Predicting Patient Subpopulation Dynamics from Fluctuation Theory

从波动理论预测患者亚群动态

基本信息

批准号：
8663928
负责人：
MICHAEL W DEEM
金额：
$ 37.56万
依托单位：
RICE UNIVERSITY
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：
2011-09-15 至 2015-05-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant):Biological health is not a single, stable fixed point. Rather, health reflects a rich interplay of complex dynamics. Recent observations suggest that erosion of mechanisms that underlie natural physiological complexity may be one of the most significant damaging effects of trauma or illness. To preempt that erosion, there is a critical need for predictive physiology. To date, clinical predictions are based on pattern classification. Echoing predictive meteorology-that is, the use of dense data, high speed computing and repeated application of simple physical law-this project embarks on predictive physiology. This marriage of the mathematics and clinical medicine contains a deeper postulate, the existence of "Newton's Laws for Biology." Modern biology embraces principles of scaling, modularity, and heritability. These principles speak to structure, distance and space. The team believes that there is underlying structure to biological time and observables. With its access to dense data, computational power, and far-from-equilibrium theory, the team will explore specific clinically important contexts. The team will develop, advance, and apply the conceptual framework of fluctuation-dissipation theory to predict the response to standard clinical interventions from the fluctuations that characterize all physiologic time series data. The model intervention is the spontaneous breathing trial (SBT), a frequent procedure in critical care during which mechanical ventilation is briefly suspended while the patient breathes for a period of time without that support. Clinical data from Emory University Hospitals will be used to test these novel far-from-equilibrium predictions for the heart rate and blood pressure responses. As a conservative step toward improving treatment, the team will also predict the decisions of clinicians following SBTs, namely whether groups of patients will be safely be liberated from the ventilator.

描述（由申请人提供）：生物健康不是一个稳定的固定点。相反，健康反映了复杂动态的丰富相互作用。最近的观察结果表明，基于自然生理复杂性的机制的侵蚀可能是创伤或疾病最重要的破坏性影响之一。为了抢占这种侵蚀，预测生理存在迫切需要。迄今为止，临床预测基于模式分类。回应预测性气象 - 即，使用密集数据，高速计算和重复应用简单的物理定律的使用 - 该项目将着手进行预测生理。数学和临床医学的这种婚姻包含了一个更深层次的假设，即“牛顿生物学定律”的存在。现代生物学包含缩放，模块化和遗传力的原则。这些原则说明了结构，距离和空间。该小组认为，生物学时间和可观察到的基本结构。凭借其获得密集数据，计算能力和远程平衡理论的访问，该团队将探索特定的临床重要环境。该团队将开发，进步和应用波动 - 隔离理论的概念框架，以预测从表征所有生理时间序列数据的波动中对标准临床干预的反应。模型干预是自发呼吸试验（SBT），这是重症监护中经常进行的程序，在此期间，机械通气被短暂悬挂，而患者则在没有该支持的情况下呼吸一段时间。埃默里大学医院的临床数据将用于测试这些新颖的远程平衡预测，以确定心率和血压反应。作为改善治疗的保守步骤，该团队还将预测SBT后临床医生的决定，即是否将安全地从呼吸机中解放出一组患者。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Hierarchy in gene expression is predictive of risk, progression, and outcome in adult acute myeloid leukemia.

DOI：
10.1088/1478-3975/12/1/016016
发表时间：
2015-02-16
期刊：
Physical biology
影响因子：
2
作者：
Tripathi S;Deem MW
通讯作者：
Deem MW

Evolution: life has evolved to evolve: comment on "How life changes itself: the Read-Write (RW) genome" by James Shapiro.

DOI：
10.1016/j.plrev.2013.07.010
发表时间：
2013-09
期刊：
PHYSICS OF LIFE REVIEWS
影响因子：
11.7
作者：
Deem, Michael W.
通讯作者：
Deem, Michael W.

Prediction of heart rate response to conclusion of the spontaneous breathing trial by fluctuation dissipation theory.

DOI：
10.1088/1478-3975/10/1/016006
发表时间：
2013-02
期刊：
Physical biology
影响因子：
2
作者：
Chen M;Niestemski LR;Prevost R;McRae M;Cholleti S;Najarro G;Buchman TG;Deem MW
通讯作者：
Deem MW

Quasispecies theory for evolution of modularity.