Using Patient Simulation to Optimize Hospital Insulin Infusion in Cardiac Surgery

使用患者模拟优化心脏手术中的医院胰岛素输注

• 批准号: 8624190
• 负责人: ANTHONY L MCCALL
• 金额: $ 23.2万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-05-15 至 2016-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8624190
• 关键词: Address; Adopted; Algorithms; Biomedical Engineering; Blood Glucose; Cardiac Surgery procedures; Cardiovascular Surgical Procedures; Clinical; Clinical Research; Clinical Trials; Computer Simulation; Computers; Critical Care; Data; Data Analyses; Data Set; Dose; Endocrine; Etiology; Event; Glucose; Goals; Guidelines; Hospital Mortality; Hospitals; Hyperglycemia; Hypoglycemia; Incidence; Infection; Infusion procedures; Inpatients; Insulin; Intensive Care Units; Methodology; Methods; Morbidity - disease rate; Multicenter Studies; Operative Surgical Procedures; Outcome; Paper; Patient Simulation; Patients; Physiology; Population; Postoperative Period; Process; Protocols documentation; Recommendation; Reporting; Societies; Stress; System; Testing; Time; Treatment Protocols; Wound Healing; base; blood glucose regulation; cost; design; feeding; glucose metabolism; glycemic control; improved; innovation; insulin sensitivity; models and simulation; mortality; novel; operation; patient population; prospective; public health relevance; response; therapy design; virtual

Project Summary / Abstract Stress hyperglycemia and associated glycemic variability are common in critical care and have been found to contribute to infection, slow wound healing, and short and long-term mortality. Early clinical trials utilizing intensive insulin therapy to maintain Tight Glycemic Control (TGC) in surgical patients, resulted in a 34% decrease in in-hospital mortality and comparable decreases in morbidity. Consequently, many hospitals adopted aggressive inpatient glycemic targets for their Intensive Care Unit (ICU) patients. However, in subsequent studies the benefits of TGC were less apparent. Many factors contribute to the variability of reported TGC outcomes, including (i) the insulin therapy protocols themselves, which offer surprisingly divergent insulin dose recommendations under similar circumstances, (ii) the etiology of extreme BG variability in diverse patient populations, and (iii) the accuracy of the methods used to assess BG concentration and inform the insulin therapies. The main obstacle to developing optimized insulin therapy protocols is that clinical trials are expensive, time consuming, and cannot compare glycemic outcomes for different protocols in identical patients. To overcome these problems we have proposed and partially validated an innovative Bioengineering Insulin Therapy Design Methodology (BITDM) based on (i) characterization of the population-specific variability in patients' insulin sensitivity parameters in a well validated simulation model of glucose metabolism; (ii) creation of a computer-based ICU BG Simulator centered around a virtual subject population that replicates the responses of the real patient population to different insulin therapies; and (iii) simulator-based in silico design and optimization of TGC algorithms. The central hypothesis of this proposal is that BITDM can provide an accurate means of evaluating, comparing, and optimizing insulin protocols that safely improves TGC in specific patient populations, in this instance cardiovascular surgery (CVS) patients. Accordingly, the following specific aims are proposed: Aim 1. Apply BITDM to the distinct physiology of postoperative CVS patients. Aim 2. Establish the efficacy of BITDM-based insulin protocol optimization within U.Va.'s cardiothoracic ICU. Once established, BITDM will allow for different glycemic management strategies to be tested, compared and optimized within a common set of in silico patients at a fraction of the cost and time it will take to perform a clinical trial. If successful, this study will allow us to start addressing our long-term goal - developing a simulator-based bioengineering methodology for optimization of insulin treatment that safely achieves TGC and allows for improved outcomes.

项目总结/摘要 应激性高血糖和相关的血糖变异性在重症监护中很常见， 导致感染、伤口愈合缓慢以及短期和长期死亡。早期临床试验 使用强化胰岛素治疗来维持手术患者的严格血糖控制（TGC），导致 住院死亡率降低34%，发病率也相应降低。因此，许多 医院对他们的重症监护室（ICU）患者采用了积极的住院血糖目标。 然而，在随后的研究中，TGC的益处不那么明显。许多因素促成了 报告的TGC结局的变异性，包括（i）胰岛素治疗方案本身， 在类似情况下令人惊讶的不同胰岛素剂量建议，（ii） 不同患者人群的极端BG变异性，以及（iii）用于评估的方法的准确性 血糖浓度并告知胰岛素治疗。开发优化胰岛素的主要障碍 治疗方案的一个缺点是，临床试验昂贵、耗时， 在相同患者中的不同方案的结果。为了克服这些问题，我们提出了 部分验证了一种创新的生物工程胰岛素治疗设计方法（BITDM），该方法基于（i） 井中患者胰岛素敏感性参数的人群特异性变异性的表征 葡萄糖代谢的验证模拟模型;（ii）创建基于计算机的ICU BG模拟器 该虚拟受试者群体复制了真实的患者群体的反应， 不同的胰岛素治疗;和（iii）基于模拟器的计算机设计和TGC算法的优化。 该建议的核心假设是BITDM可以提供一种准确的评估方法， 比较和优化胰岛素方案，安全地改善特定患者人群的TGC， 例如心血管手术（CVS）患者。因此，提出了以下具体目标： 目标1.将BITDM应用于术后CVS患者的不同生理。 目标2.确定弗吉尼亚大学内基于BITDM的胰岛素方案优化的有效性。的 心胸重症监护室 一旦建立，BITDM将允许不同的血糖管理策略进行测试， 并在一组常见的计算机模拟患者中进行优化，所需的成本和时间仅为 进行临床试验。如果成功，这项研究将使我们能够开始实现我们的长期目标- 开发一种基于模拟器的生物工程方法，用于优化胰岛素治疗， 实现TGC并允许改善结果。