Predicting Glucose Values: A New Era for Continuous Glucose Monitoring.

IF 4.1 Q2 ENDOCRINOLOGY & METABOLISM
Bernhard Kulzer, Lutz Heinemann
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引用次数: 0

Abstract

The last 25 years of CGM have been characterized above all by providing better and more accurate glucose values in real time and analyzing the measured glucose values. Trend arrows are the only way to look into the future, but they are often too imprecise for therapy adjustment. While AID systems provide algorithms to use glucose values for glucose control, this has not been possible with stand-alone CGM systems, which are most used by people with diabetes. By analyzing the measured values with algorithms, often supported by AI, this should be possible in the future. This provides the user with important information about the further course of the glucose level, such as during the night. Predictive approaches can be used by next-generation CGM systems. These systems can proactively prevent glucose events such as hypo- or hyperglycemia. With the Accu-Chek® SmartGuide Predict app, an integral part of a novel CGM system, and the Glucose Predict (GP) feature, people with diabetes have the first commercially available CGM system with predictive algorithms. It characterizes the CGM systems of the future, which not only analyze past values and current glucose values in the future, but also use these values to predict future glucose progression.

预测葡萄糖值:持续葡萄糖监测的新时代。
CGM 在过去 25 年中的主要特点是实时提供更好、更准确的血糖值,并对测量的血糖值进行分析。趋势箭头是展望未来的唯一方法,但对于调整疗法而言,趋势箭头往往过于不精确。虽然 AID 系统提供了利用血糖值控制血糖的算法,但糖尿病患者使用最多的独立 CGM 系统却无法做到这一点。通过通常由人工智能支持的算法对测量值进行分析,这在未来应该可以实现。这将为用户提供有关血糖水平进一步变化的重要信息,例如夜间血糖水平。下一代 CGM 系统可采用预测方法。这些系统可以主动预防低血糖或高血糖等血糖事件的发生。Accu-Chek® SmartGuide Predict 应用程序是新型 CGM 系统不可或缺的一部分,它的 Glucose Predict(GP)功能使糖尿病患者拥有了第一款具有预测算法的商用 CGM 系统。它是未来 CGM 系统的特征,不仅能分析过去的血糖值和未来的血糖值,还能利用这些值预测未来的血糖进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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