Model-based decision support for tight glucose control without hypoglycemia
基于模型的决策支持,可严格控制血糖而不会发生低血糖
基本信息
- 批准号:8176486
- 负责人:
- 金额:$ 20.48万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-08-01 至 2013-07-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAlgorithmsAnatomyArtificial PancreasBlood GlucoseCharacteristicsClinicalClinical DataClinical TrialsComputer SimulationCritical CareCritical IllnessDataData SetDecision Support SystemsDevelopmentDevicesDoseElectronicsEngineeringEventFrequenciesGlucagonGlucoseGoalsHyperglycemiaHypoglycemiaIncidenceIndividualInformation SystemsInpatientsInsulinInterventionLiteratureLogisticsMeasurementMeasuresMedicalModelingNotificationNursesOperative Surgical ProceduresOutcomePatientsPhysiologicalPhysiologyPopulationProcessRandomized Clinical TrialsRecommendationRecoveryRegulationResearchScienceStructureSystemTechnologyTestingTimeValidationVariantWorkloadbaseblood glucose regulationcohortdata modelingdesignimprovedmathematical modelmeetingsminimally invasivemodel developmentpredictive modelingpreventprogramssensortooltreatment strategy
项目摘要
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.
描述(由申请人提供):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,但关于其总体益处仍然存在很多争议;部分原因是低血糖或低血糖的发生率不可接受。用于重症监护中血糖控制的决策支持系统,与人工胰腺非常相似,由三个基本组件组成:(1) 血糖测量设备,(2) 解释该测量结果并推荐治疗策略的算法,以及 (3 )实施该策略的输送装置,将胰岛素、葡萄糖或一些其他药剂(例如胰高血糖素)输送给患者。该提案将利用系统工程工具对以下问题提供有力的答案:鉴于微创血糖测量设备的特点,在避免低血糖的同时可实现的最严格的血糖控制是什么,以及实现这种控制的策略是什么?我们建议使用接受胰岛素的危重患者的非常大的多中心数据集,旨在(1)校准和验证葡萄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变化。然后,这样的模型将用于(3)设计和提供为患者量身定制的决策支持系统,以便携式界面的形式,预先警告临床医生潜在的低血糖发作,并建议注射胰岛素或葡萄糖剂量。该提案的最终目标是为危重患者严格血糖控制的随机临床试验配备所有必要的工具,同时完全避免低血糖发作。预计该提案的成功完成将产生巨大的转化影响,并对系统工程科学做出贡献,特别是根据患者的特定需求定制复杂的算法。
公共卫生相关性:重症外科和内科患者在严格血糖控制下表现出更好的生存率,但在临床试验人群中,严格血糖控制往往会导致低血糖(低血糖)发作率不可接受,需要进一步治疗。拟议的研究计划将开发一种基于交互式模型的决策支持系统,该系统将预先警告临床医生潜在的低血糖发作,并建议胰岛素或葡萄糖的给药剂量。该提案的最终目标是为危重患者严格血糖控制的随机临床试验配备所有必要的工具,同时通过我们的决策支持系统完全避免低血糖发作。
项目成果
期刊论文数量(0)
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Gilles Clermont其他文献
Gilles Clermont的其他文献
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