一个基于生理学的数字双胞胎用于酒精消费 - - 预测现实生活中的饮酒反应和长期的血PET
Henrik Podéus1, Christian Simonsson1,2, Patrik Nasr3,4
1Department of Biomedical Engineering (IMT), Linköping University, Linköping, Sweden.
NPJ digital medicine
|May 3, 2024
概括
一个新的数学模型模拟了现实生活中的酒精消费,将饮酒习惯与长期生物标志物如酸丁乙醇 (PEth) 联系起来. 这种数字双胞胎技术有助于个性化健康和减少危险的饮酒行为.
科学领域:
- 生物医学工程 生物医学工程
- 计算毒理学计算毒理学
- 数字健康数字健康
背景情况:
- 酒精消费是可预防死亡和发病的主要原因之一.
- 电子健康应用程序在减少有害饮酒方面表现有前途.
- 现有的数学模型缺乏现实世界的适用性,并且无法整合临床生物标志物.
研究的目的:
- 开发一种新的数学模型,在现实生活中模拟饮酒情况.
- 为了将短期的酒精摄入与长期的临床标志物联系起来,特别是脂乙醇 (PEth).
- 创建一个个性化的,基于生理学的数字双胞胎来评估酒精消费.
主要方法:
- 开发一个包含食物和饮料的数学模型.
- 酒精消费与脂乙醇 (PEth) 动态的整合.
- 个性化模型使用人体测量数据创建数字双胞胎.
- 使用估计和独立数据集 (χ2-test) 进行验证.
主要成果:
- 该模型准确地描述了估计数据 (187.0 < Tχ2 = 226.4) 和验证数据 (70.8 < Tχ2 = 93.5).
- 数字双胞胎成功地将短期的酒精摄入量与长期的PEth水平联系起来.
- 从PEth水平来确定患者的酒精消耗的新方法.
结论:
- 开发的模型和数字双胞胎提供了一个基于生理学的方法来模拟酒精消费.
- 该工具可以对酒精摄入量进行个性化评估和监测,将行为与临床生物标志物联系起来.
- 将其集成到电子健康应用程序中,为个人和临床医生提供了宝贵的资源,以减轻风险饮酒.
相关概念视频
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