Revert Ana, Rossetti Paolo, Calm Remei, Vehí Josep, Bondia Jorge
Instituto Universitario de Automática e Informática Industrial, Universidad Politécnica de Valencia, Camino de Vera s/n, Valencia, Spain.
J Diabetes Sci Technol. 2010 Nov 1;4(6):1424-37. doi: 10.1177/193229681000400617.
Achieving good postprandial glycemic control, without triggering hypoglycemia events, is a challenge of treatment strategies for type 1 diabetes subjects. Continuous subcutaneous insulin infusion, the gold standard of therapy, is based on heuristic adjustments of both basal and prandial insulin. Some tools, such as bolus calculators, are available to aid patients in selecting a meal-related insulin dose. However, they are still based on empiric parameters such as the insulin-to-carbohydrate ratio and on the physicians' and patients' ability to fit bolus mode to meal composition.
In this article, a nonheuristic method for assessment of prandial insulin administration is presented and evaluated. An algorithm based on set inversion via interval analysis is used to coordinate basal and bolus insulin infusions to deal with postprandial glucose excursions. The evaluation is carried out through an in silico study using the 30 virtual patients available in the educational version of the Food and Drug Administration-accepted University of Virginia simulator. Results obtained using the standard bolus strategy and different coordinated basal-bolus solutions provided by the algorithm are compared.
Coordinated basal-bolus solutions improve postprandial glucose performance in most cases, mainly in terms of reducing hypoglycemia risk, but also increasing the percentage of time in normoglycemia. Moreover, glycemic variability is reduced considerably by using these innovative solutions.
The algorithm presented here is a robust nonheuristic alternative to deal with postprandial glycemic control. It is shown as a powerful tool that could be integrated in future smart insulin pumps.
在不引发低血糖事件的情况下实现良好的餐后血糖控制,是1型糖尿病患者治疗策略面临的一项挑战。持续皮下胰岛素输注作为治疗的金标准,是基于对基础胰岛素和餐时胰岛素进行启发式调整。一些工具,如大剂量计算器,可帮助患者选择与进餐相关的胰岛素剂量。然而,它们仍基于胰岛素与碳水化合物比例等经验参数,以及医生和患者使大剂量模式适应饮食成分的能力。
本文介绍并评估了一种用于评估餐时胰岛素给药的非启发式方法。一种基于区间分析的集反演算法用于协调基础胰岛素和大剂量胰岛素输注,以应对餐后血糖波动。通过使用美国食品药品监督管理局认可的弗吉尼亚大学模拟器教育版中提供的30名虚拟患者进行计算机模拟研究来进行评估。比较使用标准大剂量策略和该算法提供的不同协调基础-大剂量方案所获得的结果。
在大多数情况下,协调基础-大剂量方案可改善餐后血糖表现,主要体现在降低低血糖风险方面,同时也增加了血糖正常的时间百分比。此外,使用这些创新方案可显著降低血糖变异性。
本文提出的算法是一种用于处理餐后血糖控制的强大的非启发式替代方法。它被证明是一种可集成到未来智能胰岛素泵中的强大工具。