Dynamic assessment of signal entropy for prognostication and secondary brain insult detection after traumatic brain injury

动态评估信号熵在创伤性脑损伤后预后预测和继发性脑损伤检测中的应用

阅读:1

Abstract

BACKGROUND: Entropy quantifies the level of disorder within a system. Low entropy reflects increased rigidity of homeostatic feedback systems possibly reflecting failure of protective physiological mechanisms like cerebral autoregulation. In traumatic brain injury (TBI), low entropy of heart rate and intracranial pressure (ICP) predict unfavorable outcome. Based on the hypothesis that entropy is a dynamically changing process, we explored the origin and value of entropy time trends. METHODS: 232 continuous recordings of arterial blood pressure and ICP of TBI patients with available clinical information and 6-month outcome (Glasgow Outcome Scale) were accessed form the Brain Physics database. Biosignal entropy was estimated as multiscale entropy (MSE) that aggregates entropy at several time scales (20 coarse graining steps starting from 0.1 Hz). MSE was calculated repeatedly for consecutive, overlapping 6 h segments. Percentage monitoring time (ptime) or dosage (duration*level/hour) below different cutoffs were evaluated against outcome using univariable and multivariable analyses, and propensity score matching. Associations to clinical and monitoring metrics were explored using correlation coefficients. Lastly, individual secondary brain insults (deviations in ICP, cerebral perfusion pressure - CPP, or pressure reactivity) were assessed in relation to changes in MSE. RESULTS: Increased MSE abp and MSE cpp ptime (OR 1.28 (1.07-1.58) and OR 1.50 (1.16-2.03) for MSE abp and cpp respectively) and dose (OR 1.12 (1.02-1.27) and OR 1.21 (1.06-1.46) for MSE abp and cpp respectively) were associated with poor outcome even after propensity score matching within multivariable models correcting for ICP, CPP, and the pressure reactivity index. MSE trajectories differed significantly dependent on outcome. The entropy metrics displayed weak correlations to clinical parameters. Individual episodes of deranged physiology were associated with decreases in the MSE metrics from both cerebral and systemic biosignals. CONCLUSIONS: Biosignal entropy of changes dynamically after TBI. The assessment of these variations augments individualized, dynamic, outcome prognostication and identification of secondary cerebral insults. Additionally, these explorations allow for further exploitation of the extensive physiological data lakes acquired for each TBI patient within an intensive care environment.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。