Association Between EEG Patterns and Serum Neurofilament Light After Cardiac Arrest: A Post Hoc Analysis of the TTM Trial

Linnéa Grindegård, Tobias Cronberg, Sofia Backman, Kaj Blennow, Josef Dankiewicz, Hans Friberg, Christian Hassager, Janneke Horn, Troels W Kjaer, Jesper Kjaergaard, Michael Kuiper, Niklas Mattsson-Carlgren, Niklas Nielsen, Anne-Fleur van Rootselaar, Andrea O Rossetti, Pascal Stammet, Susann Ullén, Henrik Zetterberg, Erik Westhall, Marion Moseby-Knappe, Linnéa Grindegård, Tobias Cronberg, Sofia Backman, Kaj Blennow, Josef Dankiewicz, Hans Friberg, Christian Hassager, Janneke Horn, Troels W Kjaer, Jesper Kjaergaard, Michael Kuiper, Niklas Mattsson-Carlgren, Niklas Nielsen, Anne-Fleur van Rootselaar, Andrea O Rossetti, Pascal Stammet, Susann Ullén, Henrik Zetterberg, Erik Westhall, Marion Moseby-Knappe

Abstract

Background and objectives: EEG is widely used for prediction of neurologic outcome after cardiac arrest. To better understand the relationship between EEG and neuronal injury, we explored the association between EEG and neurofilament light (NfL) as a marker of neuroaxonal injury, evaluated whether highly malignant EEG patterns are reflected by high NfL levels, and explored the association of EEG backgrounds and EEG discharges with NfL.

Methods: We performed a post hoc analysis of the Target Temperature Management After Out-of-Hospital Cardiac Arrest trial. Routine EEGs were prospectively performed after the temperature intervention ≥36 hours postarrest. Patients who awoke or died prior to 36 hours postarrest were excluded. EEG experts blinded to clinical information classified EEG background, amount of discharges, and highly malignant EEG patterns according to the standardized American Clinical Neurophysiology Society terminology. Prospectively collected serum samples were analyzed for NfL after trial completion. The highest available concentration at 48 or 72 hours postarrest was used.

Results: A total of 262/939 patients with EEG and NfL data were included. Patients with highly malignant EEG patterns had 2.9 times higher NfL levels than patients with malignant patterns and NfL levels were 13 times higher in patients with malignant patterns than those with benign patterns (95% CI 1.4-6.1 and 6.5-26.2, respectively; effect size 0.47; p < 0.001). Both background and the amount of discharges were independently strongly associated with NfL levels (p < 0.001). The EEG background had a stronger association with NfL levels than EEG discharges (R2 = 0.30 and R2 = 0.10, respectively). NfL levels in patients with a continuous background were lower than for any other background (95% CI for discontinuous, burst-suppression, and suppression, respectively: 2.26-18.06, 3.91-41.71, and 5.74-41.74; effect size 0.30; p < 0.001 for all). NfL levels did not differ between suppression and burst suppression. Superimposed discharges were only associated with higher NfL levels if the EEG background was continuous.

Discussion: Benign, malignant, and highly malignant EEG patterns reflect the extent of brain injury as measured by NfL in serum. The extent of brain injury is more strongly related to the EEG background than superimposed discharges. Combining EEG and NfL may be useful to better identify patients misclassified by single methods.

Trial registration information: ClinicalTrials.gov NCT01020916.

Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

Figures

Figure 1. Flow Chart of Patient Inclusion
Figure 1. Flow Chart of Patient Inclusion
The modified intention-to-treat population in the Target Temperature Management After Out-of-Hospital Cardiac Arrest trial (TTM-trial) consisted of 939 patients. Nine study sites were excluded due to technical issues in providing EEGs for export in sufficient quality required for centralized evaluation. EEG: routine EEG performed after rewarming but

Figure 2. Highly Malignant, Malignant, and Benign…

Figure 2. Highly Malignant, Malignant, and Benign EEG Patterns and Serum NfL

Boxplot demonstrating logarithmic…

Figure 2. Highly Malignant, Malignant, and Benign EEG Patterns and Serum NfL
Boxplot demonstrating logarithmic peak neurofilament light (NfL) levels (highest serum neurofilament levels at either 48 or 72 hours postarrest) for EEG patterns as defined by Westhall et al.: “highly malignant”: burst-suppression or suppression with or without discharges; “malignant”: discontinuous, reversed anterio-posterior gradient or low-voltage background, abundant rhythmic or periodic discharges or unequivocal seizures; “benign”: continuous background without malignant features. Neurologic outcome for each patient is indicated through “X” (poor outcome, Cerebral Performance Category [CPC] 3–5) or “O” (good outcome, CPC 1–2) at 6 months’ follow-up. Peak NfL was increasingly higher in more malignant EEG patterns (p < 0.001).

Figure 3. EEG Background, Discharges, and Serum…

Figure 3. EEG Background, Discharges, and Serum NfL

Boxplots demonstrating logarithmic peak neurofilament light (NfL)…

Figure 3. EEG Background, Discharges, and Serum NfL
Boxplots demonstrating logarithmic peak neurofilament light (NfL) according to EEG background (A) or the presence of discharges (B). Neurologic outcome for each patient is indicated through “X” (poor outcome, Cerebral Performance Category [CPC] 3–5) or “O” (good outcome, CPC 1–2) at 6 months’ follow-up. The highest peak NfL levels were seen in patients with burst-suppression or suppression. In patients with a continuous background, patients with poor outcome had higher NfL levels than did patients with good outcome (median 60.7 [interquartile range (IQR) 32.8–118.7] pg/mL vs median 998.3 [IQR 366.0–3,449.7] pg/mL; p < 0.005). Peak NfL was higher in patients with an abundant amount of discharges than in patients without discharges (p < 0.001). In patients without discharges, NfL levels were higher in patients with poor outcome than in patients with good outcome (median 60.7 [IQR 32.9–128.4] pg/mL vs median 5,305.5 [IQR 1,064.8–12,926.6] pg/mL; p < 0.005).

Figure 4. EEG Background, Superimposed Discharges, and…

Figure 4. EEG Background, Superimposed Discharges, and Serum NfL

Boxplot demonstrating logarithmic peak neurofilament light…

Figure 4. EEG Background, Superimposed Discharges, and Serum NfL
Boxplot demonstrating logarithmic peak neurofilament light (NfL) in patients with continuous, discontinuous, burst-suppression, and suppressed EEG background and the presence of superimposed discharges. Neurologic outcome for each patient is indicated through “X” (poor outcome, Cerebral Performance Category [CPC] 3–5) or “O” (good outcome, CPC 1–2) at 6 months’ follow-up. In patients with a continuous background, NfL levels were higher in patients with an intermediate or abundant amount of discharges than in patients without discharges (p < 0.001). No other differences could be found between noncontinuous backgrounds and the presence of discharges.
Figure 2. Highly Malignant, Malignant, and Benign…
Figure 2. Highly Malignant, Malignant, and Benign EEG Patterns and Serum NfL
Boxplot demonstrating logarithmic peak neurofilament light (NfL) levels (highest serum neurofilament levels at either 48 or 72 hours postarrest) for EEG patterns as defined by Westhall et al.: “highly malignant”: burst-suppression or suppression with or without discharges; “malignant”: discontinuous, reversed anterio-posterior gradient or low-voltage background, abundant rhythmic or periodic discharges or unequivocal seizures; “benign”: continuous background without malignant features. Neurologic outcome for each patient is indicated through “X” (poor outcome, Cerebral Performance Category [CPC] 3–5) or “O” (good outcome, CPC 1–2) at 6 months’ follow-up. Peak NfL was increasingly higher in more malignant EEG patterns (p < 0.001).
Figure 3. EEG Background, Discharges, and Serum…
Figure 3. EEG Background, Discharges, and Serum NfL
Boxplots demonstrating logarithmic peak neurofilament light (NfL) according to EEG background (A) or the presence of discharges (B). Neurologic outcome for each patient is indicated through “X” (poor outcome, Cerebral Performance Category [CPC] 3–5) or “O” (good outcome, CPC 1–2) at 6 months’ follow-up. The highest peak NfL levels were seen in patients with burst-suppression or suppression. In patients with a continuous background, patients with poor outcome had higher NfL levels than did patients with good outcome (median 60.7 [interquartile range (IQR) 32.8–118.7] pg/mL vs median 998.3 [IQR 366.0–3,449.7] pg/mL; p < 0.005). Peak NfL was higher in patients with an abundant amount of discharges than in patients without discharges (p < 0.001). In patients without discharges, NfL levels were higher in patients with poor outcome than in patients with good outcome (median 60.7 [IQR 32.9–128.4] pg/mL vs median 5,305.5 [IQR 1,064.8–12,926.6] pg/mL; p < 0.005).
Figure 4. EEG Background, Superimposed Discharges, and…
Figure 4. EEG Background, Superimposed Discharges, and Serum NfL
Boxplot demonstrating logarithmic peak neurofilament light (NfL) in patients with continuous, discontinuous, burst-suppression, and suppressed EEG background and the presence of superimposed discharges. Neurologic outcome for each patient is indicated through “X” (poor outcome, Cerebral Performance Category [CPC] 3–5) or “O” (good outcome, CPC 1–2) at 6 months’ follow-up. In patients with a continuous background, NfL levels were higher in patients with an intermediate or abundant amount of discharges than in patients without discharges (p < 0.001). No other differences could be found between noncontinuous backgrounds and the presence of discharges.

References

    1. Friberg H, Cronberg T, Dünser MW, Duranteau J, Horn J, Oddo M. Survey on current practices for neurological prognostication after cardiac arrest. Resuscitation. 2015;90:158-162.
    1. Jørgensen EO, Malchow-Møller A. Natural history of global and critical brain ischaemia: part II: EEG and neurological signs in patients remaining unconscious after cardiopulmonary resuscitation. Resuscitation. 1981;9(2):155-174.
    1. Raffin CN, Harrison M, Sick TJ, Rosenthal M. EEG suppression and anoxic depolarization: influences on cerebral oxygenation during ischemia. J Cereb Blood Flow Metab. 1991;11(3):407-415.
    1. Rossetti AO, Tovar Quiroga DF, Juan E, et al. . Electroencephalography predicts poor and good outcomes after cardiac arrest: a two-center study. Crit Care Med. 2017;45(7):e674-e682.
    1. Ruijter BJ, Tjepkema-Cloostermans MC, Tromp SC, et al. . Early electroencephalography for outcome prediction of postanoxic coma: a prospective cohort study. Ann Neurol. 2019;86(2):203-214.
    1. Cloostermans MC, van Meulen FB, Eertman CJ, Hom HW, van Putten MJ. Continuous electroencephalography monitoring for early prediction of neurological outcome in postanoxic patients after cardiac arrest: a prospective cohort study. Crit Care Med. 2012;40(10):2867-2875.
    1. Westhall E, Rossetti AO, van Rootselaar AF, et al. . Standardized EEG interpretation accurately predicts prognosis after cardiac arrest. Neurology. 2016;86(16):1482-1490.
    1. 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.
    1. Duez CHV, Johnsen B, Ebbesen MQ, et al. . Post resuscitation prognostication by EEG in 24 vs 48 h of targeted temperature management. Resuscitation. 2019;135:145-152.
    1. Backman S, Cronberg T, Friberg H, et al. . Highly malignant routine EEG predicts poor prognosis after cardiac arrest in the Target Temperature Management trial. Resuscitation. 2018;131:24-28.
    1. Sandroni C, D'Arrigo S, Cacciola S, et al. . Prediction of poor neurological outcome in comatose survivors of cardiac arrest: a systematic review. Intens Care Med. 2020;46(10):1803-1851.
    1. Nolan JP, Sandroni C, Bottiger BW, et al. . European Resuscitation Council and European Society of Intensive Care Medicine Guidelines 2021: post-resuscitation care. Intens Care Med. 2022;172:229-236.
    1. Ruijter BJ, van Putten MJ, Hofmeijer J. Generalized epileptiform discharges in postanoxic encephalopathy: quantitative characterization in relation to outcome. Epilepsia. 2015;56(11):1845-1854.
    1. Barbella G, Lee JW, Alvarez V, et al. . Prediction of regaining consciousness despite an early epileptiform EEG after cardiac arrest. Neurology. 2020;94(16):e1675-e1683.
    1. Eastwood GM, Schneider AG, Suzuki S, et al. . Targeted therapeutic mild hypercapnia after cardiac arrest: a phase II multi-centre randomised controlled trial (the CCC trial). Resuscitation. 2016;104:83-90.
    1. Jakkula P, Pettilä V, Skrifvars MB, et al. . Targeting low-normal or high-normal mean arterial pressure after cardiac arrest and resuscitation: a randomised pilot trial. Intens Care Med. 2018;44(12):2091-2101.
    1. Moseby-Knappe M, Mattsson N, Nielsen N, et al. . Serum neurofilament light chain for prognosis of outcome after cardiac arrest. JAMA Neurol. 2019;76:64-71.
    1. Wihersaari L, Ashton NJ, Reinikainen M, et al. . Neurofilament light as an outcome predictor after cardiac arrest: a post hoc analysis of the COMACARE trial. Intens Care Med. 2021;47(1):39-48.
    1. Nielsen N, Wetterslev J, Cronberg T, et al. . Targeted temperature management at 33 degrees C versus 36 degrees C after cardiac arrest. N Engl J Med. 2013;369:2197-2206.
    1. Nielsen N, Winkel P, Cronberg T, et al. . Detailed statistical analysis plan for the target temperature management after out-of-hospital cardiac arrest trial. Trials. 2013;14:300.
    1. Lybeck A, Friberg H, Aneman A, et al. . Prognostic significance of clinical seizures after cardiac arrest and target temperature management. Resuscitation. 2017;114:146-151.
    1. Dragancea I, Wise MP, Al-Subaie N, et al. . Protocol-driven neurological prognostication and withdrawal of life-sustaining therapy after cardiac arrest and targeted temperature management. Resuscitation. 2017;117:50-57.
    1. Dragancea I, Horn J, Kuiper M, et al. . Neurological prognostication after cardiac arrest and targeted temperature management 33°C versus 36°C: results from a randomised controlled clinical trial. Resuscitation. 2015;93:164-170.
    1. Lybeck A, Cronberg T, Aneman A, et al. . Time to awakening after cardiac arrest and the association with target temperature management. Resuscitation. 2018;126:166-171.
    1. World Medical Association. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310:2191-2194.
    1. Nielsen N, Wetterslev J, al-Subaie N, et al. . Target temperature management after out-of-hospital cardiac arrest: a randomized, parallel-group, assessor-blinded clinical trial: rationale and design. Am Heart J. 2012;163(4):541-548.
    1. Stammet P, Collignon O, Hassager C, et al. . Neuron-specific enolase as a predictor of death or poor neurological outcome after out-of-hospital cardiac arrest and targeted temperature management at 33°C and 36°C. J Am Coll Cardiol. 2015;65:2104-2114.
    1. Westhall E, Rosen I, Rossetti AO, et al. . Electroencephalography (EEG) for neurological prognostication after cardiac arrest and targeted temperature management; rationale and study design. BMC Neurol. 2014;14:159.
    1. Endisch C, Westhall E, Kenda M, et al. . Hypoxic-ischemic encephalopathy evaluated by brain autopsy and neuroprognostication after cardiac arrest. JAMA Neurol. 2020;77(11):1430-1439.
    1. Steriade M, Amzica F, Contreras D. Cortical and thalamic cellular correlates of electroencephalographic burst-suppression. Electroencephalogr Clin Neurophysiol. 1994;90(1):1-16.
    1. Hofmeijer J, Tjepkema-Cloostermans MC, van Putten MJ. Burst-suppression with identical bursts: a distinct EEG pattern with poor outcome in postanoxic coma. Clin Neurophysiol. 2014;125(5):947-954.
    1. Ruijter BJ, van Putten MJAM, van den Bergh WM, Tromp SC, Hofmeijer J. Propofol does not affect the reliability of early EEG for outcome prediction of comatose patients after cardiac arrest. Clin Neurophysiol. 2019;130(8):1263-1270.
    1. Hviid CVB, Knudsen CS, Parkner T. Reference interval and preanalytical properties of serum neurofilament light chain in Scandinavian adults. Scand J Clin Lab Invest. 2020;80(4):291-295.
    1. Ruijter BJ, Hofmeijer J, Meijer HGE, van Putten MJAM. Synaptic damage underlies EEG abnormalities in postanoxic encephalopathy: a computational study. Clin Neurophysiol. 2017;128(9):1682-1695.
    1. Hofmeijer J, Beernink TM, Bosch FH, Beishuizen A, Tjepkema-Cloostermans MC, van Putten MJ. Early EEG contributes to multimodal outcome prediction of postanoxic coma. Neurology. 2015;85(2):137-143.
    1. Lybeck A, Friberg H, Nielsen N, et al. . Postanoxic electrographic status epilepticus and serum biomarkers of brain injury. Resuscitation. 2021;158:253-257.
    1. Rossetti AO, Carrera E, Oddo M. Early EEG correlates of neuronal injury after brain anoxia. Neurology. 2012;78(11):796-802.
    1. van Putten MJ, Hofmeijer J. Generalized periodic discharges: pathophysiology and clinical considerations. Epilepsy Behav. 2015;49:228-233.
    1. Yemisci M, Gurer G, Saygi S, Ciger A. Generalised periodic epileptiform discharges: clinical features, neuroradiological evaluation and prognosis in 37 adult patients. Seizure. 2003;12(7):465-472.
    1. Tjepkema-Cloostermans MC, Hindriks R, Hofmeijer J, van Putten MJ. Generalized periodic discharges after acute cerebral ischemia: reflection of selective synaptic failure? Clin Neurophysiol. 2014;125:255-262.
    1. Disanto G, Prosperetti C, Gobbi C, et al. . Serum neurofilament light chain as a prognostic marker in postanoxic encephalopathy. Epilepsy Behav. 2019;101(pt B):106432.
    1. Dragancea I, Backman S, Westhall E, Rundgren M, Friberg H, Cronberg T. Outcome following postanoxic status epilepticus in patients with targeted temperature management after cardiac arrest. Epilepsy Behav. 2015;49:173-177.
    1. Moseby-Knappe M, Mattsson-Carlgren N, Stammet P, et al. . Serum markers of brain injury can predict good neurological outcome after out-of-hospital cardiac arrest. Intensive Care Med. 2021;47:984-994.
    1. Cronberg T, Horn J, Kuiper MA, Friberg H, Nielsen N. A structured approach to neurologic prognostication in clinical cardiac arrest trials. Scand J Trauma Resusc Emerg Med. 2013;21:45.
    1. 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):1-29.
    1. Moseby-Knappe M, Cronberg T. Blood biomarkers of brain injury after cardiac arrest: a dynamic field. Resuscitation. 2020;156:273-276.

Source: PubMed

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