DYNAMIC RISK MEASURES FOR SEVERE HYPOGLYCEMIA

描述：在患有胰岛素依赖型糖尿病的个体中 严重低血糖(SH--昏迷/昏迷)是由一些 动态相互作用的生物和行为因素，包括，但是 不限于：荷尔蒙反调节失败，密集 治疗后血糖(BG)正常化，低血糖意识不足。这个 SH的发生是一个平稳的时间过程--SH和/或 频繁的低BG读数之后是未来的SH。了解极端 作为特定时间范围内的一个过程的BG波动将我们引向 本申请中提出的动态风险模型。 最近与国家科学基金会中心就 生物计时表明，经过一些修改，研究人员的 当前的数据收集为开发动态数据提供了理想的机会 SH的风险度量涉及到时间与时间的关系 胰岛素注射、饮食和锻炼的自我护理行为 在低BG下的性能。同样，调查员将在唯一的 开发行为恶化的动态模型的立场 摔倒和脑电波改变。第一阶段将涉及开发这些 模型、后续计算方法、算法和软件。 调查人员最近得到了资助，进行了横截面 I型成人在野外和实验室的比较 有或没有近期多发性SH病史的糖尿病患者。这个 意图是确定哪些生物、心理和行为因素 区分这两组人。在阶段2A期间，他们将修改其 现场数据采集，以检验和验证两个SH动态模型 在阶段I期间开发在阶段2B期间，驾驶的时间序列分析 在研究人员的实验室研究中收集的行为和脑电数据 在正常血糖诱导的低血糖条件下，将进行。 这项拟议的研究将利用这些独特的机会 支持1)开发此类动态模型所需的人员以及 后续数据分析方法、算法和软件，以及2)测试 并用实际数据对模型进行了验证。

DESCRIPTION: Among individuals with insulin dependent diabetes mellitus severe hypoglycemia (SH--stupor/unconsciousness) is triggered by a number of dynamically interacting biological and behavioral factors, that include, but are not limited to: failure to hormonally counterregulate, intensive therapy to normalize blood glucose (BG), hypoglycemia unawareness. The occurrence of SH is a stationary over time process--a history of SH and/or frequent low BG readings are followed by future SH. Understanding extreme BG fluctuations as a process in a specific time frame leads us to the dynamic risk models proposed in this application. Recent discussions with the National Science Foundation Center for Biological Timing suggest that, with some modifications, the investigators' current data collection provides an ideal opportunity to develop dynamic risk measures of SH involving the relationships between timing of the self-care behaviors of insulin injection, food consumption and exercise performance with low BG. Similarly, the investigator would be in the unique position to develop a dynamic model of the deterioration in behavior as BG falls and EEG changes. Phase I would involve the development of these models, subsequent computational methods, algorithms and software. The investigators have recently been funded to perform cross-sectional comparisons, both in the field and laboratory, of adults with Type I diabetes who either do or do not have a recent history of multiple SH. The intent is to determine what biological, psychological and behavioral factors differentiate these two groups. During Phase 2A they would modify their field data collection in order to test and verify two dynamic models of SH developed during Phase I. During Phase 2B, time series analyses of driving behavior and EEG data, collected in the investigators' laboratory study under conditions of euglycemia-induced hypoglycemia, will be performed. This proposed study would take advantage of these unique opportunities by supporting the personnel necessary to 1) develop such dynamic models and subsequent data analysis methods, algorithms and software, and 2) to test and validate the models with real data.