Skip to main content

Electrocerebral Signature of Cardiac Death

Neurocritical Care volume 35, pages 853–861 (2021)Cite this article

Abstract

Background

Electroencephalography (EEG) findings following cardiovascular collapse in death are uncertain. We aimed to characterize EEG changes immediately preceding and following cardiac death.

Methods

We retrospectively analyzed EEGs of patients who died from cardiac arrest while undergoing standard EEG monitoring in an intensive care unit. Patients with brain death preceding cardiac death were excluded. Three events during fatal cardiovascular failure were investigated: (1) last recorded QRS complex on electrocardiogram (QRS0), (2) cessation of cerebral blood flow (CBF0) estimated as the time that blood pressure and heart rate dropped below set thresholds, and (3) electrocerebral silence on EEG (EEG0). We evaluated EEG spectral power, coherence, and permutation entropy at these time points.

Results

Among 19 patients who died while undergoing EEG monitoring, seven (37%) had a comfort-measures-only status and 18 (95%) had a do-not-resuscitate status in place at the time of death. EEG0 occurred at the time of QRS0 in five patients and after QRS0 in two patients (cohort median − 2.0, interquartile range − 8.0 to 0.0), whereas EEG0 was seen at the time of CBF0 in six patients and following CBF0 in 11 patients (cohort median 2.0 min, interquartile range − 1.5 to 6.0). After CBF0, full-spectrum log power (p < 0.001) and coherence (p < 0.001) decreased on EEG, whereas delta (p = 0.007) and theta (p < 0.001) permutation entropy increased.

Conclusions

Rarely may patients have transient electrocerebral activity following the last recorded QRS (less than 5 min) and estimated cessation of cerebral blood flow. These results may have implications for discussions around cardiopulmonary resuscitation and organ donation.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price includes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3

References

  1. Salehi S, Tran K, Grayson WL. Advances in perfusion systems for solid organ preservation. Yale J Biol Med. 2018;91(3):301–12.

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Blundon EG, Gallagher RE, Ward LM. Electrophysiological evidence of preserved hearing at the end of life. Sci Rep. 2020;10(1):10336.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Pozhitkov AE, Neme R, Domazet-Lošo T, et al. Tracing the dynamics of gene transcripts after organismal death. Open Biol. 2017;7(1):160267.

    PubMed  PubMed Central  Google Scholar 

  4. Ferreira PG, Muñoz-Aguirre M, Reverter F, et al. The effects of death and post-mortem cold ischemia on human tissue transcriptomes. Nat Commun. 2018;9(1):490.

    PubMed  PubMed Central  Google Scholar 

  5. Borjigin J, Lee U, Liu T, et al. Surge of neurophysiological coherence and connectivity in the dying brain. Proc Natl Acad Sci. 2013;110(35):14432–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Reagan EM, Nguyen RT, Ravishankar ST, et al. Monitoring the relationship between changes in cerebral oxygenation and electroencephalography patterns during cardiopulmonary resuscitation. Crit Care Med. 2018;46(5):757–63.

    PubMed  Google Scholar 

  7. Norton L, Gibson RM, Gofton T, et al. Electroencephalographic recordings during withdrawal of life-sustaining therapy until 30 minutes after declaration of death. Can J Neurol Sci. 2017;44(2):139–45.

    PubMed  Google Scholar 

  8. Chawla LS, Akst S, Junker C, Jacobs B, Seneff MG. Surges of electroencephalogram activity at the time of death: a case series. J Palliat Med. 2009;12(12):1095–100.

    PubMed  Google Scholar 

  9. Auyong DB, Klein SM, Gan TJ, Roche AM, Olson D, Habib AS. Processed electroencephalogram during donation after cardiac death. Anesth Analg. 2010;110(5):1428–32.

    PubMed  Google Scholar 

  10. Edlow BL, Fins JJ. Assessment of covert consciousness in the intensive care unit: clinical and ethical considerations. J Head Trauma Rehabil. 2018;33(6):424–34.

    PubMed  PubMed Central  Google Scholar 

  11. Claassen J, Doyle K, Matory A, et al. Detection of brain activation in unresponsive patients with acute brain injury. N Engl J Med. 2019;380(26):2497–505.

    PubMed  Google Scholar 

  12. Altwegg-Boussac T, Schramm AE, Ballestero J, et al. Cortical neurons and networks are dormant but fully responsive during isoelectric brain state. Brain. 2017;140(9):2381–98.

    PubMed  Google Scholar 

  13. Levin P, Kinnel J. Successful cardiac resuscitation despite prolonged silence of EEG. Arch Intern Med. 1966;117(4):557.

    CAS  PubMed  Google Scholar 

  14. Trojaborg W, Boysen G. Relation between EEG, regional cerebral blood flow and internal carotid artery pressure during carotid endarterectomy. Electroencephalogr Clin Neurophysiol. 1973;34(1):61–9.

    CAS  PubMed  Google Scholar 

  15. Clute HL, Levy WJ. Electroencephalographic changes during brief cardiac arrest in humans. Anesthesiology. 1990;73(5):821–5.

    CAS  PubMed  Google Scholar 

  16. Chawla LS, Terek M, Junker C, et al. Characterization of end-of-life electroencephalographic surges in critically ill patients. Death Stud. 2017;41(6):385–92.

    PubMed  Google Scholar 

  17. Lee DE, Lee LG, Siu D, et al. Neural correlates of consciousness at near-electrocerebral silence in an asphyxial cardiac arrest model. Brain Connect. 2017;7(3):172–81.

    PubMed  PubMed Central  Google Scholar 

  18. Moss J, Rockoff M. EEG monitoring during cardiac arrest and resuscitation. JAMA. 1980;244(24):2750–1.

    CAS  PubMed  Google Scholar 

  19. Nichols GS. Guideline 3: minimum technical standards for EEG recording in suspected cerebral death. J Clin Neurophysiol. 2012;29(2):109.

    PubMed  Google Scholar 

  20. Das MK, Zipes DP. Fragmented QRS: a predictor of mortality and sudden cardiac death. Hear Rhythm. 2009;6(3):S8-14.

    Google Scholar 

  21. Oostenveld R, Fries P, Maris E, Schoffelen J-M. FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput Intell Neurosci. 2011;2011:1–9.

    Google Scholar 

  22. Bokil H, Andrews P, Kulkarni JE, Mehta S, Mitra PP. Chronux: a platform for analyzing neural signals. J Neurosci Methods. 2010;192(1):146–51.

    PubMed  PubMed Central  Google Scholar 

  23. Bandt C, Pompe B. Permutation entropy: a natural complexity measure for time series. Phys Rev Lett. 2002;88(17):174102.

    PubMed  Google Scholar 

  24. Azevedo MA, Bitencourt Othero JC. Human death as a triptych process. Mortality. 2020;25(4):490–504. https://doi.org/10.1080/13576275.2020.1756765.

    Article  Google Scholar 

  25. de Vries JW, Bakker PFA, Visser GH, Diephuis JC, van Huffelen AC. Changes in cerebral oxygen uptake and cerebral electrical activity during defibrillation threshold testing. Anesth Analg. 1998;87(1):16–20.

    PubMed  Google Scholar 

  26. Pana R, Hornby L, Shemie SD, Dhanani S, Teitelbaum J. Time to loss of brain function and activity during circulatory arrest. J Crit Care. 2016;34:77–83.

    CAS  PubMed  Google Scholar 

  27. Dhanani S, Hornby L, van Beinum A, et al. Resumption of cardiac activity after withdrawal of life-sustaining measures. N Engl J Med. 2021;384(4):345–52.

    PubMed  Google Scholar 

  28. Schramm AE, Carton-Leclercq A, Diallo S, et al. Identifying neuronal correlates of dying and resuscitation in a model of reversible brain anoxia. Prog Neurobiol. 2020;185:101733.

    PubMed  Google Scholar 

  29. Vrselja Z, Daniele SG, Silbereis J, et al. Restoration of brain circulation and cellular functions hours post-mortem. Nature. 2019;568(7752):336–43.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Hossmann K-A, Zimmermann V. Resuscitation of the monkey brain after 1 H complete ischemia: I: physiological and morphological observations. Brain Res. 1974;81(1):59–74.

    CAS  PubMed  Google Scholar 

  31. Jacobs J. Hippocampal theta oscillations are slower in humans than in rodents: implications for models of spatial navigation and memory. Philos Trans R Soc Lond B Biol Sci. 2014;369(1635):20130304.

    PubMed  PubMed Central  Google Scholar 

  32. Watrous AJ, Lee DJ, Izadi A, Gurkoff GG, Shahlaie K, Ekstrom AD. A comparative study of human and rat hippocampal low-frequency oscillations during spatial navigation. Hippocampus. 2013;23(8):656–61.

    PubMed  PubMed Central  Google Scholar 

  33. Wang J, Li D, Li X, et al. Phase–amplitude coupling between theta and gamma oscillations during nociception in rat electroencephalography. Neurosci Lett. 2011;499(2):84–7.

    CAS  PubMed  Google Scholar 

  34. Olofsen E, Sleigh JW, Dahan A. Permutation entropy of the electroencephalogram: a measure of anaesthetic drug effect. Br J Anaesth. 2008;101(6):810–21.

    CAS  PubMed  Google Scholar 

  35. Kreuzer M, Kochs EF, Schneider G, Jordan D. Non-stationarity of EEG during wakefulness and anaesthesia: advantages of EEG permutation entropy monitoring. J Clin Monit Comput. 2014;28(6):573–80.

    PubMed  Google Scholar 

  36. Sitt JD, King J-R, El Karoui I, et al. Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state. Brain. 2014;137(8):2258–70.

    PubMed  PubMed Central  Google Scholar 

  37. Suffczynski P, Kalitzin S, Lopes Da Silva FH. Dynamics of non-convulsive epileptic phenomena modeled by a bistable neuronal network. Neuroscience. 2004;126(2):467–84.

    CAS  PubMed  Google Scholar 

  38. Ferlazzo E, Zifkin BG, Andermann E, Andermann F. Cortical triggers in generalized reflex seizures and epilepsies. Brain. 2005;128(4):700–10.

    PubMed  Google Scholar 

  39. Takeshita D, Sato YD, Bahar S. Transitions between multistable states as a model of epileptic seizure dynamics. Phys Rev E. 2007;75(5):051925.

    Google Scholar 

  40. Nitsch C, Klatzo I. Regional patterns of blood-brain barrier breakdown during epileptiform seizures induced by various convulsive agents. J Neurol Sci. 1983;59(3):305–22.

    CAS  PubMed  Google Scholar 

  41. Clarke HB, Gabrielsen TO. Seizure induced disruption of blood-brain barrier demonstrated by CT. J Comput Assist Tomogr. 1989;13(5):889–92.

    CAS  PubMed  Google Scholar 

  42. Seiffert E, Dreier JP, Ivens S, et al. Lasting blood-brain barrier disruption induces epileptic focus in the rat somatosensory cortex. J Neurosci. 2004;24(36):7829–36.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. van Vliet EA, Otte WM, Gorter JA, Dijkhuizen RM, Wadman WJ. Longitudinal assessment of blood-brain barrier leakage during epileptogenesis in rats: A quantitative MRI study. Neurobiol Dis. 2014;63:74–84.

    PubMed  Google Scholar 

  44. Löscher W. Epilepsy and alterations of the blood–brain barrier: cause or consequence of epileptic seizures or both? Handb Exp Pharmacol. 2020. https://doi.org/10.1007/164_2020_406.

    Article  PubMed  Google Scholar 

  45. Mueller AL, Dunwiddie TV. Anticonvulsant and proconvulsant actions of alpha- and beta-noradrenergic agonists on epileptiform activity in rat hippocampus in vitro. Epilepsia. 1983;24(1):57–64.

    CAS  PubMed  Google Scholar 

  46. Wortsman J. Role of epinephrine in acute stress. Endocrinol Metab Clin North Am. 2002;31(1):79–106.

    CAS  PubMed  Google Scholar 

  47. Haut SR, Hall CB, Masur J, Lipton RB. Seizure occurrence: precipitants and prediction. Neurology. 2007;69(20):1905–10.

    PubMed  Google Scholar 

  48. Stiegler P, Sereinigg M, Puntschart A, et al. A 10 min “no-touch” time—is it enough in DCD? A DCD animal study Transpl Int. 2012;25(4):481–92.

    PubMed  Google Scholar 

  49. Nagao K, Nonogi H, Yonemoto N, et al. Duration of prehospital resuscitation efforts after out-of-hospital cardiac arrest. Circulation. 2016;133(14):1386–96.

    PubMed  Google Scholar 

  50. Morley PT, Lang E, Aickin R, et al. Part 2: evidence evaluation and management of conflicts of interest. Circulation. 2015;132(16 suppl 1):S40-50.

    PubMed  Google Scholar 

  51. Nakagawa TA, Ashwal S, Mathur M, Mysore M. Guidelines for the determination of brain death in infants and children: an update of the 1987 task force recommendations-executive summary. Ann Neurol. 2012;71(4):573–85.

    PubMed  Google Scholar 

  52. Greer DM, Shemie SD, Lewis A, et al. Determination of brain death/death by neurologic criteria: the world brain death project. JAMA. 2020;324(11):1078–97.

    Google Scholar 

  53. Fernández-Torre JL, Hernández-Hernández MA, Muñoz-Esteban C. Non confirmatory electroencephalography in patients meeting clinical criteria for brain death: scenario and impact on organ donation. Clin Neurophysiol. 2013;124(12):2362–7.

    PubMed  Google Scholar 

  54. Truog RD. Defining death-making sense of the case of Jahi McMath. JAMA. 2018;319(18):1859–60.

    PubMed  Google Scholar 

  55. Dhanani S, Hornby L, Ward R, et al. Vital signs after cardiac arrest following withdrawal of life-sustaining therapy. Crit Care Med. 2014;42(11):2358–69.

    PubMed  Google Scholar 

  56. Greyson B, Evans BN. Distressing near-death experiences. Psychiatry. 1992;55(1):95–110.

    CAS  PubMed  Google Scholar 

  57. Bonenfant RJ. A child’s encounter with the devil: an unusual near-death experience with both blissful and frightening elements. JNDS. 2001;20(2):87–100.

    Google Scholar 

  58. French CC. Dying to know the truth: visions of a dying brain, or false memories? Lancet. 2001;358(9298):2010–1.

    CAS  PubMed  Google Scholar 

  59. Palmieri A, Calvo V, Kleinbub JR, et al. “Reality” of near-death-experience memories: evidence from a psychodynamic and electrophysiological integrated study. Front Hum Neurosci. 2014;8(429):1–16.

    Google Scholar 

  60. KeshavarzShirazi T, Gonzales AM, Dickinson A, Parnia S. Abstract 314: cardiac arrest related cognitive activity. Circulation. 2020;142(suppl 4):314.

    Google Scholar 

  61. Dreier JP, Major S, Foreman B, et al. Terminal spreading depolarization and electrical silence in death of human cerebral cortex. Ann Neurol. 2018;83(2):295–310.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

Thank you to the nurses, attending physicians, fellows, and residents of the Neurological ICU of Columbia University Irving Medical Center for their overall support of this project. We would like to thank Professor Laura Lennihan for her insightful comments regarding the ethical implications of our work and for providing helpful critiques for our paper.

Funding

JC is supported by grant funding from the National Institutes of Health (R01 NS106014 and R03 NS112760), the James McDonnell Foundation, and the Dana Foundation. AA is supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under the Miami Clinical and Translational Science Institute KL2 Career Development Award (UL1TR002736). SP is supported by the National Institutes of Health (K01 ES026833).

Author information

Authors and Affiliations

  1. Department of Neurology, Neurological Institute, Columbia University Medical Center, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York, NY, 10032, USA

    Adu L. Matory, Ayham Alkhachroum, Wei-Ting Chiu, Andrey Eliseyev, Kevin Doyle, Benjamin Rohaut, Jennifer A. Egbebike, Angela G. Velazquez, Lucy Paniker, Sachin Agarwal, David Roh, Soojin Park & Jan Claassen

  2. Bernstein Center for Computational Neuroscience, Berlin, Germany

    Adu L. Matory

  3. Department of Neurology, University of Miami, Miami, FL, USA

    Ayham Alkhachroum

  4. Department of Neurology, Shuang Ho Hospital, Taipei Medical University, Taipei, Taiwan

    Wei-Ting Chiu

  5. Department of Neurology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan

    Wei-Ting Chiu

  6. Taipei Neuroscience Institute, Taipei Medical University, Taipei, Taiwan

    Wei-Ting Chiu

  7. Division of Critical Care Medicine, Department of Emergency and Critical Care Medicine, Shuang Ho Hospital, Taipei Medical University, Taipei, Taiwan

    Wei-Ting Chiu

  8. Brain institute - ICM, Inserm U1127, CNRS UMR 7225, Sorbonne Université, Paris, France

    Benjamin Rohaut

  9. Department of Neurology, Neuro-ICU, Groupe Hospitalier Universitaire APHP, Pitié-Salpêtrière, Sorbonne Université, Paris, France

    Benjamin Rohaut

  10. Sorbonne Université, Paris, France

    Benjamin Rohaut

  11. Pharmacy, Columbia University Irving Medical Center, New York, NY, USA

    Caroline Der-Nigoghossian

  12. Clinical Ethics, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA

    Kenneth M. Prager

Authors
  1. Adu L. Matory
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ayham Alkhachroum
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wei-Ting Chiu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Andrey Eliseyev
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kevin Doyle
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Benjamin Rohaut
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jennifer A. Egbebike
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Angela G. Velazquez
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Caroline Der-Nigoghossian
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Lucy Paniker
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Kenneth M. Prager
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Sachin Agarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. David Roh
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Soojin Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Jan Claassen
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

ALM and JC contributed to the design of the study, analysis and writing of the manuscript. AE, KD, and BR contributed to the analysis and writing of the manuscript. AA, WC, CD, KMP, SA, DR, and SP provided helpful edits for the manuscript. JAE, AGV, and LP provided data collection and helpful edits for the manuscript.

Corresponding author

Correspondence to Jan Claassen.

Ethics declarations

Conflicts of Interest

JC reports grants from the National Institute of Neurological Disorders and Stroke and the Dana Foundation. He is a minority shareholder at iCE Neurosystems. None of these constitute a conflict of interest to the work presented here. The remaining authors do not have any conflicts of interest.

Ethical approval/informed consent

We confirm adherence to ethical guidelines and indicate ethical approvals (local institutional review board, IRB-AAAL4106) and the use of informed consent, as appropriate. Because this was a retrospective study approved by the local institutional review board at Columbia University, informed consent was waived per section IV of the local institutional review board’s Health Insurance Portability and Accountability Act policy, citing 45 CFR 164.512(i)(1)(iii).

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

12028_2021_1233_MOESM1_ESM.tiff

Supplemental Figure 1 Change in full-spectrum EEG features after CBF0. Change in epoch-averaged, full-spectrum EEG features 5 minutes before vs. 5 minutes after CBF0 for patients 1 – 19. Patients are ordered by magnitude of change in global power five minutes before CBF0 vs. five minutes after. For log-power, values between channel locations are interpolated with a linear radial basis function kernel. For coherence, the color of channel-connecting lines encodes coherence change and the color of the channel encodes the average channel coherence. A high-pass threshold was applied to coherence values. Cohort-wide changes in log-power and coherence are statistically significant (p<0.028). (TIFF 2333 kb)

12028_2021_1233_MOESM2_ESM.tiff

Supplemental Figure 2 Raw EEG in a patient with electrocerebral activity on EEG after death declaration. Raw EEG displayed in a bipolar montage at time of (A) non-convulsive status epilepticus (NCSE), (B) cessation of cerebral blood flow (CBF0), (C) start of chest compressions (CC), and (D) end of chest compressions (CC_end). Raw EEG data at each event are shown. Sensitivity is 5 μV/mm, with 60 Hz filter artifacts on. (TIFF 5616 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Matory, A.L., Alkhachroum, A., Chiu, WT. et al. Electrocerebral Signature of Cardiac Death. Neurocrit Care 35, 853–861 (2021). https://doi.org/10.1007/s12028-021-01233-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12028-021-01233-0

Keywords

  • Death
  • Encephalography
  • Consciousness
  • Cardiac arrest
  • Brain hypoxia
  • Hypotension