Gómez Ana M, Muñoz Oscar M, Marin Alejandro, Fonseca Maria Camila, Rondon Martin, Robledo Gómez María Alejandra, Sanko Andrei, Lujan Dilcia, García-Jaramillo Maira, León Vargas Fabian Mauricio
1 Pontificia Universidad Javeriana, Bogotá, Colombia.
2 Hospital Universitario San Ignacio, Bogotá, Colombia.
J Diabetes Sci Technol. 2018 Sep;12(5):1007-1015. doi: 10.1177/1932296818758105. Epub 2018 Feb 16.
Recent publications frequently introduce new indexes to measure glycemic variability (GV), quality of glycemic control, or glycemic risk; however, there is a lack of evidence supporting the use of one particular parameter, especially in clinical practice.
A cohort of type 2 diabetes mellitus (T2DM) patients in ambulatory care were followed using continuous glucose monitoring sensors (CGM). Mean glucose (MG), standard deviation, coefficient of variation (CV), interquartile range, CONGA1, 2, and 4, MAGE, M value, J index, high blood glucose index, and low blood glucose index (LBGI) were estimated. Hypoglycemia incidence (<54 mg/dl) was calculated. Area under the curve (AUC) was determined for different indexes as identifiers of patients with risk of hypoglycemia (IRH). Optimal cutoff thresholds were determined from analysis of the receiver operating characteristic curves.
CGM data for 657 days from 140 T2DM patients (4.69 average days per patient) were analyzed. Hypoglycemia was present in 50 patients with 144 hypoglycemic events in total (incidence rate of 0.22 events per patient/day). In the multivariate analysis, both CV (OR 1.20, 95% CI 1.12-1.28, P < .001) and LBGI (OR 4.83, 95% CI 2.41-9.71, P < .001) were shown to have a statistically significant association with hypoglycemia. The highest AUC were for CV (0.84; 95% CI 0.77-0.91) and LBGI (0.95; 95% CI 0.92-0.98). The optimal cutoff threshold for CV as IRH was 34%, and 3.4 for LBGI.
This analysis shows that CV can be recommended as the preferred parameter of GV to be used in clinical practice for T2DM patients. LBGI is the preferred IRH between glycemic risk indexes.
最近的出版物经常引入新的指标来衡量血糖变异性(GV)、血糖控制质量或血糖风险;然而,缺乏证据支持使用某一特定参数,尤其是在临床实践中。
使用连续血糖监测传感器(CGM)对一组接受门诊治疗的2型糖尿病(T2DM)患者进行随访。估算了平均血糖(MG)、标准差、变异系数(CV)、四分位间距、CONGA1、2和4、平均血糖波动幅度(MAGE)、M值、J指数、高血糖指数和低血糖指数(LBGI)。计算低血糖发生率(<54 mg/dl)。确定不同指标作为低血糖风险患者(IRH)标识符的曲线下面积(AUC)。通过分析受试者工作特征曲线确定最佳截断阈值。
分析了140例T2DM患者657天的CGM数据(每位患者平均4.69天)。50例患者出现低血糖,共发生144次低血糖事件(发生率为每位患者/天0.22次事件)。在多变量分析中,CV(比值比1.20,95%置信区间1.12 - 1.28,P <.001)和LBGI(比值比4.83,95%置信区间2.41 - 9.71,P <.001)均显示与低血糖有统计学显著关联。最高的AUC分别为CV(0.84;95%置信区间0.77 - 0.91)和LBGI(0.95;95%置信区间0.92 - 0.98)。作为IRH的CV最佳截断阈值为34%,LBGI为3.4。
该分析表明,CV可被推荐为T2DM患者临床实践中GV的首选参数。在血糖风险指标中,LBGI是首选的IRH。