Literature DB >> 16508396

Time delay of index calculation: analysis of cerebral state, bispectral, and narcotrend indices.

Stefanie Pilge1, Robert Zanner, Gerhard Schneider, Jasmin Blum, Matthias Kreuzer, Eberhard F Kochs.   

Abstract

BACKGROUND: On the basis of electroencephalographic analysis, several parameters have been proposed as a measure of the hypnotic component of anesthesia. All currently available indices have different time lags to react to a change in the level of anesthesia. The aim of this study was to determine the latency of three frequently used indices: the Cerebral State Index (Danmeter, Odense, Denmark), the Bispectral Index (Aspect Medical Systems Inc., Newton, MA), and the Narcotrend Index (MonitorTechnik, Bad Bramstedt, Germany).
METHODS: Artificially generated signals were used to produce up to 14 constant index values per monitor that indicate "awake state," "general anesthesia," and "deep anesthesia" and smaller steps in between. The authors simulated loss of and return to consciousness by changing between the artificial electroencephalographic signals in a full-step and two stepwise approaches and measured the time necessary to adapt the indices to the particular input signal.
RESULTS: Time delays between 14 and 155 s were found for all indices. These delays were not constant. Results were different for decreasing and increasing values and between the full-step and the stepwise approaches. Calculation time depended on the particular starting and target index value.
CONCLUSIONS: The time delays of the tested indices may limit their value in prevention of recall of intraoperative events. Furthermore, different latencies for decreasing and increasing values may indicate a limitation of these monitors for pharmacodynamic studies.

Mesh:

Year:  2006        PMID: 16508396     DOI: 10.1097/00000542-200603000-00016

Source DB:  PubMed          Journal:  Anesthesiology        ISSN: 0003-3022            Impact factor:   7.892


  29 in total

1.  Changes in near-infrared spectroscopy and the bispectral index during tilt-table examination.

Authors:  Aymen N Naguib; Peter Winch; Pamela S Ro; Vincent Olshove; Joseph D Tobias
Journal:  Pediatr Cardiol       Date:  2011-01-06       Impact factor: 1.655

2.  Characterizing Awake and Anesthetized States Using a Dimensionality Reduction Method.

Authors:  M Mirsadeghi; H Behnam; R Shalbaf; H Jelveh Moghadam
Journal:  J Med Syst       Date:  2015-10-29       Impact factor: 4.460

3.  Cerebral state index versus bispectral index during propofol-fentanyl-nitrous oxide anesthesia.

Authors:  Tomoki Nishiyama; Kyoko Komatsu
Journal:  J Anesth       Date:  2010-03-26       Impact factor: 2.078

Review 4.  [Measurement of the depth of anaesthesia].

Authors:  G N Schmidt; J Müller; P Bischoff
Journal:  Anaesthesist       Date:  2008-01       Impact factor: 1.041

5.  Monitoring depth of anesthesia using combination of EEG measure and hemodynamic variables.

Authors:  R Shalbaf; H Behnam; H Jelveh Moghadam
Journal:  Cogn Neurodyn       Date:  2014-05-09       Impact factor: 5.082

6.  Non-stationarity of EEG during wakefulness and anaesthesia: advantages of EEG permutation entropy monitoring.

Authors:  Matthias Kreuzer; Eberhard F Kochs; Gerhard Schneider; Denis Jordan
Journal:  J Clin Monit Comput       Date:  2014-01-18       Impact factor: 2.502

7.  Spectral and Entropic Features Are Altered by Age in the Electroencephalogram in Patients under Sevoflurane Anesthesia.

Authors:  Matthias Kreuzer; Matthew A Stern; Darren Hight; Sebastian Berger; Gerhard Schneider; James W Sleigh; Paul S García
Journal:  Anesthesiology       Date:  2020-05       Impact factor: 7.892

8.  Frontal-temporal functional connectivity of EEG signal by standardized permutation mutual information during anesthesia.

Authors:  Fahimeh Afshani; Ahmad Shalbaf; Reza Shalbaf; Jamie Sleigh
Journal:  Cogn Neurodyn       Date:  2019-08-22       Impact factor: 5.082

9.  Anaesthesia monitoring by recurrence quantification analysis of EEG data.

Authors:  Klaus Becker; Gerhard Schneider; Matthias Eder; Andreas Ranft; Eberhard F Kochs; Walter Zieglgänsberger; Hans-Ulrich Dodt
Journal:  PLoS One       Date:  2010-01-26       Impact factor: 3.240

10.  Real-time closed-loop control in a rodent model of medically induced coma using burst suppression.

Authors:  ShiNung Ching; Max Y Liberman; Jessica J Chemali; M Brandon Westover; Jonathan D Kenny; Ken Solt; Patrick L Purdon; Emery N Brown
Journal:  Anesthesiology       Date:  2013-10       Impact factor: 7.892

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