Model-based decision support for tight glucose control without hypoglycemia

描述(申请人提供)：虽然严格的血糖控制已被证明可以改善一些重症监护患者的预后，但关于其总体益处的许多争议仍然存在；部分原因是低血糖或低血糖的发生率不可接受。重症监护中的血糖控制决策支持系统就像人工胰腺一样，由三个基本组件组成：(1)血糖测量设备，(2)解释该测量并推荐治疗策略的算法，以及(3)实施该策略的输送设备，向患者输送胰岛素、葡萄糖或其他制剂(例如，胰高血糖素)。这项提案将使用系统工程工具为以下问题提供强有力的答案：鉴于微创血糖测量设备的特点，在避免低血糖的同时可以实现的最严格的血糖控制是什么，实现这种控制的策略是什么？我们建议使用一个非常大的接受胰岛素治疗的危重患者的多中心数据集，旨在(1)校准和验证血糖和胰岛素动力学的数学模型，以及(2)表征模型参数中体现的患者之间的差异。这样的模型将被用来(3)设计和提供患者定制的决策支持系统，以便携式界面的形式，可以预先警告临床医生潜在的低血糖发作，并建议使用胰岛素或葡萄糖剂量。这项建议的最终目标是为危重患者严格控制血糖的随机临床试验提供所有必要的工具，同时完全避免低血糖发作。预计这项提议的成功完成将产生很高的翻译影响，并对系统工程科学做出贡献，特别是在为患者特定需求定制复杂算法方面。 公共卫生相关性：重症外科和内科患者在严格控制血糖的情况下表现出更好的存活率，但临床试验人群中严格的血糖控制通常是在需要进一步治疗的低血糖(低血糖)发作的不可接受的比率下实现的。拟议的研究计划将开发一个基于模型的交互式决策支持系统，该系统将预先警告临床医生潜在的低血糖发作，并建议使用胰岛素或葡萄糖剂量。这项建议的最终目标是为危重患者严格控制血糖的随机临床试验提供所有必要的工具，同时通过我们的决策支持系统完全避免低血糖发作。

DESCRIPTION (provided by applicant): While tight glucose control has been shown to improve the outcomes of some critical care patients, much controversy regarding its overall benefit persists; in part due an unacceptable incidence of hypoglycemia, or low blood sugar. A decision support system for glucose control in critical care, much like an artificial pancreas, is comprised of three essential components: (1) a glucose measuring device, (2) an algorithm that interprets this measurement and recommends a treatment strategy, and (3) a delivery device that implements this strategy, delivering insulin, glucose, or some other agent (e.g., glucagon) to a patient. This proposal will use systems engineering tools to provide a robust answer to the following questions: given the characteristics of a minimally invasive glucose measuring device, what is the tightest glucose control achievable while avoiding hypoglycemia, and what is the strategy to achieve this control? We propose to use a very large multi-center dataset of critically ill patients receiving insulin, aiming to (1) calibrate and validate a mathematical model of glucose and insulin dynamics and (2) characterize between-patient variations as embodied in model parameters. Such a model will then be used to (3) design and deliver a patient-tailored decision support system, in the form of a portable interface that would forewarn clinical practitioners of potential hypoglycemic episodes and recommend insulin or dextrose dose administration. The ultimate goal of this proposal is to put all necessary tools in place for a randomized clinical trial of tight glucose control in critically ill patients, while completely avoiding episodes of hypoglycemia. It is expected that a successful completion of this proposal will have high translational impact and contribute to systems engineering science, specifically in the tailoring of sophisticated algorithms to patient- specific needs. PUBLIC HEALTH RELEVANCE: Critically ill surgical and medical patients demonstrate better survival with tight glucose control, but tight glucose control in clinical trial populations has often been achieved with an unacceptable rate of hypoglycemic (low blood sugar) episodes requiring further treatment. The research program proposed will develop an interactive model-based Decision Support System that would forewarn clinical practitioners of potential hypoglycemic episodes and recommend insulin or dextrose dose administration. The ultimate goal of this proposal is to put all necessary tools in place for a randomized clinical trial of tight glucose control in critically ill patients, while completely avoiding episodes of hypoglycemia via our decision support system.