EAGER: Insulin Delivery for Diabetes Management in the Intensive Care Unit as a Feedback Control Problem

0938288-灰色糖尿病影响了超过30%的住院患者。目前，在医院环境中监测血糖的管理方案过于简单，而且往往无效。一个由一名糖尿病专家/内分泌学家和一名控制工程师组成的跨学科团队寻求改善重症监护环境中患者的血糖水平调节，特别是那些术后在那里的患者。目前的胰岛素剂量方案实际上是血糖水平的反馈控制算法，但对它们进行分析的工作很少。这项提议的中心主题是反馈控制技术可以导致更好的执行和更安全的胰岛素剂量方案。PI将建立和验证血糖对静脉注射胰岛素输注速度的动态模型，该模型适用于ICU中的各种患者。该模型将基于患者数据，并将考虑重要的扰动因素，如葡萄糖输注速度、营养(口服和静脉注射)、胰岛素抵抗或致敏药物、患者体温和进入ICU时的临床严重程度。他们将利用所获得的动态模型对现有的胰岛素注射方案进行广泛的闭环控制分析，重点研究它们的标称响应以及它们对广泛的模型参数变化的响应。在上述模型建立和闭环控制分析的基础上，PI将对现有协议提出改进建议，包括全球医院采用的所谓纸质协议，这些协议反映了优越的控制法。智力优势：尚未发表各种协议在达到目标的速度和一致性或低血糖频率等因素方面的比较。也没有系统地研究现有方案对患者变化的稳健性，如营养(特别是碳水化合物)、变化的血管增压剂、类固醇和其他药物。已公布的方案声称46%至69%的血糖水平达到了目标。在几项研究中，低血糖的发生率从0.3%到15%不等。一项能够使血糖水平迅速达到目标、对胰岛素抵抗/敏感性的变化做出适当和及时反应的方案，以及解决膳食和药物制度问题的方案，将对患者护理产生重大影响。通过自动记录胰岛素敏感性的变化来预防低血糖，可以解决对低血糖水平的恐惧。对于无反应的镇静剂患者，这将有助于将对低血糖的担忧降至最低，低血糖是使用胰岛素的最大障碍。最后，除了解决所有上述问题外，理想的方案是允许医疗保健提供者为不同ICU环境(内科、外科、心脏或创伤烧伤)的患者测定不同的血糖范围和敏感性，最大限度地减少用餐或输液中含有葡萄糖的血糖波动，并防止低血糖。这里提出的工作将使我们朝着这一目标迈出重要的一步。更广泛的影响：这项研究制定的一般原则应该适用于糖尿病的门诊管理，其范围是巨大的，以及包括麻醉和疼痛管理在内的各种其他环境。

0938288-GrizzleDiabetes impacts more than 30% of hospitalized patients. Currently, management protocols for monitoring blood glucose in the hospital setting are overly simplistic and often ineffective. An interdisciplinary team consisting of a diabetologist/endocrinologist and a control engineer seeks to improve the regulation of blood glucose levels in patients in the intensive care setting, especially those who are there postoperatively. The current insulin dosing protocols are actually feedback control algorithms for blood glucose levels, but little work has been done to analyze them as such. The central theme of this proposal is that feedback control techniques can lead to better performing and safer insulin dosing protocols. The PIs will build and validate a dynamic model of blood glucose response to intravenous insulin infusion rate that is adapted to various classes of patients seen in the ICU. The model will be based on patient data and will account for important perturbing factors such as dextrose infusion rates, nutrition (oral and parenteral), insulin resistant or sensitizing drugs, patient body temperature and clinical severity when entering the ICU. They will perform an extensive control analysis of existing insulin infusion protocols in closed-loop with the obtained dynamic model, with an emphasis on studying their nominal response as well as their response to a wide range of model parameter variations. On the basis of the model building and closed-loop control analysis performed above, the PIs will propose improvements to the existing protocols, including the so-called paper protocols that are employed in hospitals worldwide, which reflect a superior control law.Intellectual Merit: There have been no published comparisons of various protocols for such factors as rapidity and consistency of reaching targets or frequency of hypoglycemia. Neither has there been a systematic study of robustness of the existing protocols to patient variations such as nutrition (especially carbohydrates), changing vasopressors, steroids and other drugs. Published protocols claim between 46 to 69 % of blood glucose levels reach goal. Hypoglycemia rates can range from 0.3 to 15 % in several studies. A protocol that could bring blood glucose levels to goal quickly, respond appropriately and in a timely manner to changing insulin resistance/sensitivity, and address meals and drug regimes would have a significant impact on patient care. Preempting hypoglycemia by automatically noting the changing insulin sensitivity could address the fear of low blood glucose levels. In an unresponsive sedated patient, this would help minimize the concern for hypoglycemia which is the biggest barrier to the use of insulin. Lastly the ideal protocol in addition to addressing all the above issues would allow the health care provider to titrate a different blood glucose range and sensitivity for patients in different ICU settings (medical, surgical, cardiac, or trauma burn), minimize blood glucose swings with meals or infusions containing dextrose, and prevent hypoglycemia. The work proposed here will take us a significant step toward this goal.Broader Impacts: The general principles developed by this research should be transferable to the outpatient management of diabetes where the scope is of an enormous magnitude and a variety of other settings, including anesthesia and pain management.