平均血糖波动幅度计算机辅助计算算法及实现  

The Use of a Computer-aided Calculation Algorithm for Calculating Mean Amplitude of Glycemic Excursions

作　　者：简峻[1] 沈洁[2] 彭达明[2] 陈志[2] 余学飞[1] 

机构地区：[1]南方医科大学生物医学工程学院,广州510515 [2]南方医科大学南方医院,广州510515

出　　处：《中国生物医学工程学报》2011年第6期820-828,共9页Chinese Journal of Biomedical Engineering

基　　金：广东省科技计划项目(2009B011400036)

摘　　要：以传统人工计算方法为基础,结合利用改进微分法,寻找动态血糖数据极值点,并完善血糖有效波动的判断条件,提出一种能利用计算机辅助计算平均血糖波动幅度(MAGE)的算法,利用Visual C#2008实现该算法的软件应用,并利用传统人工计算方法(MAGEo)与计算机辅助计算方法(MAGEc),对76例临床动态血糖监测数据(正常成人27例,2型糖尿病成人患者25例,正常孕妇24例)进行比较计算,对结果进行相关分析及两种方法的一致性评估。比较结果显示:1)MAGEc方法与MAGEo方法的计算结果对于不同受监测者分组均显著相关(正常成人组r=0.994,P<0.01;2型糖尿病成人患者组r=0.997,P<0.01;正常孕妇组r=0.998,P<0.01;所有受监测者r=0.997,P<0.01)。2)Bland-Altman法分析可知,落在一致性界限外的点分别为:正常成人组3个,占11.1%(3/27);2型糖尿病成人患者组1个,占4%(1/25);正常孕妇组1个,占4.2%(1/24);所有受监测者6个,占7.9%(6/76)。两种方法之间具有较好的一致性。利用MAGE计算机辅助计算算法,能解决临床科研工作中通过人工计算MAGE带来的计算时间冗长、计算结果准确性低的问题,大大提高临床科研工作的效率。In this paper a computer-aided calculation algorithm based on the original manually method was proposed, on the basis of combining with the improved differentiation for searching extreme value points in continuous glucose monitoring data and improving the judgment of the amplitude of glycemic excursions, that implemented by using Visual C# 2008. The development and test of algorithm based on 24-h continuous glucose monitoring profile data collected during three different clinical studies involving 76 outpatients＇ CGM datasets （27 normal, 25 with type 2 diabetes and 24 from normal pregnant women） , using the CGMS Gold（ Medtronic MiniMed, Northridge, CA）. Correlation analyses and a Bland-Altman procedure were used to compare the results of MAGE calculations performed using the developed computer program （MAGEc） and the original method （MAGEo）. Results： （1） Close linear correlations between MAGEc and MAGEo were documented in the normal, the type 2 diabetes, the normal pregnant women and all subjects （ r = 0. 994, O. 997, 0. 998, and 0. 997, respectively; P 〈 0. O1 for all） , as was the absence of any systematic error between the two calculation methods. （2）From the Bland-Ahman plots, the point s fall outside the limits in consistency were followed by the normal 11.1% , the type 2 diabetes 4% , the normal pregnant women 4.2% and all subjects 7.9%. The proposed algorithm eliminates both tedium and/or errors of manually calculating the mean amplitude of glycemicexcursions, and greatly improves the efficiency of clinical studies.

关 键 词：平均血糖波动幅度 计算机辅助计算 

分 类 号：R318[医药卫生—生物医学工程]