DYNAMIC RISK MEASURES FOR SEVERE HYPOGLYCEMIA

描述：在胰岛素依赖型糖尿病患者中 严重低血糖（SH-木僵/无意识）是由许多 动态相互作用的生物和行为因素，包括，但 不限于：未能进行实质性的反调节， 血糖（BG）正常化治疗，低血糖无意识。 的 SH的发生是一个随时间推移的平稳过程-SH的历史和/或 频繁的低血糖读数之后是未来的SH。 理解极端 血糖波动作为一个过程，在一个特定的时间框架导致我们的 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的讨论， 生物计时表明，经过一些修改，研究人员的 目前的数据收集提供了一个理想的机会， 风险措施的SH涉及的时间之间的关系， 胰岛素注射、饮食和运动的自我护理行为 低血糖的表现。 同样，调查人员将在独特的 位置开发行为恶化的动态模型作为BG 福尔斯和脑电图改变。 第一阶段将涉及开发这些 模型，随后的计算方法，算法和软件。 研究人员最近得到资助， 在野外和实验室中对I型糖尿病成年患者进行比较， 糖尿病患者近期有或没有多发性SH病史。 的 目的是确定哪些生物、心理和行为因素 区分这两个群体。 在第2A阶段，他们将修改他们的 现场数据采集，以检验和验证两个动态模型的SH 在第一阶段开发。在第2B阶段，驾驶时间序列分析 行为和脑电图数据，在研究人员的实验室研究中收集 在正常血糖诱导的低血糖情况下进行。 这项拟议的研究将利用这些独特的机会， 支持必要的人员1）开发这种动态模型， 后续的数据分析方法、算法和软件，以及2）测试 并用真实的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.