distribution were represented as Mean±SD,and comparison between groups was analyzed using the t test.Measure‑ment data with skewed distribution were represented as M(Q1,Q3),and comparison between groups was analyzed using the rank sum test.Count data were represented as absolute numbers,and com‑parison between groups was analyzed using the chi‑square test or Fisher exact probability.The uni‑variate analysis was performed using statistical methods appropriate to the data type.The optimal cut-off value was determined by the receiver operating characteristic curves.Multivariate analysis was conducted using the Logistic regression model with forward method.Based on the results of the multivariate analysis,a nomogram prediction model was constructed.The receiver operating charac‑teristic curve was drawn,and the discrimination was evaluated using the area under curve.The con‑sistency of the nomogram prediction model was evaluated using calibration curve,and its clinical benefit was evaluated using decision curve.

关 键 词：急性胰腺炎 脾大 危险因素 列线图 预测模型 

分 类 号：R657.51[医药卫生—外科学]