León-Vargas Fabian, Calm Remei, Bondia Jorge, Vehí Josep
Institute of Informatics and Applications, University of Girona, Girona, Spain.
J Diabetes Sci Technol. 2012 Nov 1;6(6):1420-8. doi: 10.1177/193229681200600623.
Set-inversion-based prandial insulin delivery is a new model-based bolus advisor for postprandial glucose control in type 1 diabetes mellitus (T1DM). It automatically coordinates the values of basal-bolus insulin to be infused during the postprandial period so as to achieve some predefined control objectives. However, the method requires an excessive computation time to compute the solution set of feasible insulin profiles, which impedes its integration into an insulin pump. In this work, a new algorithm is presented, which reduces computation time significantly and enables the integration of this new bolus advisor into current processing features of smart insulin pumps.
A new strategy was implemented that focused on finding the combined basal-bolus solution of interest rather than an extensive search of the feasible set of solutions. Analysis of interval simulations, inclusion of physiological assumptions, and search domain contractions were used. Data from six real patients with T1DM were used to compare the performance between the optimized and the conventional computations.
In all cases, the optimized version yielded the basal-bolus combination recommended by the conventional method and in only 0.032% of the computation time. Simulations show that the mean number of iterations for the optimized computation requires approximately 3.59 s at 20 MHz processing power, in line with current features of smart pumps.
A computationally efficient method for basal-bolus coordination in postprandial glucose control has been presented and tested. The results indicate that an embedded algorithm within smart insulin pumps is now feasible. Nonetheless, we acknowledge that a clinical trial will be needed in order to justify this claim.
基于集合反演的餐时胰岛素输注是一种新型的基于模型的大剂量胰岛素输注建议器,用于1型糖尿病(T1DM)患者的餐后血糖控制。它能自动协调餐后期间基础-餐时胰岛素输注量,以实现一些预定义的控制目标。然而,该方法计算可行胰岛素输注方案解集所需的计算时间过长,这阻碍了它与胰岛素泵的集成。在这项研究中,我们提出了一种新算法,该算法显著减少了计算时间,并能将这种新型大剂量胰岛素输注建议器集成到智能胰岛素泵的当前处理功能中。
实施了一种新策略,重点是找到感兴趣的基础-餐时联合解决方案,而不是广泛搜索可行的解决方案集。采用了区间模拟分析、纳入生理假设和搜索域收缩等方法。使用6例T1DM真实患者的数据比较优化计算和传统计算之间的性能。
在所有情况下,优化版本都能得出传统方法推荐的基础-餐时组合,且计算时间仅为传统方法的0.032%。模拟显示,在20 MHz处理能力下,优化计算的平均迭代次数约为3.59秒,符合智能泵的当前功能。
我们提出并测试了一种在餐后血糖控制中进行基础-餐时协调的高效计算方法。结果表明,在智能胰岛素泵中嵌入算法现在是可行的。尽管如此,我们承认需要进行临床试验来证实这一说法。