Steil Garry M, Deiss Dorothee, Shih Judy, Buckingham Bruce, Weinzimer Stuart, Agus Michael S D
Department of Medicine, Children's Hospital Boston , Boston, Massachusetts.
J Diabetes Sci Technol. 2009 Jan;3(1):125-140. doi: 10.1177/193229680900300114.
Studies showing improved outcomes with tight glycemic control in the intensive care unit (ICU) have resulted in a substantial number of new insulin delivery algorithms being proposed. The present study highlights mechanisms used in the better-known approaches, examines what might be critical differences among them, and uses systems theory to characterize the conditions under which each can be expected to perform best. METHODS: Algorithm dose (DeltaI/DeltaG) and step (response to a persistent elevation in glucose) response curves were calculated for written instruction algorithms, developed at the Providence Heart and Vascular Institute (Portland [P] protocol), the University of Washington (UW), and Yale University (Y), together with similar curves for the Glucommander (GM) and proportional integral derivative (PID) computer algorithms. From the simulated curves, different mechanisms used to adjust insulin delivery were identified. RESULTS: All algorithms increased insulin delivery in response to persistent hyperglycemia, but the mechanism used altered the algorithm's sensitivity to glucose, or gain, in the GM, UW, and Y protocols, while leaving it unchanged for the P protocol and PID algorithm. CONCLUSIONS: The increase in insulin delivery in response to persistent hyperglycemia observed with all the algorithms can be expected to bring subjects who respond to insulin to targeted glucose ranges. However, because the PID and P protocols did not alter the insulin delivery response curves, these algorithms can be expected to take longer to achieve target glucose levels in individuals who are insulin resistant and/or are exposed to increased carbohydrate loads (e.g., glucose infusions). By contrast, the GM, UW, and Y algorithms can be expected to adapt to the insulin resistance such that the time to achieve target levels is unchanged if the time for insulin to act does not change. If the insulin resistance is accompanied by a longer time for insulin to act, the UW, Y, and GM algorithms may increase the risk of hypoglycemia. Under these conditions, the longer time required for the PID and P protocols to achieve a target glucose level may be a reasonable trade-off for no increase in the risk of hypoglycemia.
多项研究表明，在重症监护病房（ICU）进行严格的血糖控制可改善治疗效果，这促使人们提出了大量新的胰岛素给药算法。本研究着重介绍了一些知名方法中所采用的机制，探讨了它们之间可能存在的关键差异，并运用系统理论来描述每种算法有望实现最佳性能的条件。方法：计算了普罗维登斯心脏与血管研究所（波特兰[P]方案）、华盛顿大学（UW）和耶鲁大学（Y）制定的书面指导算法的算法剂量（DeltaI/DeltaG）和步长（对持续性血糖升高的反应）响应曲线，同时还计算了Glucommander（GM）和比例积分微分（PID）计算机算法的类似曲线。从模拟曲线中，确定了用于调整胰岛素给药的不同机制。结果：所有算法均会在持续性高血糖时增加胰岛素给药量，但在GM、UW和Y方案中，所采用的机制改变了算法对葡萄糖的敏感性或增益，而P方案和PID算法的敏感性则保持不变。结论：所有算法在持续性高血糖时胰岛素给药量的增加，有望使对胰岛素有反应的患者血糖达到目标范围。然而，由于PID和P方案未改变胰岛素给药响应曲线，对于胰岛素抵抗和/或碳水化合物负荷增加（如葡萄糖输注）的个体，预计这些算法需要更长时间才能达到目标血糖水平。相比之下，如果胰岛素作用时间不变，GM、UW和Y算法有望适应胰岛素抵抗，从而使达到目标水平的时间保持不变。如果胰岛素抵抗伴随着更长的胰岛素作用时间，UW、Y和GM算法可能会增加低血糖风险。在这些情况下，PID和P方案达到目标血糖水平所需的较长时间，可能是不增加低血糖风险的合理权衡。
