Glycemic Risk Index Profiles and Predictors Among Diverse Adults With Type 1 Diabetes.

IF 4.1 Q2 ENDOCRINOLOGY & METABOLISM
Claire J Hoogendoorn, Raymond Hernandez, Stefan Schneider, Mark Harmel, Loree T Pham, Gladys Crespo-Ramos, Shivani Agarwal, Jill Crandall, Anne L Peters, Donna Spruijt-Metz, Jeffrey S Gonzalez, Elizabeth A Pyatak
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Abstract

Background: The Glycemia Risk Index (GRI) was introduced as a single value derived from the ambulatory glucose profile that identifies patients who need attention. This study describes participants in each of the five GRI zones and examines the percentage of variation in GRI scores that is explained by sociodemographic and clinical variables among diverse adults with type 1 diabetes.

Methods: A total of 159 participants provided blinded continuous glucose monitoring (CGM) data over 14 days (mean age [SD] = 41.4 [14.5] years; female = 54.1%, Hispanic = 41.5%). Glycemia Risk Index zones were compared on CGM, sociodemographic, and clinical variables. Shapley value analysis examined the percentage of variation in GRI scores explained by different variables. Receiver operating characteristic curves examined GRI cutoffs for those more likely to have experienced ketoacidosis or severe hypoglycemia.

Results: Mean glucose and variability, time in range, and percentage of time in high, and very high, glucose ranges differed across the five GRI zones (P values < .001). Multiple sociodemographic indices also differed across zones, including education level, race/ethnicity, age, and insurance status. Sociodemographic and clinical variables collectively explained 62.2% of variance in GRI scores. A GRI score ≥84.5 reflected greater likelihood of ketoacidosis (area under the curve [AUC] = 0.848), and scores ≥58.2 reflected greater likelihood of severe hypoglycemia (AUC = 0.729) over the previous six months.

Conclusions: Results support the use of the GRI, with GRI zones identifying those in need of clinical attention. Findings highlight the need to address health inequities. Treatment differences associated with the GRI also suggest behavioral and clinical interventions including starting individuals on CGM or automated insulin delivery systems.

不同类型1型糖尿病成年人的血糖风险指数概况和预测因素。
背景:血糖风险指数(GRI)是从动态血糖谱中得出的一个单一值,用于识别需要关注的患者。这项研究描述了五个GRI区域中每一个区域的参与者,并检查了GRI评分的变化百分比,这是由不同的1型糖尿病成年人的社会人口统计学和临床变量解释的。方法:共有159名参与者提供了14天内的盲法连续血糖监测(CGM)数据(平均年龄[SD]=41.4[14.5]岁;女性=54.1%,西班牙裔=41.5%)。比较了CGM、社会人口统计学和临床变量的血糖风险指数区。Shapley值分析检验了由不同变量解释的GRI得分的变化百分比。受试者操作特征曲线检查了那些更有可能经历酮症酸中毒或严重低血糖的GRI临界值。结果:五个GRI区域的平均血糖和变异性、范围内时间以及高血糖和极高血糖范围内时间的百分比存在差异(P值<.001)。多个社会人口学指标也存在差异,包括教育水平、种族/民族、年龄和保险状况。社会形态和临床变量共同解释了GRI评分62.2%的差异。GRI评分≥84.5反映酮症酸中毒的可能性更大(曲线下面积AUC=0.484),评分≥58.2反映前六个月发生严重低血糖的可能性更高(AUC=0.729)。结论:结果支持GRI的使用,GRI区域确定了那些需要临床注意的区域。调查结果强调了解决卫生不平等问题的必要性。与GRI相关的治疗差异也表明了行为和临床干预措施,包括让个体开始使用CGM或自动胰岛素输送系统。
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来源期刊
Journal of Diabetes Science and Technology
Journal of Diabetes Science and Technology Medicine-Internal Medicine
CiteScore
7.50
自引率
12.00%
发文量
148
期刊介绍: The Journal of Diabetes Science and Technology (JDST) is a bi-monthly, peer-reviewed scientific journal published by the Diabetes Technology Society. JDST covers scientific and clinical aspects of diabetes technology including glucose monitoring, insulin and metabolic peptide delivery, the artificial pancreas, digital health, precision medicine, social media, cybersecurity, software for modeling, physiologic monitoring, technology for managing obesity, and diagnostic tests of glycation. The journal also covers the development and use of mobile applications and wireless communication, as well as bioengineered tools such as MEMS, new biomaterials, and nanotechnology to develop new sensors. Articles in JDST cover both basic research and clinical applications of technologies being developed to help people with diabetes.
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