scholarly journals Evaluation of Anesthetic Specific EEG Dynamics during State Transitions between Loss and Return of Responsiveness

2021 ◽  
Vol 12 (1) ◽  
pp. 37
Author(s):  
Matthias Kreuzer ◽  
Tobias Kiel ◽  
Leonie Ernst ◽  
Marlene Lipp ◽  
Gerhard Schneider ◽  
...  
Keyword(s):  
General Anesthesia ◽  
Dynamic State ◽  
Permutation Entropy ◽  
State Transitions ◽  
Emergence Period ◽  
Emergence Patterns ◽  
Processed Eeg ◽  
Inhalational Anesthetic ◽  
Cortical Depression ◽  
State Index

Purpose: electroencephalographic (EEG) information is used to monitor the level of cortical depression of a patient undergoing surgical intervention under general anesthesia. The dynamic state transitions into and out of anesthetic-induced loss and return of responsiveness (LOR, ROR) present a possibility to evaluate the dynamics of the EEG induced by different substances. We evaluated changes in the EEG power spectrum during anesthesia emergence for three different anesthetic regimens. We also assessed the possible impact of these changes on processed EEG parameters such as the permutation entropy (PeEn) and the cerebral state index (CSI). Methods: we analyzed the EEG from 45 patients, equally assigned to three groups. All patients were induced with propofol and the groups differed by the maintenance anesthetic regimen, i.e., sevoflurane, isoflurane, or propofol. We evaluated the EEG and parameter dynamics during LOR and ROR. For the emergence period, we focused on possible differences in the EEG dynamics in the different groups. Results: depending on the substance, the EEG emergence patterns showed significant differences that led to a substance-specific early activation of higher frequencies as indicated by the “wake” CSI values that occurred minutes before ROR in the inhalational anesthetic groups. Conclusion: our results highlight substance-specific differences in the emergence from anesthesia that can influence the EEG-based monitoring that probably have to be considered in order to improve neuromonitoring during general anesthesia.

scholarly journals High Incidence of Burst Suppression during Propofol Sedation for Outpatient Colonoscopy: Lessons Learned from Neuromonitoring

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Jamie Bloom ◽  
David Wyler ◽  
Marc C. Torjman ◽  
Tuan Trinh ◽  
Lucy Li ◽  
...  
Keyword(s):  
General Anesthesia ◽  
Lessons Learned ◽  
Burst Suppression ◽  
University Hospital ◽  
Institutional Practice ◽  
Anesthesia Providers ◽  
Processed Eeg ◽  
High Incidence ◽  
Patient State ◽  
State Index

Background. Although anesthesia providers may plan for moderate sedation, the depth of sedation is rarely quantified. Using processed electroencephalography (EEG) to assess the depth of sedation, this study investigates the incidence of general anesthesia with variable burst suppression in patients receiving propofol for outpatient colonoscopy. The lessons learned from neuromonitoring can then be used to guide institutional best sedation practice. Methods. This was a prospective observational study of 119 outpatients undergoing colonoscopy at Thomas Jefferson University Hospital (TJUH). Propofol was administered by CRNAs under anesthesiologists’ supervision. The Patient State Index (PSi™) generated by the Masimo SedLine® Brain Root Function monitor (Masimo Corp., Irvine, CA) was used to assess the depth of sedation. PSi data correlating to general anesthesia with variable burst suppression were confirmed by neuroelectrophysiologists’ interpretation of unprocessed EEG. Results. PSi values of <50 consistent with general anesthesia were attained in 118/119 (99.1%) patients. Of these patients, 33 (27.7%) attained PSi values <25 consistent with variable burst suppression. The 118 patients that reached PSi <50 spent a significantly greater percentage (53.1% vs. 42%) of their case at PSi levels <50 compared to PSi levels >50 (p=0.001). Mean total propofol dose was significantly correlated to patient PSi during periods of PSi <25 (R=0.406, p=0.021). Conclusion. Although providers planned for moderate to deep sedation, processed EEG showed patients were under general anesthesia, often with burst suppression. Anesthesiologists and endoscopists may utilize processed EEG to recognize their institutional practice patterns of procedural sedation with propofol and improve upon it.

Foxtail (Setariaspp.) seedling dynamics in spring wheat (Triticum aestivum) are influenced by seeding date and tillage regime

Weed Science ◽  
1999 ◽  
Vol 47 (2) ◽  
pp. 156-160 ◽  
Author(s):  
Eric Spandl ◽  
Beverly R. Durgan ◽  
Frank Forcella
Keyword(s):  
Spring Wheat ◽  
Wheat Yield ◽  
Seedling Density ◽  
Emergence Period ◽  
No Till ◽  
Seeding Date ◽  
Emergence Patterns ◽  
Seedling Dynamics ◽  
Chisel Plow ◽  
Moldboard Plow

Emergence patterns of foxtail in spring wheat following soybean were evaluated for three seeding dates and three tillage regimes. Cumulative foxtail emergence, as a percentage of total plants emerged in the growing season, was generally not influenced by tillage regime throughout most of the emergence period, but when differences occurred, emergence was lower with no-till than with moldboard plow. Foxtail seedling densities were greater in no-till and chisel plow than in moldboard plow. Weed biomass and wheat yields were not affected by tillage regime. Delaying wheat seeding reduced foxtail percent emergence and emerged seedling density. Differences in emergence patterns of foxtail were attributable to thermal accumulation after seeding. Wheat yield was not influenced by seeding date in 2 of 3 yr.

Cerebral oxygenation and processed EEG response to clamping and shunting during carotid endarterectomy under general anesthesia

2015 ◽  
Vol 29 (6) ◽  
pp. 713-720 ◽  
Author(s):  
William Perez ◽  
Christopher Dukatz ◽  
Sami El-Dalati ◽  
James Duncan ◽  
Mahmoud Abdel-Rasoul ◽  
...  
Keyword(s):  
General Anesthesia ◽  
Carotid Endarterectomy ◽  
Cerebral Oxygenation ◽  
Processed Eeg

scholarly journals The effects of trawling on the physical condition of the Norway lobster Nephrops norvegicus in relation to seasonal cycles in the Clyde Sea area

2009 ◽  
Vol 66 (3) ◽  
pp. 488-494 ◽  
Author(s):  
R. J. Milligan ◽  
A. Albalat ◽  
R. J. A. Atkinson ◽  
D. M. Neil
Keyword(s):  
Physical Condition ◽  
Seasonal Effects ◽  
Seasonal Cycles ◽  
Physical Damage ◽  
Nephrops Norvegicus ◽  
Emergence Period ◽  
Norway Lobster ◽  
Emergence Patterns ◽  
Clyde Sea ◽  
Sea Area

Abstract Milligan, R. J., Albalat, A., Atkinson, R. J. A., and Neil, D. M. 2009. The effects of trawling on the physical condition of the Norway lobster Nephrops norvegicus in relation to seasonal cycles in the Clyde Sea area. – ICES Journal of Marine Science, 66: 488–494. The fishery for Norway lobster, Nephrops norvegicus, is the most valuable in Scotland, but few studies have examined the physical condition of the animals trawled. This study aimed to determine the extent of physical damage caused by trawling to Nephrops in the Clyde Sea area in relation to trawl duration, sex, size, and moult stage. Longer trawls (2.5–4 h) corresponded to increased damage in “hard” (intermoult) Nephrops compared with short (1 h) or very short (15 min) trawls, but there was no correlation in “soft” (late intermoult or recently moulted) or “jelly” (immediate post-moult) Nephrops. This effect appeared to be limited to Nephrops with a carapace length (CL) of 20.0–29.9 mm. Seasonal effects were also observed, with numbers of jelly Nephrops highest in May 2006, corresponding to a peak in female prevalence in the catches, an increase in the mean CL of females, and greater damage in females. The proportion of females was higher than males from May to September 2006, and it is suggested that this corresponds to female emergence patterns. As quality will be low, it may be pertinent to avoid fishing during the peak emergence period to maximize the quality and profitability of catches.

scholarly journals A novel multivariate STeady-state index during general ANesthesia (STAN)

2016 ◽  
Vol 31 (4) ◽  
pp. 851-860 ◽  
Author(s):  
Ana Castro ◽  
Fernando Gomes de Almeida ◽  
Pedro Amorim ◽  
Catarina S. Nunes
Keyword(s):  
Steady State ◽  
General Anesthesia ◽  
State Index

scholarly journals Time-varying Dynamic Network Model For Dynamic Resting State Functional Connectivity in fMRI and MEG imaging

2021 ◽  
Author(s):  
Fei Jiang ◽  
Huaqing Jin ◽  
Yijing Bao ◽  
Xihe Xie ◽  
Jennifer Cummings ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Dynamic Network ◽  
Dynamic State ◽  
State Transitions ◽  
Dimensional Manifold ◽  
Time Varying ◽  
Resting State Functional Connectivity ◽  
Brain Signals ◽  
Low Dimensional

Dynamic resting state functional connectivity (RSFC) characterizes fluctuations that occurs over time in functional brain networks. Existing methods to extract dynamic RSFCs, such as sliding-window and clustering methods, have various limitations due to their inherent non-adaptive nature and high-dimensionality including an inability to reconstruct brain signals, insufficiency of data for reliable estimation, insensitivity to rapid changes in dynamics, and a lack of generalizability across multi- modal functional imaging datasets. To overcome these deficiencies, we develop a novel and unifying time-varying dynamic network (TVDN) framework for examining dynamic resting state functional connectivity. TVDN includes a generative model that describes the relation between low-dimensional dynamic RSFC and the brain signals, and an inference algorithm that automatically and adaptively learns to detect dynamic state transitions in data and a low-dimensional manifold of dynamic RSFC. TVDN is generalizable to handle multimodal functional neuroimaging data (fMRI and MEG/EEG). The resulting estimated low-dimensional dynamic RSFCs manifold directly links to the frequency content of brain signals. Hence we can evaluate TVDN performance by examining whether learnt features can reconstruct observed brain signals. We conduct comprehensive simulations to evaluate TVDN under hypothetical settings. We then demonstrate the application of TVDN with real fMRI and MEG data, and compare the results with existing benchmarks. Results demonstrate that TVDN is able to correctly capture the dynamics of brain activity and more robustly detect brain state switching both in resting state fMRI and MEG data.

scholarly journals STMC-14. GLIOBLASTOMA CANCER STEM CELLS UNDERGO DYNAMIC STATE TRANSITIONS

2016 ◽  
Vol 18 (suppl_6) ◽  
pp. vi185-vi185
Author(s):  
Anne Dirkse ◽  
Nicolaas H. C. Brons ◽  
Thomas Buder ◽  
Andreas Deutsch ◽  
Sonia Leite ◽  
...  
Keyword(s):  
Stem Cells ◽  
Cancer Stem Cells ◽  
Dynamic State ◽  
State Transitions

ANALYSIS OF ABSENCE SEIZURE GENERATION USING EEG SPATIAL-TEMPORAL REGULARITY MEASURES

2012 ◽  
Vol 22 (06) ◽  
pp. 1250024 ◽  
Author(s):  
NADIA MAMMONE ◽  
DOMENICO LABATE ◽  
AIME LAY-EKUAKILLE ◽  
FRANCESCO C. MORABITO
Keyword(s):  
Healthy Subjects ◽  
Dynamical Behavior ◽  
Epileptic Seizures ◽  
Temporal Analysis ◽  
Extensive Study ◽  
Permutation Entropy ◽  
State Transitions ◽  
Gradual Transition ◽  
Absence Seizure ◽  
Two Parameters

Epileptic seizures are thought to be generated and to evolve through an underlying anomaly of synchronization in the activity of groups of neuronal populations. The related dynamic scenario of state transitions is revealed by detecting changes in the dynamical properties of Electroencephalography (EEG) signals. The recruitment procedure ending with the crisis can be explored through a spatial-temporal plot from which to extract suitable descriptors that are able to monitor and quantify the evolving synchronization level from the EEG tracings. In this paper, a spatial-temporal analysis of EEG recordings based on the concept of permutation entropy (PE) is proposed. The performance of PE are tested on a database of 24 patients affected by absence (generalized) seizures. The results achieved are compared to the dynamical behavior of the EEG of 40 healthy subjects. Being PE a feature which is dependent on two parameters, an extensive study of the sensitivity of the performance of PE with respect to the parameters' setting was carried out on scalp EEG. Once the optimal PE configuration was determined, its ability to detect the different brain states was evaluated. According to the results here presented, it seems that the widely accepted model of "jump" transition to absence seizure should be in some cases coupled (or substituted) by a gradual transition model characteristic of self-organizing networks. Indeed, it appears that the transition to the epileptic status is heralded before the preictal state, ever since the interictal stages. As a matter of fact, within the limits of the analyzed database, the frontal-temporal scalp areas appear constantly associated to PE levels higher compared to the remaining electrodes, whereas the parieto-occipital areas appear associated to lower PE values. The EEG of healthy subjects neither shows any similar dynamic behavior nor exhibits any recurrent portrait in PE topography.

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