Prognostic and diagnostic value of EEG signal coupling measures in coma

OBJECTIVE Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients. METHODS In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. RESULTS Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). CONCLUSIONS EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. SIGNIFICANCE Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches.

[1]  Peter Achermann,et al.  Frequency and state specific hemispheric asymmetries in the human sleep EEG , 1999, Neuroscience Letters.

[2]  Claudio Pollo,et al.  Detecting Functional Hubs of Ictogenic Networks , 2014, Brain Topography.

[3]  V. Synek Value of a Revised EEG Coma Scale for Prognosis after Cerebral Anoxia and Diffuse Head Injury , 1990, Clinical EEG.

[4]  Kaspar Anton Schindler,et al.  Assessing seizure dynamics by analysing the correlation structure of multichannel intracranial EEG. , 2006, Brain : a journal of neurology.

[5]  Mark D. Huffman,et al.  Heart disease and stroke statistics--2013 update: a report from the American Heart Association. , 2013, Circulation.

[6]  M. Kramer,et al.  Coalescence and Fragmentation of Cortical Networks during Focal Seizures , 2010, The Journal of Neuroscience.

[7]  C. Stam,et al.  Functional and structural brain networks in epilepsy: What have we learned? , 2013, Epilepsia.

[8]  C W Hess,et al.  Early prognosis in coma after cardiac arrest: a prospective clinical, electrophysiological, and biochemical study of 60 patients. , 1996, Journal of neurology, neurosurgery, and psychiatry.

[9]  G. Tononi,et al.  Local sleep in awake rats , 2011, Nature.

[10]  C. Stam,et al.  The organization of physiological brain networks , 2012, Clinical Neurophysiology.

[11]  Jan Claassen,et al.  Recommendations on the use of EEG monitoring in critically ill patients: consensus statement from the neurointensive care section of the ESICM , 2013, Intensive Care Medicine.

[12]  K. Biagas Hypoxic-ischemic brain injury: advancements in the understanding of mechanisms and potential avenues for therapy. , 1999, Current opinion in pediatrics.

[13]  Schreiber,et al.  Measuring information transfer , 2000, Physical review letters.

[14]  S. Dehaene,et al.  Information Sharing in the Brain Indexes Consciousness in Noncommunicative Patients , 2013, Current Biology.

[15]  Matthäus Staniek,et al.  Symbolic transfer entropy. , 2008, Physical review letters.

[16]  J. Soar,et al.  Prognostication in comatose survivors of cardiac arrest: An advisory statement from the European Resuscitation Council and the European Society of Intensive Care Medicine , 2014, Intensive Care Medicine.

[17]  K. Jordan,et al.  Emergency EEG and Continuous EEG Monitoring in Acute Ischemic Stroke , 2004, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[18]  Nasser M. Nasrabadi,et al.  Pattern Recognition and Machine Learning , 2006, Technometrics.

[19]  R. Howard,et al.  Hypoxic-ischaemic brain injury , 2011, Practical Neurology.

[20]  A. Rossetti,et al.  Early Multimodal Outcome Prediction After Cardiac Arrest in Patients Treated With Hypothermia* , 2014, Critical care medicine.

[21]  L. Tsimring,et al.  Generalized synchronization of chaos in directionally coupled chaotic systems. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[22]  Michel J. A. M. van Putten,et al.  The revised brain symmetry index , 2007, Clinical Neurophysiology.

[23]  G. Tononi,et al.  The cortical topography of local sleep. , 2011, Current topics in medicinal chemistry.

[24]  Roger D. White,et al.  The Role of EEG after Cardiac Arrest and Hypothermia , 2013, Epilepsy currents.

[25]  M. Boly,et al.  Breakdown of within- and between-network Resting State Functional Magnetic Resonance Imaging Connectivity during Propofol-induced Loss of Consciousness , 2010, Anesthesiology.

[26]  Gjerrit Meinsma,et al.  A Cerebral Recovery Index (CRI) for early prognosis in patients after cardiac arrest , 2013, Critical Care.

[27]  J. Binnekade,et al.  Prognostication of neurologic outcome in cardiac arrest patients after mild therapeutic hypothermia: a meta-analysis of the current literature , 2013, Intensive Care Medicine.

[28]  J. Vincent,et al.  How to assess prognosis after cardiac arrest and therapeutic hypothermia , 2014, Critical Care.

[29]  M. Boly,et al.  Brain Connectivity in Pathological and Pharmacological Coma , 2010, Front. Syst. Neurosci..

[30]  M. V. van Putten,et al.  Electroencephalogram Predicts Outcome in Patients With Postanoxic Coma During Mild Therapeutic Hypothermia* , 2015, Critical care medicine.

[31]  UnCheol Lee,et al.  Disruption of Frontal–Parietal Communication by Ketamine, Propofol, and Sevoflurane , 2013, Anesthesiology.

[32]  L. Mukhametov,et al.  Unihemispheric slow-wave sleep in the Amazonian dolphin, Inia geoffrensis , 1987, Neuroscience Letters.

[33]  S. Mayer,et al.  Continuous electroencephalography in the medical intensive care unit* , 2009, Critical care medicine.

[34]  Anthony G. Hudetz,et al.  Volatile anesthetics disrupt frontal-posterior recurrent information transfer at gamma frequencies in rat , 2005, Neuroscience Letters.

[35]  UnCheol Lee,et al.  The directionality and functional organization of frontoparietal connectivity during consciousness and anesthesia in humans , 2009, Consciousness and Cognition.

[36]  E. Wijdicks,et al.  Diagnosis of reversible causes of coma , 2014, The Lancet.

[37]  David M. Groppe,et al.  Mass univariate analysis of event-related brain potentials/fields I: a critical tutorial review. , 2011, Psychophysiology.

[38]  M. Sigman,et al.  Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state. , 2014, Brain : a journal of neurology.

[39]  Maxim Bazhenov,et al.  The Impact of Cortical Deafferentation on the Neocortical Slow Oscillation , 2014, The Journal of Neuroscience.

[40]  Jan Claassen,et al.  Quantitative EEG for the detection of brain ischemia , 2012, Critical Care.

[41]  G. B. Young,et al.  Clinical practice. Neurologic prognosis after cardiac arrest. , 2009, The New England journal of medicine.

[42]  Michel J. A. M. van Putten,et al.  Continuous electroencephalography monitoring for early prediction of neurological outcome in postanoxic patients after cardiac arrest: A prospective cohort study* , 2012, Critical care medicine.

[43]  J. Gotman,et al.  Automatic seizure detection in the newborn: methods and initial evaluation. , 1997, Electroencephalography and clinical neurophysiology.

[44]  Mauro Oddo,et al.  Prognostication after cardiac arrest and hypothermia: A prospective study , 2010, Annals of neurology.

[45]  Michel J. A. M. van Putten,et al.  Burst-suppression with identical bursts: A distinct EEG pattern with poor outcome in postanoxic coma , 2014, Clinical Neurophysiology.

[46]  Kaspar Anton Schindler,et al.  Ordinal patterns in epileptic brains: Analysis of intracranial EEG and simultaneous EEG-fMRI , 2013, The European Physical Journal Special Topics.

[47]  Jan Claassen,et al.  Quantitative continuous EEG for detecting delayed cerebral ischemia in patients with poor-grade subarachnoid hemorrhage , 2004, Clinical Neurophysiology.

[48]  V. Lagerburg,et al.  Detecting temporal lobe seizures from scalp EEG recordings: A comparison of various features , 2005, Clinical Neurophysiology.

[49]  G. B. Young,et al.  Practice Parameter: Prediction of outcome in comatose survivors after cardiopulmonary resuscitation (an evidence-based review) , 2006, Neurology.

[50]  D. L. Schomer,et al.  Niedermeyer's Electroencephalography: Basic Principles, Clinical Applications, and Related Fields , 2012 .

[51]  Igor Timofeev,et al.  Partial cortical deafferentation promotes development of paroxysmal activity. , 2003, Cerebral cortex.

[52]  C. Finney,et al.  A review of symbolic analysis of experimental data , 2003 .

[53]  C. Stam,et al.  Synchronization likelihood: an unbiased measure of generalized synchronization in multivariate data sets , 2002 .

[54]  Michel J A M van Putten,et al.  Continuous Quantitative EEG Monitoring in Hemispheric Stroke Patients Using the Brain Symmetry Index , 2004, Stroke.

[55]  M. Putten,et al.  A novel approach for computer assisted EEG monitoring in the adult ICU , 2011, Clinical Neurophysiology.

[56]  J. Sarnthein,et al.  Inter-Hemispheric Oscillations in Human Sleep , 2012, PloS one.

[57]  K. Sacco,et al.  Disrupted intrinsic functional connectivity in the vegetative state , 2008, Journal of Neurology, Neurosurgery, and Psychiatry.

[58]  R. Stevens,et al.  Continuous Electroencephalographic Monitoring in Critically Ill Patients: Indications, Limitations, and Strategies* , 2013, Critical care medicine.

[59]  I. Rosén,et al.  Continuous amplitude-integrated electroencephalogram predicts outcome in hypothermia-treated cardiac arrest patients , 2010, Critical care medicine.

[60]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[61]  David L McArthur,et al.  Cortical synchrony changes detected by scalp electrode electroencephalograph as traumatic brain injury patients emerge from coma. , 2007, Surgical neurology.

[62]  Mauro Oddo,et al.  Early EEG correlates of neuronal injury after brain anoxia , 2012, Neurology.

[63]  A A Borbély,et al.  Brain topography of the human sleep EEG: antero‐posterior shifts of spectral power , 1996, Neuroreport.

[64]  T. Cronberg,et al.  Long-term neurological outcome after cardiac arrest and therapeutic hypothermia. , 2009, Resuscitation.