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1型糖尿病患者胰岛素治疗调整的决策支持系统

Decision Support Systems for Insulin Treatment Adjustment in People with Type 1 Diabetes.

作者信息

Nimri Revital

机构信息

The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel, E-mail:

出版信息

Pediatr Endocrinol Rev. 2020 Mar;17(Suppl 1):170-182. doi: 10.17458/per.vol17.2020.n.insulintreatmenttype1diabetes.

DOI:10.17458/per.vol17.2020.n.insulintreatmenttype1diabetes
PMID:32208561
Abstract

For people with type 1 diabetes, achieving optimal glycemic control requires use of intensive insulin therapy. To achieve this goal individuals are required to become proficient in accurately determining the appropriate amount of insulin needed to address a variety of situations throughout the day while considering numerous influencing factors. They also need to perform multiple tasks a day such as counting carbohydrates to accurately determine the required premeal bolus. There is also a need to periodically adjust insulin dosing as insulin sensitivity varies considerably over time. Sophisticated advanced technologies are being used by growing numbers of individuals to manage diabetes. However, despite innovations in glucose monitoring technologies and new insulin formulations, many of these individuals are not achieving their glycemic goals. The new technologies provide ample amount of valuable diabetes related data that may complicate even further the insulin dosing decision making for people with diabetes as well as for the health care providers. Mobile health, digital tools and decision support systems can help to increase accurate, timely insulin dosing and insulin titration and holds the potential to improve glycemic control to a wide range of individuals with diabetes. The emerging mobile toolbox for insulin dosing adjustments that will be reviewed in this paper includes insulin management Apps; diverse range of Apps to guide insulin adjustments such as in times of physical activity and eating; data management systems which enable visualization and analysis of insulin and glucose data of various devices; real-time alarms and glucose prediction Apps that help to prevent hypoglycemia and hyperglycemia events; various bolus calculators for meal time dosing; sophisticated decision support algorithms for people using insulin pump, multiple insulin injections and closed loop systems for real-time and retrospective insulin dosing adjustments.

摘要

对于1型糖尿病患者而言,实现最佳血糖控制需要采用强化胰岛素治疗。为实现这一目标,患者需要熟练掌握如何在考虑众多影响因素的情况下,准确确定全天应对各种情况所需的胰岛素剂量。他们还需要每天执行多项任务,如计算碳水化合物含量以准确确定餐前所需的大剂量胰岛素。此外,由于胰岛素敏感性会随时间大幅变化,因此还需要定期调整胰岛素剂量。越来越多的人开始使用先进的技术来管理糖尿病。然而,尽管血糖监测技术和新型胰岛素制剂有所创新,但许多患者仍未实现其血糖目标。这些新技术提供了大量与糖尿病相关的宝贵数据,这可能会使糖尿病患者以及医疗保健人员的胰岛素剂量决策变得更加复杂。移动健康、数字工具和决策支持系统有助于提高胰岛素剂量和滴定的准确性与及时性,并有可能改善广大糖尿病患者的血糖控制。本文将介绍的新兴胰岛素剂量调整移动工具包包括胰岛素管理应用程序;多种用于指导胰岛素调整的应用程序,如在体育活动和进食时;能够可视化和分析各种设备的胰岛素和血糖数据的数据管理系统;有助于预防低血糖和高血糖事件的实时警报和血糖预测应用程序;用于餐时给药的各种大剂量计算器;为使用胰岛素泵、多次胰岛素注射和闭环系统进行实时和回顾性胰岛素剂量调整的患者提供的复杂决策支持算法。

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引用本文的文献

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The effectiveness of digital health technologies for patients with diabetes mellitus: A systematic review.数字健康技术对糖尿病患者的有效性:一项系统综述。
Front Clin Diabetes Healthc. 2022 Oct 24;3:936752. doi: 10.3389/fcdhc.2022.936752. eCollection 2022.
2
Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors.人工智能和连续血糖监测传感器在糖尿病管理中的应用。
Sensors (Basel). 2020 Jul 10;20(14):3870. doi: 10.3390/s20143870.