Forehead electrodes sufficiently detect propofol-induced slow waves for the assessment of brain function after cardiac arrest

Jukka Kortelainen, Eero Väyrynen, Ilkka Juuso, Jouko Laurila, Juha Koskenkari, Tero Ala-Kokko, Jukka Kortelainen, Eero Väyrynen, Ilkka Juuso, Jouko Laurila, Juha Koskenkari, Tero Ala-Kokko

Abstract

In a recent study, we proposed a novel method to evaluate hypoxic ischemic encephalopathy (HIE) by assessing propofol-induced changes in the 19-channel electroencephalogram (EEG). The study suggested that patients with HIE are unable to generate EEG slow waves during propofol anesthesia 48 h after cardiac arrest (CA). Since a low number of electrodes would make the method clinically more practical, we now investigated whether our results received with a full EEG cap could be reproduced using only forehead electrodes. Experimental data from comatose post-CA patients (N = 10) were used. EEG was recorded approximately 48 h after CA using 19-channel EEG cap during a controlled propofol exposure. The slow wave activity was calculated separately for all electrodes and four forehead electrodes (Fp1, Fp2, F7, and F8) by determining the low-frequency (< 1 Hz) power of the EEG. HIE was defined by following the patients' recovery for six months. In patients without HIE (N = 6), propofol substantially increased (244 ± 91%, mean ± SD) the slow wave activity in forehead electrodes, whereas the patients with HIE (N = 4) were unable to produce such activity. The results received with forehead electrodes were similar to those of the full EEG cap. With the experimental pilot study data, the forehead electrodes were as capable as the full EEG cap in capturing the effect of HIE on propofol-induced slow wave activity. The finding offers potential in developing a clinically practical method for the early detection of HIE.

Keywords: Anesthesia; Brain injury; Electroencephalogram; Intensive care; Monitoring; Propofol.

Conflict of interest statement

Jukka Kortelainen, Eero Väyrynen and Ilkka Juuso are co-founders of Cerenion Oy, a company developing EEG-based technology for measuring brain function in intensive care.

Figures

Fig. 1
Fig. 1
Effect of propofol on EEG slow wave activity in four forehead channels and all 19 channels of full EEG cap. a Propofol infusion rate during the experiment. b Low-frequency (< 1 Hz) EEG power representing the slow wave activity of a patient with good neurological outcome. The average low-frequency power (thick curve) is calculated from all 19 single channel powers (gray curves). The average power of the four forehead electrodes (dashed curve) is also shown. The topographic distribution of the low-frequency EEG power at different phases of the experiment is given above the curves. c The same data of a patient with poor neurological outcome
Fig. 2
Fig. 2
The location of electrodes for full 19-channel EEG cap and the four forehead channels used in the analysis
Fig. 3
Fig. 3
Slow wave activity of four forehead channels and all 19 channels of full EEG cap in the groups of good and poor neurological outcome. Above, topographic distribution of low-frequency (

References

    1. Young GB. Clinical practice. Neurologic prognosis after cardiac arrest. N Engl J Med. 2009;361:605–611. doi: 10.1056/NEJMcp0903466.
    1. Taccone FS, Cronberg T, Friberg H, Greer D, Horn J, Oddo M, et al. How to assess prognosis after cardiac arrest and therapeutic hypothermia. Crit Care. 2014;18:202. doi: 10.1186/cc13696.
    1. Rossetti A, Rabinstein A, Oddo M. Neurological prognostication of outcome in patients in coma after cardiac arrest. Lancet Neurol. 2016;15:597–609. doi: 10.1016/S1474-4422(16)00015-6.
    1. Oh SH, Park KN, Shon Y-M, Kim Y-M, Kim HJ, Youn CS, et al. Continuous amplitude-integrated electroencephalographic monitoring is a useful prognostic tool for hypothermia-treated cardiac arrest patients. Circulation. 2015;132:1094–1103. doi: 10.1161/CIRCULATIONAHA.115.015754.
    1. Tjepkema-Cloostermans MC, Hofmeijer J, Beishuizen A, Hom HW, Blans MJ, Bosch FH, van Putten MJAM. Cerebral Recovery Index: Reliable help for prediction of neurologic outcome after cardiac arrest. Crit Care Med. 2017;45:e789–e797. doi: 10.1097/CCM.0000000000002412.
    1. Kortelainen J, Väyrynen E, Huuskonen U, Laurila J, Koskenkari J, Backman JT, Alahuhta S, Seppänen T, Ala-Kokko T. Pilot study of propofol-induced slow waves as a pharmacologic test for brain dysfunction after brain injury. Anesthesiology. 2017;126:94–103. doi: 10.1097/ALN.0000000000001385.
    1. Crunelli V, Hughes SW. The slow (< 1 Hz) rhythm of non-REM sleep: a dialogue between three cardinal oscillators. Nat Neurosci. 2010;13:9–17. doi: 10.1038/nn.2445.
    1. Steriade M, McCormick DA, Sejnowski TJ. Thalamocortical oscillations in the sleeping and aroused brain. Science. 1993;262:679–685. doi: 10.1126/science.8235588.
    1. Purdon PL, Pierce ET, Mukamel EA, Prerau MJ, Walsh JL, Wong KF, Salazar-Gomez AF, Harrell PG, Sampson AL, Cimenser A, Ching S, Kopell NJ, Tavares-Stoeckel C, Habeeb K, Merhar R, Brown EN. Electroencephalogram signatures of loss and recovery of consciousness from propofol. Proc Natl Acad Sci USA. 2013;110:E1142-51. doi: 10.1073/pnas.1221180110.
    1. Stickgold R. Sleep-dependent memory consolidation. Nature. 2005;437:1272–1278. doi: 10.1038/nature04286.
    1. Marshall L, Helgadottir H, Molle M, Born J. Boosting slow oscillations during sleep potentiates memory. Nature. 2006;444:610–613. doi: 10.1038/nature05278.
    1. Northoff G. “Paradox of slow frequencies”—are slow frequencies in upper cortical layers a neural predisposition of the level/state of consciousness (NPC)? Conscious Cogn. 2017;54:20–35. doi: 10.1016/j.concog.2017.03.006.
    1. Welch PD. The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans Audio Electroacoust. 1967;15:70–73. doi: 10.1109/TAU.1967.1161901.
    1. Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods. 2004;134:9–21. doi: 10.1016/j.jneumeth.2003.10.009.
    1. Gugino L, Chabot R, Prichep L, John E, Formanek V, Aglio L. Quantitative EEG changes associated with loss and return of consciousness in healthy adult volunteers anaesthetized with propofol or sevoflurane. Br J Anaesth. 2001;87:421–428. doi: 10.1093/bja/87.3.421.
    1. Hagihira S. Changes in the electroencephalogram during anaesthesia and their physiological basis. Br J Anaesth. 2015;115:i27–i31. doi: 10.1093/bja/aev212.
    1. Murphy M, Bruno M, Riedner B, Boveroux P, Noirhomme Q, Landsness E, Brichant J, Phillips C, Massimini M, Laureys S, Tononi G, Boly M. Propofol anesthesia and sleep: a high-density EEG study. Sleep. 2011;34:283–291. doi: 10.1093/sleep/34.3.283.
    1. Backman S, Westhall E, Dragancea I, Friberg H, Rundgren M, Ullén S, Cronberg T. Electroencephalographic characteristics of status epilepticus after cardiac arrest. Clin Neurophysiol. 2017;128:681–688. doi: 10.1016/j.clinph.2017.01.002.
    1. Rittenberger J, Popescu A, Brenner R, Guyette F, Callaway C. Frequency and timing of nonconvulsive status epilepticus in comatose post-cardiac arrest subjects treated with hypothermi. Neurocrit Care. 2013;16:114–122. doi: 10.1007/s12028-011-9565-0.
    1. Ribeiro A, Singh R, Brunnhuber F. Clinical outcome of generalized periodic epileptiform discharges on first EEG in patients with hypoxic encephalopathy postcardiac arrest. Epilepsy Behav. 2015;49:268–272. doi: 10.1016/j.yebeh.2015.06.010.
    1. Myllymaa S, Lepola P, Töyräs J, Hukkanen T, Mervaala E, Lappalainen R, Myllymaa K. New disposable forehead electrode set with excellent signal quality and imaging compatibility. J Neurosci Methods. 2013;215:103–109. doi: 10.1016/j.jneumeth.2013.02.003.
    1. Lepola P, Myllymaa S, Töyräs J, Muraja-Murro A, Mervaala E, Lappalainen R, Myllymaa K. Screen-printed EEG electrode set for emergency use. Sens Actuators A. 2014;213:19–26. doi: 10.1016/j.sna.2014.03.029.

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