An adaptive and generalizable closed-loop system for control of medically induced coma and other states of anesthesia
An adaptive and generalizable closed-loop system for control of medically induced coma and other states of anesthesia
复制标题
用于控制药物引起的昏迷和其他麻醉状态的自适应且可推广的闭环系统
DOI：
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发表时间：
2016
影响因子：
4
通讯作者：
M. Shanechi
中科院分区：
文献类型：
--
作者：
Yuxiao Yang;M. Shanechi
Objective.闭环麻醉输送（CLAD）系统的设计是一个重要的课题，特别是对于需要长时间维持的医学诱导昏迷。目前用于医学诱导昏迷的CLAD需要单独的离线实验来进行模型参数估计，这导致治疗中断并且难以执行。此外，CLAD可能由于固有的时间变化和非平稳性而表现出偏差，并且在稳态下可能具有大的输注速率变化。最后，目前的CLAD缺乏理论上的性能保证。我们开发了第一个自适应CLAD用于医学诱导的昏迷，解决了这些限制。此外，我们将我们的自适应系统推广到其他麻醉状态。Approach.我们设计了一般参数药效学，药代动力学和神经观测模型与相关的指导方针，并推导出一种新的自适应控制器。我们进一步惩罚控制器中的大的稳态药物输注速率变化。我们从理论上保证了自适应系统具有零稳态偏差。使用类似于真实的时变和噪声环境的模拟，我们测试了用于控制两种不同麻醉状态的闭环系统，即药物诱导昏迷中的爆发抑制和全身麻醉中的无意识。主要结果。在1200次模拟中，自适应系统实现了对两种麻醉状态的精确控制，尽管存在非平稳性、时变、噪声和无初始参数知识。在这两种情况下，自适应系统的性能接近于准确知道参数的基线系统。相比之下，非自适应系统导致大的稳态偏差和误差。与现有系统相比，自适应系统还导致显著更小的稳态输注速率变化。意义这些结果对临床上可行的CLAD设计具有重要意义，适用于各种麻醉状态，具有潜在的成本节约和治疗益处。
Objective. Design of closed-loop anesthetic delivery (CLAD) systems is an important topic, particularly for medically induced coma, which needs to be maintained for long periods. Current CLADs for medically induced coma require a separate offline experiment for model parameter estimation, which causes interruption in treatment and is difficult to perform. Also, CLADs may exhibit bias due to inherent time-variation and non-stationarity, and may have large infusion rate variations at steady state. Finally, current CLADs lack theoretical performance guarantees. We develop the first adaptive CLAD for medically induced coma, which addresses these limitations. Further, we extend our adaptive system to be generalizable to other states of anesthesia. Approach. We designed general parametric pharmacodynamic, pharmacokinetic and neural observation models with associated guidelines, and derived a novel adaptive controller. We further penalized large steady-state drug infusion rate variations in the controller. We derived theoretical guarantees that the adaptive system has zero steady-state bias. Using simulations that resembled real time-varying and noisy environments, we tested the closed-loop system for control of two different anesthetic states, burst suppression in medically induced coma and unconsciousness in general anesthesia. Main results. In 1200 simulations, the adaptive system achieved precise control of both anesthetic states despite non-stationarity, time-variation, noise, and no initial parameter knowledge. In both cases, the adaptive system performed close to a baseline system that knew the parameters exactly. In contrast, a non-adaptive system resulted in large steady-state bias and error. The adaptive system also resulted in significantly smaller steady-state infusion rate variations compared to prior systems. Significance. These results have significant implications for clinically viable CLAD design for a wide range of anesthetic states, with potential cost-saving and therapeutic benefits.
DOI：
10.1056/nejmra0808281
发表时间：
2010-12-30
期刊：
The New England journal of medicine
影响因子：
--
作者：
Brown EN;Lydic R;Schiff ND
通讯作者：
Schiff ND
影响因子：
13.9
作者：
Brown EN;Purdon PL;Van Dort CJ
通讯作者：
Van Dort CJ