摘要
背景糖化血红蛋白(HbA_(1c))控制达标可降低老年2型糖尿病患者的并发症发生风险,维持良好的HbA_(1c)是管理老年2型糖尿病的重要手段,但近年来有越来越多的研究表明老年2型糖尿病患者HbA_(1c)达标率普遍较低,而HbA_(1c)预测模型可以辅助降低老年糖尿病患者HbA_(1c)控制不达标的风险。目的寻找影响老年2型糖尿病患者HbA_(1c)控制达标的因素,建立HbA_(1c)达标预测模型及评分表,为老年2型糖尿病患者的血糖管理提供一种可靠工具。方法采用面对面的问卷调查方式收集2018年3月—2019年12月在四川省人民医院内分泌科就诊的老年2型糖尿病患者的性别、年龄、在岗情况、民族、婚姻状况、文化程度、体型、中心性肥胖、糖尿病家族史、前次HbA_(1c)、糖尿病病程、空腹血糖监测情况、本次HbA_(1c)检查结果、空腹血糖、现阶段治疗方案维持时间、服药依从性情况、使用口服药物种类、是否使用胰岛素、降糖药物日花费、是否高血压、是否高脂血症、是否合并糖尿病并发症、每日运动时间、睡眠情况、是否合理控制饮食、抑郁状态等信息,并根据患者本次HbA_(1c)检查结果分为HbA_(1c)达标组(224例)及HbA_(1c)未达标组(259例)。使用单因素Logistic分析及Lasso-Logistic回归分析筛选变量,以HbA_(1c)为结局指标建立Logistic回归模型与评分表。采用Bootstrap方法对模型进行内部验证,使用受试者工作特征曲线(ROC曲线)和校准图评价模型的区分度和校准度、使用评分-发生概率图验证评分表性能,并找出评分表的最佳切点。结果两组老年2型糖尿病患者年龄、中心性肥胖、前次HbA_(1c)、糖尿病病程、空腹血糖、服药依从性、使用口服药物种类、使用胰岛素情况、糖尿病并发症情况、每日运动时间、合理控制饮食情况、抑郁状态比较,差异均有统计学意义(P<0.05)。单因素Logistic回归分析结果显�
Background Achieving hemoglobin control can reduce the risk of complications of type 2 diabetes among elderly patients and the hemoglobin management is crucial in the daily management of type 2 diabetes.However,there has been increasingly evidence shows that the achieving rate of hemoglobin-control among elderly patients with type 2 diabetes are generally poor.However,the risk prediction models of hemoglobin can be generally used to predict high level hemoglobin risk for individual patients.Objective To establish target predictive model and scale of HbA_(1c) by exploring influencing factors of hemoglobin-control in elderly patients with type 2 diabetes,in order to provide a kind of versatile and reliable tool for diabetes management.Methods The basic information and related laboratory indexes of 483 elderly patients with type 2 diabetes referred to the endocrinology department,Sichuan Provincial People's Hospital from March 2018 to December 2019 were collected by face-to-face questionnaire survey,including gender,age,occupation,nationality,marital status,educational level,body size,family history of diabetes,central obesity comparison,previous HbA_(1c) values,the HbA_(1c) test result,the duration of diabetes,fasting blood sugar monitoring situation,fasting blood glucose values,the present stage treatment,medication compliance,type of oral medication,whether to use insulin,glucose-lowering drugs daily cost,high blood pressure,high cholesterol,whether merger diabetes complications,daily exercise time,quality of sleep,diet control,and depression.According to the results of HbA_(1c) examination,the patients were divided into:HbA_(1c) up to standard group(224 cases)and HbA_(1c) not up to standard group(259 cases).Univariate and multivariate Lasso-Logistic regression were used for variable selection,and hemoglobin values were used as independent variables to build the predictive models and rating scales.Bootstrap method were used for internal validity analysis of the prediction models.The sensitivity,specificity as wel
作者
杨恒博
袁蓉
石霞
吴行伟
YANG Hengbo;YUAN Rong;SHI Xia;WU Xingwei(Chengdu Second People's Hospital,Chengdu 610213,China;Sichuan Academy of Medical Sciences/Sichuan Provincial People's Hospital,Chengdu 610072,China;School of Medicine,University of Electronic Science and Technology of China/Personalized Drug Therapy Key Laboratory of Sichuan Province,Chengdu 610054,China)
出处
《中国全科医学》
CAS
北大核心
2021年第14期1841-1847,共7页
Chinese General Practice
基金
四川省卫生健康科研课题普及项目(19PJ262)。
关键词
糖尿病
2型
老年人
糖化血红蛋白
预测模型
并发症
Diabetes mellitus,type 2
Aged
Hemoglobin control
Predicting model
Complications
