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

EAGER：重症监护病房糖尿病管理中的胰岛素输送作为反馈控制问题

• 批准号: 0938288
• 负责人: Jessy Grizzle
• 金额: $ 14.95万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0938288&HistoricalAwards=false
• 关键词: EAGER; Insulin; Delivery; Diabetes; Management

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.

0938288-GrizzleDiabetes影响超过30%的住院患者。目前，用于在医院环境中监测血糖的管理协议过于简单并且通常无效。由糖尿病专家/内分泌专家和控制工程师组成的跨学科团队旨在改善重症监护环境中患者的血糖水平调节，特别是那些术后患者。目前的胰岛素给药方案实际上是血糖水平的反馈控制算法，但几乎没有工作来分析它们。该提案的中心主题是反馈控制技术可以导致更好的性能和更安全的胰岛素给药方案。PI将建立并验证血糖对静脉胰岛素输注速率的动态响应模型，该模型适用于ICU中的各类患者。该模型将基于患者数据，并将考虑重要的干扰因素，如葡萄糖输注速率、营养（口服和肠外）、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。他们将使用获得的动态模型对闭环中现有的胰岛素输注方案进行广泛的控制分析，重点是研究其标称响应以及对广泛的模型参数变化的响应。在上述模型构建和闭环控制分析的基础上，PI将对现有协议提出改进建议，包括在全球医院中使用的所谓纸质协议，其反映了上级控制律。智力优点：尚未发表各种协议对达到目标或低血糖频率的快速性和一致性等因素的比较。也没有对现有方案对患者变化（如营养（特别是碳水化合物）、改变血管加压药、类固醇和其他药物）的稳健性进行系统研究。已发表的方案声称46%至69%的血糖水平达到目标。在几项研究中，低血糖率范围为0.3%至15%。一个可以使血糖水平快速达到目标，适当及时地应对胰岛素抵抗/敏感性变化，并解决膳食和药物方案的方案将对患者护理产生重大影响。通过自动注意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。在无反应的镇静患者中，这将有助于最大限度地减少对低血糖的担忧，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之外，理想的方案还将允许医疗保健提供者针对不同ICU环境（内科、外科、心脏或创伤烧伤）中的患者滴定不同的血糖范围和灵敏度，最小化含葡萄糖的膳食或输注的血糖波动，并防止低血糖。更广泛的影响：本研究所提出的一般原则应可转移到糖尿病的门诊管理，其范围是巨大的，以及各种其他设置，包括麻醉和疼痛管理。