Statistical inference for continuous variables and critical illness monitoring

连续变量和危重疾病监测的统计推断

• 批准号: 2576568
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2576568
• 关键词: Statistical; inference; continuous; variables; critical

Critical illness is defined by the evidence of acute organ failure needing monitoring and/or support, either with drugs or machines. Close monitoring inevitably generates large amounts of data from multiple sources. These data are used to make clinical decisions by the bedside. Data are generated at different frequencies e.g. vital signs such as heart rate and oxygen levels may be monitored continuously at the bedside. Blood gas analysis may be undertaken every 4-6 hours, other blood tests may be performed 12-24 hourly. Many of the variables are inter-connected and treatments may have predictable effects on some of the variables. We propose the use of Bayesian multi-level modelling and Bayesian networks using real patient data (>50000 patients from UCLH and >5000 patients from Great Ormond Street Hospital) to generate continuous estimations of intermittently sampled values and model for the missingness mechanism. These wil be applied to modelling the pH changes continuously and how haemoglobin binds to oxygen, based on data from the ventilator, vital signs, drug used and blood tests. The work will be part of the UCL CHIMERA hub (www.ucl.ac.uk/chimera) which uses a multi-disciplinary approach to enhance the understanding of human physiology using real patient data.Research Areas:1. Statistics and applied probability 2. Operational Research

危重病的定义是急性器官衰竭的证据，需要监测和/或支持，无论是药物或机器。密切监测不可避免地会产生来自多个来源的大量数据。这些数据用于在床边做出临床决策。以不同的频率生成数据，例如，可以在床边连续监测诸如心率和氧气水平的生命体征。血气分析可以每4-6小时进行一次，其他血液检查可以每12-24小时进行一次。许多变量是相互关联的，治疗可能对某些变量产生可预测的影响。我们建议使用贝叶斯多层次建模和贝叶斯网络，使用真实的患者数据（>50000例患者从UCLH和>5000例患者从大奥蒙德街医院），以产生连续的估计间歇采样值和模型的缺失机制。根据呼吸机、生命体征、使用的药物和血液测试的数据，这些将被应用于模拟pH值的连续变化以及血红蛋白如何与氧气结合。这项工作将是UCL CHIMERA中心（www.ucl.ac.uk/chimera）的一部分，该中心采用多学科方法，利用真实的患者数据增强对人类生理学的理解。统计学和应用概率2。运筹学