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Predicting Glucose Values: A New Era for Continuous Glucose Monitoring.
Kulzer, Bernhard; Heinemann, Lutz.
Afiliación
  • Kulzer B; Research Institute Diabetes Academy Mergentheim, Bad Mergentheim, Germany.
  • Heinemann L; Diabetes Center Mergentheim, Bad Mergentheim, Germany.
J Diabetes Sci Technol ; 18(5): 1000-1003, 2024 Sep.
Article en En | MEDLINE | ID: mdl-39158996
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Glucemia / Algoritmos / Automonitorización de la Glucosa Sanguínea Límite: Humans Idioma: En Revista: J Diabetes Sci Technol Asunto de la revista: ENDOCRINOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Glucemia / Algoritmos / Automonitorización de la Glucosa Sanguínea Límite: Humans Idioma: En Revista: J Diabetes Sci Technol Asunto de la revista: ENDOCRINOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Estados Unidos