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Background EEG Suppression Ratio for Early Detection of Cerebral Injury in Pediatric Cardiac Arrest

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Abstract

Background

Our objective was to assess the utility of the 1-h suppression ratio (SR) as a biomarker of cerebral injury and neurologic prognosis after cardiac arrest (CA) in the pediatric hospital setting.

Methods

Prospectively, we reviewed data from children presenting after CA and monitored by continuous electroencephalography (cEEG). Patients aged 1 month to 21 years were included. The SR, a quantitative measure of low-voltage cEEG (≤ 3 µV) content, was dichotomized as present or absent if there was > 0% suppression for one continuous hour. A multivariate logistic regression analysis was performed including age, sex, type of CA (i.e., in-hospital or out-of-hospital), and the presence of SR as a predictor of global anoxic cerebral injury as confirmed by magnetic resonance imaging (MRI).

Results

We included 84 patients with a median age of 4 years (interquartile range 0.9–13), 64% were male, and 49% (41/84) had in-hospital CA. Cerebral injury was seen in 50% of patients, of whom 65% had global injury. One-hour SR presence, independent of amount, predicted cerebral injury with 81% sensitivity (95% confidence interval (CI) (66–91%) and 98% specificity (95% CI 88–100%). Multivariate logistic regression analyses indicated that SR was a significant predictor of both cerebral injury (β = 6.28, p < 0.001) and mortality (β = 3.56, p < 0.001).

Conclusions

The SR a sensitive and specific marker of anoxic brain injury and post-CA mortality in the pediatric population. Once detected in the post-CA setting, the 1-h SR may be a useful threshold finding for deployment of early neuroprotective strategies prior or for prompting diagnostic neuroimaging.

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References

  1. Robinson JA, LaPage MJ, Atallah J, et al. Outcomes of pediatric patients with defibrillators following initial presentation with sudden cardiac arrest. Circ Arrhythm Electrophysiol. 2021;14:e008517.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Topjian AA, de Caen A, Wainwright MS, et al. Pediatric post-cardiac arrest care: a scientific statement from the American Heart Association. Circulation. 2019;140:e194–233.

    Article  PubMed  Google Scholar 

  3. Herman ST, Abend NS, Bleck TP, et al. Consensus statement on continuous EEG in critically ill adults and children, part I: indications. J Clin Neurophysiol. 2015;32:87–95.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Grundmann S, Busch HJ. Neurologic prognosis after cardiac arrest. N Engl J Med. 2009;361:1999 (author reply 1999–2000).

    Article  CAS  PubMed  Google Scholar 

  5. Nesseler N, Leurent G, Seguin P. Neurologic prognosis after cardiac arrest. N Engl J Med. 2009;361:1999 (author reply 1999–2000).

    Article  CAS  PubMed  Google Scholar 

  6. Young GB. Clinical practice. Neurologic prognosis after cardiac arrest. N Engl J Med. 2009;361:605–11.

    Article  CAS  PubMed  Google Scholar 

  7. Sansevere AJ, DiBacco ML, Akhondi-Asl A, et al. EEG features of brain injury during extracorporeal membrane oxygenation in children. Neurology. 2020;95:e1372–80.

    Article  PubMed  Google Scholar 

  8. Amorim E, Rittenberger JC, Baldwin ME, Callaway CW, Popescu A, Post Cardiac Arrest S. Malignant EEG patterns in cardiac arrest patients treated with targeted temperature management who survive to hospital discharge. Resuscitation. 2015;90:127–32.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Bevers MB, Scirica BM, Avery KR, Henderson GV, Lin AP, Lee JW. Combination of clinical exam, MRI and EEG to predict outcome following cardiac arrest and targeted temperature management. Neurocrit Care. 2018;29:396–403.

    Article  PubMed  Google Scholar 

  10. Ostendorf AP, Hartman ME, Friess SH. Early electroencephalographic findings correlate with neurologic outcome in children following cardiac arrest. Pediatr Crit Care Med. 2016;17:667–76.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Lee S, Zhao X, Davis KA, Topjian AA, Litt B, Abend NS. Quantitative EEG predicts outcomes in children after cardiac arrest. Neurology. 2019;92:e2329–38.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Sansevere AJ, Hahn CD, Abend NS. Conventional and quantitative EEG in status epilepticus. Seizure. 2019;68:38–45.

    Article  PubMed  Google Scholar 

  13. Stewart CP, Otsubo H, Ochi A, Sharma R, Hutchison JS, Hahn CD. Seizure identification in the ICU using quantitative EEG displays. Neurology. 2010;75:1501–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Swisher CB, Sinha SR. Utilization of quantitative EEG trends for critical care continuous EEG monitoring: a survey of neurophysiologists. J Clin Neurophysiol. 2016;33:538–44.

    Article  PubMed  Google Scholar 

  15. Du Pont-Thibodeau G, Sanchez SM, Jawad AF, et al. Seizure detection by critical care providers using amplitude-integrated electroencephalography and color density spectral array in pediatric cardiac arrest patients. Pediatr Crit Care Med. 2017;18:363–9.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Topjian AA, Fry M, Jawad AF, et al. Detection of electrographic seizures by critical care providers using color density spectral array after cardiac arrest is feasible. Pediatr Crit Care Med. 2015;16:461–7.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Dell’anna AM, Scolletta S, Donadello K, Taccone FS. Early neuroprotection after cardiac arrest. Curr Opin Crit Care. 2014;20:250–8.

    Article  PubMed  Google Scholar 

  18. Hirsch LJ, Fong MWK, Leitinger M, et al. American clinical neurophysiology society’s standardized critical care EEG terminology: 2021 version. J Clin Neurophysiol. 2021;38:1–29.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Hirsch LJ, LaRoche SM, Gaspard N, et al. American clinical neurophysiology society’s standardized critical care EEG terminology: 2012 version. J Clin Neurophysiol. 2013;30:1–27.

    Article  CAS  PubMed  Google Scholar 

  20. Abend NS, Gutierrez-Colina A, Zhao H, et al. Interobserver reproducibility of electroencephalogram interpretation in critically ill children. J Clin Neurophysiol. 2011;28:15–9.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Lewis DW, Johnson EL. Prognosis of periodic and rhythmic patterns in adult and pediatric populations. J Clin Neurophysiol. 2018;35:303–8.

    Article  PubMed  Google Scholar 

  22. Babcock DS, Han BK, Weiss RG, Ryckman FC. Brain abnormalities in infants on extracorporeal membrane oxygenation: sonographic and CT findings. AJR Am J Roentgenol. 1989;153:571–6.

    Article  CAS  PubMed  Google Scholar 

  23. LaRovere KL, Vonberg FW, Prabhu SP, et al. Patterns of head computed tomography abnormalities during pediatric extracorporeal membrane oxygenation and association with outcomes. Pediatr Neurol. 2017;73:64–70.

    Article  PubMed  Google Scholar 

  24. Sansevere AJ, Arya R, Sanchez Fernandez I, et al. Electroencephalographic reporting for refractory status epilepticus. J Clin Neurophysiol. 2019;36:365–70.

    Article  PubMed  Google Scholar 

  25. Abend NS, Topjian A, Ichord R, et al. Electroencephalographic monitoring during hypothermia after pediatric cardiac arrest. Neurology. 2009;72:1931–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Sansevere AJ, DiBacco ML, Pearl PL, Rotenberg A. Quantitative electroencephalography for early detection of elevated intracranial pressure in critically Ill children: case series and proposed protocol. J Child Neurol. 2022;37:5–11.

    Article  PubMed  Google Scholar 

  27. Munjal NK, Bergman I, Scheuer ML, Genovese CR, Simon DW, Patterson CM. Quantitative electroencephalography (EEG) predicting acute neurologic deterioration in the pediatric intensive care unit: a case series. J Child Neurol. 2022;37:73–9.

    Article  PubMed  Google Scholar 

  28. Ducharme-Crevier L, Press CA, Kurz JE, Mills MG, Goldstein JL, Wainwright MS. Early presence of sleep spindles on electroencephalography is associated with good outcome after pediatric cardiac arrest. Pediatr Crit Care Med. 2017;18:452–60.

    Article  PubMed  Google Scholar 

  29. Menache CC, Bourgeois BF, Volpe JJ. Prognostic value of neonatal discontinuous EEG. Pediatr Neurol. 2002;27:93–101.

    Article  PubMed  Google Scholar 

  30. Korotchikova I, Stevenson NJ, Walsh BH, Murray DM, Boylan GB. Quantitative EEG analysis in neonatal hypoxic ischaemic encephalopathy. Clin Neurophysiol. 2011;122:1671–8.

    Article  CAS  PubMed  Google Scholar 

  31. van’t Westende C, Geraedts VJ, van Ramesdonk T, et al. Neonatal quantitative electroencephalography and long-term outcomes: a systematic review. Dev Med Child Neurol. 2022;64:413–20.

    Article  PubMed  Google Scholar 

  32. Doyle OM, Greene BR, Murray DM, Marnane L, Lightbody G, Boylan GB. The effect of frequency band on quantitative EEG measures in neonates with hypoxic-ischaemic encephalopathy. Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:717–21.

    CAS  PubMed  Google Scholar 

  33. Kota S, Massaro AN, Chang T, et al. Prognostic value of continuous electroencephalogram delta power in neonates with hypoxic-ischemic encephalopathy. J Child Neurol. 2020;35:517–25.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Press CA, Morgan L, Mills M, et al. Spectral electroencephalogram analysis for the evaluation of encephalopathy grade in children with acute liver failure. Pediatr Crit Care Med. 2017;18:64–72.

    Article  PubMed  Google Scholar 

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Funding

This study is not funded.

Author information

Authors and Affiliations

  1. Division of Epilepsy and Neurophysiology, Boston Children’s Hospital, Boston, MA, USA

    Arnold J. Sansevere, Ali Janatti, Melissa L. DiBacco, Kelly Cavan & Alexander Rotenberg

  2. Department of Neurology, Boston Children’s Hospital, Boston, MA, USA

    Arnold J. Sansevere, Ali Janatti, Melissa L. DiBacco, Kelly Cavan & Alexander Rotenberg

  3. Division of Epilepsy, Department of Neurology, Children’s National Hospital, 111 Michigan Ave NW, Washington, DC, 20001, USA

    Arnold J. Sansevere

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Contributions

AJS participated in conception, study design, data collection, data analysis, manuscript preparation, editing and submission. As the primary author AJS takes full responsibility for all aspects of this work. AJ participated in study design, data analysis, manuscript preparation editing, and approval. MLD participated in study design, data collection, manuscript preparation, editing, and approval. KC participated in study design, data collection, manuscript preparation editing, and approval. AR participated in conception, study design, manuscript preparation, editing, and approval.

Corresponding author

Correspondence to Arnold J. Sansevere.

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Conflicts of interest

Melissa DiBacco is supported in part by the National Institute of Health/National Institute of Neurological Disorders and Stroke (R01 HD 091142). Dr. DiBacco is now employed at Agios Pharmaceuticals. The work represented in this article was completed prior to employment at Agios Pharmaceuticals, and there is no conflict of interest with the work represented in this article. For the remaining authors, no conflicts were declared.

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This article has not been submitted or published elsewhere and adheres to all ethical guidelines. This is an institution review board–approved study at our institution.

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Sansevere, A.J., Janatti, A., DiBacco, M.L. et al. Background EEG Suppression Ratio for Early Detection of Cerebral Injury in Pediatric Cardiac Arrest. Neurocrit Care (2024). https://doi.org/10.1007/s12028-023-01920-0

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  • DOI: https://doi.org/10.1007/s12028-023-01920-0

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