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 construc-tion of nomogram prediction model
黄铂涵 1曹锋 1丁乙轩 1李昂 1罗涛 1王晓辉 1高崇崇 1王喆 1张超 1李非1
作者信息
- 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
- 折叠
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x2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(x2=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＜5.775×109/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(优势比=3.85,2.86,6.40,95％可信区间为1.68～8.85,1.18～6.95,1.56～26.35,P＜0.05).(3)AP继发脾大列线图预测模型的构建及评价.根据多因素分析结果,纳入AP发病24h内白细胞计数、AP发病3～7 d修订版CT严重程度指数及局部并发症构建预测AP继发脾大的列线图预测模型.列线图预测模型受试者工作特征曲线下面积为0.76(95％可信区间为0.69～0.83,P＜0.05),灵敏度为0.87,特异度为0.55.校准曲线显示:列线图预测模型预测值与实际观察值吻合较好.决策曲线显示:列线图预测模型具有较高的临床应用价值.结论 AP继发脾大患者比非继发脾大患者疾病严重程度更重.AP发病24 h内白细胞计数＜5.775×109/L、AP发病3～7d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,其列线图预测模型可预测AP继发脾大发生概率.
Abstract
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.Results(1)Occurrence and clinical characteristics of splenomegaly secondary to AP.The first detection time of 60 patients with splenomegaly secondary to AP was 60(30,120)days after the onset of AP.Cases with persistent respiratory dysfunction,multi-ple organ failure,severity of illness as mild or moderately severe/severe,pancreatic and/or peripan-creatic infection,surgery were 19,17,4,56,37,32 for 60 patients with splenomegaly secondary to AP,versus 16,19,43,77,39,29 for 120 patients without splenomegaly secondary to AP,respectively,showing significant differences in the above indicators between the two groups(x2=8.58,3.91,17.64,13.95,15.19,P＜0.05).(2)Influencing factors for splenomegaly secondary to AP.Resuts of mul-tivariate analysis showed that white blood cell count＜5.775x109/L within 24 hours of AP onset,revised computed tomography(CT)severity index＞7 in 3-7 days after onset and the presence of local complications were independent risk factors influencing the splenomegaly secondary to AP(odds ratio=3.85,2.86,6.40,95％confidence interval as 1.68-8.85,1.18-6.95,1.56-26.35,P＜0.05).(4)Construction and evaluation of a nomogram prediction model for splenomegaly secondary to AP.The nomogram prediction model was constructed based on white blood cell count within 24 hours of AP onset,revised CT severity index in 3-7 days after onset and local complications.The area under the receiver operating characteristic curve of the nomogram prediction model was 0.76(95％confidence interval as 0.69-0.83,P＜0.05),with a sensitivity of 0.87 and a specificity of 0.55.The cali-bration curve demonstrated consistency between the predicted rate from the nomogram prediction model and the actually observed rate.The decision curve analysis indicated that the nomogram pre-diction model had favorable clinical practicability.Conclusions Patients with AP who develop sec-ondary splenomegaly tend to have a higher severity of illness than those develop no secondary sple-nomegaly.White blood cell count＜5.775x109/L within 24 hours of AP onset,revised CT severity index＞7 in 3-7 days after onset and presence of local complications are independent risk factors influencing splenomegaly secondary to AP,and its nomogram prediction model can predict inci-dence rate of splenomegaly secondary to AP.
关键词
急性胰腺炎/脾大/危险因素/列线图/预测模型Key words
Acute pancreatitis/Splenomegaly/Risk factors/Nomogram/Prediction model引用本文复制引用
基金项目
首都医学发展科研专项(2020-1-2012)
首都临床诊疗技术研究项目(Z201100005520090)
北京市市属医院科研培育项目(PX2022035)
出版年
2024
NETL
NSTL
万方数据