[1]文 博,王汐玉,燕 辛,等.糖尿病足复发风险预测模型的构建：联合时间依赖ROC的生存分析[J].中国美容医学,2024,(5):26-31.
　WEN Bo,WANG Xiyu,YAN Xin,et al.Establish of Prediction Model of Diabetes Foot Recurrence by Survival Analysis Combined with Time Dependent ROC[J].Medical Aesthetics and Beauty,2024,(5):26-31.
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糖尿病足复发风险预测模型的构建：联合时间依赖ROC的生存分析()
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《中国美容医学》[ISSN:1008-6445/CN:61-1347/R]

卷:
期数:
2024年5期
页码:
26-31
栏目:
出版日期:
2024-05-10

文章信息/Info

Title:
Establish of Prediction Model of Diabetes Foot Recurrence by Survival Analysis Combined with Time Dependent ROC
文章编号:
1008-6455（2024）05-0026-04
作者:
文 博1 ; 王汐玉2 ; 燕 辛1 ; 莫 然1 ; 林 樾1 ; 谭 谦1
(1.南京大学医学院附属鼓楼医院整形烧伤科 江苏 南京 210008 ;2.东南大学医学院 江苏 南京 210003 )
Author(s):
WEN Bo1 ;  WANG Xiyu2 ;  YAN Xin1 ;  MO Ran1 ;  LIN Yue1 ;  TAN Qian1
( 1.Department of Burns and Plastic Surgery, the Affi liated Drum Tower Hospital of NanJing University Medical School, Nanjing 210008, Jiangsu, China; 2.Southeast University School of Medicine, Nanjing 210003, Jiangsu, China )
关键词:
糖尿病足; 复发; 危险因素; 生存分析; 时间依赖ROC?/html>
Keywords:
diabetes foot;  recurrence;  risk factors;  survival analysis;  time-dependent ROC
分类号:
R622
文献标志码:
A
摘要:
目的：采用回顾性队列研究的方法，以时间依赖ROC曲线联合生存分析预测糖尿病足（Diabetic foot ulceration， DFU ）复发的危险因素并构建预测模型。方法：收集2018年1月-2023年1月于笔者科室住院治疗的DFU患者临床资料并随访患 者的复发情况，设计研究因素为年龄、性别、是否合并高血压、血谷丙转氨酶值（Alanine aminotransferase，ALT）、血 谷草转氨酶值（Aspartate aminotransferase，AST）、血碱性磷酸酶值（Alkaline phosphatase，ALP）、血谷酰转肽酶值 （Gamma-glutamyltransferase，GGT）、血乳酸脱氢酶值（Lactate dehydrogenase，LDH）、白蛋白、血糖控制情况、血尿 素氮值、血肌酐值、下肢血管病变、Wagner分级、是否存在骨质破坏、有无介入手术、有无截肢（趾）、有无植皮、是否吸 烟共19项。连续数据以时间依赖受试者工作特征曲线（time-ROC）计算最佳截断值转化为分类数据，以K-M法计算复发率， log-rank 检验进行单因素分析，COX比例风险回归模型进行多因素分析并构建预测模型，C-index评价模型准确度。结果：共 纳入74例DFU患者。糖尿病足愈合后的1、2、3、4年复发率分别为：12.1%、24.8%、33.8%、43.3%。是否吸烟（P=0.002）、 Wagner 分级（P=0.004）、是否存在骨质破坏（P=0.038）、是否合并下肢血管病变（P＜0.001）、年龄大小（P=0.034）、肌酐值高低（P=0.045）、有无截肢（P=0.022）是DFU复发的危险因素，其中吸烟（P＜0.001，HR=19.805）、年龄≥73岁 （P=0.009，HR=9.429）、血肌酐值≥66μmol/L（P=0.024，HR=5.423）是DFU复发的独立危险因素。糖尿病足复发的预测模 型：Y=2.986X1+2.244X2+1.691X3（吸烟=X1，年龄水平=X2，肌酐水平=X3），C-index=0.888，模型准确性高。结论：基于 时间依赖ROC联合生存分析构建的预测模型对判断糖尿病足复发率的准确度高。?/html>
Abstract:
Objective An retrospective cohort study was conducted to analyze the risk factors of diabetes foot (DFU) recurrence and build a prediction model by time-dependent ROC combined survival analysis. Methods Collect the clinical data of DFU patients hospitalized in author’s department from January 2018 to January 2023 and follow up the recurrence of DFU. Design nineteen research factors: age, gender, whether hypertension is combined, alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), glutamyl transpeptidase (GGT), lactate dehydrogenase (LDH), albumin, blood glucose control, urea nitrogen, creatinine value, lower limb vascular disease, Wagner grade, whether there is bone destruction, whether there is intervention surgery, whether there is amputation, whether there is skin grafting, whether smoking. The continuous data is converted into categorical data by calculating the cutoff point by time-dependent ROC, and the recurrence rate is calculated by K-M method. The log-rank test is used for single-factor analysis of risk factors, and the COX risk regression model is used for multi-factor analysis. Results A total of 74 DFU patients were included. The recurrence rates of 1, 2, 3 and 5 years after healing of DFU were 12.1%, 24.8%, 33.8% and 43.3%. Smoking (P=0.002), Wagner grade (P=0.004), bone destruction (P=0.038), lower limb vascular disease (P＜0.001), age (P=0.034), creatinine value (P=0.045), amputation (P=0.022) are risk factors for DFU recurrence, among which smoking (P＜0.001, HR=19.805), age ≥ 73 years old (P=0.009, HR=9.429), and blood creatinine value ≥ 66 μ mol/L(P=0.024, HR=5.423) are independent risk factors for DFU recurrence. The prediction model of the DFU recurrence is: Y=2.986X1+2.244X2+1.691X3 (smoking=X1, age level=X2, creatinine level=X3), C-index=0.888. The accuracy of the model is high. Conclusion The prediction model based on time-dependent ROC combined survival analysis has high accuracy in judging the recurrence rate of DFU.

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更新日期/Last Update: 2024-05-08