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Liuzzi P, Cassioli T, Secci S, Hakiki B, Scarpino M, Burali R, di Palma A, Toci T, Grippo A, Cecchi F, Frosini A, Mannini A. A neurophysiological profiling of the heartbeat-evoked potential in severe acquired brain injuries: A focus on unconsciousness. Eur J Neurosci 2024. [PMID: 38797841 DOI: 10.1111/ejn.16394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 04/26/2024] [Accepted: 05/01/2024] [Indexed: 05/29/2024]
Abstract
Unconsciousness in severe acquired brain injury (sABI) patients occurs with different cognitive and neural profiles. Perturbational approaches, which enable the estimation of proxies for brain reorganization, have added a new avenue for investigating the non-behavioural diagnosis of consciousness. In this prospective observational study, we conducted a comparative analysis of the topological patterns of heartbeat-evoked potentials (HEP) between patients experiencing a prolonged disorder of consciousness (pDoC) and patients emerging from a minimally consciousness state (eMCS). A total of 219 sABI patients were enrolled, each undergoing a synchronous EEG-ECG resting-state recording, together with a standardized consciousness diagnosis. A number of graph metrics were computed before/after the HEP (Before/After) using the R-peak on the ECG signal. The peak value of the global field power of the HEP was found to be significantly higher in eMCS patients with no difference in latency. Power spectrum was not able to discriminate consciousness neither Before nor After. Node assortativity and global efficiency were found to vary with different trends at unconsciousness. Lastly, the Perturbational Complexity Index of the HEP was found to be significantly higher in eMCS patients compared with pDoC. Given that cortical elaboration of peripheral inputs may serve as a non-behavioural determinant of consciousness, we have devised a low-cost and translatable technique capable of estimating causal proxies of brain functionality with an endogenous, non-invasive stimulus. Thus, we present an effective means to enhance consciousness assessment by incorporating the interaction between the autonomic nervous system (ANS) and central nervous system (CNS) into the loop.
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Affiliation(s)
- Piergiuseppe Liuzzi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
- Istituto di BioRobotica, Scuola Superiore Sant'Anna, Pisa, Italy
| | | | - Sara Secci
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
| | - Bahia Hakiki
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
- Dipartimento di Medicina Sperimentale e Clinica, Università di Firenze, Florence, Italy
| | | | - Rachele Burali
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
| | | | - Tanita Toci
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
| | | | - Francesca Cecchi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
- Dipartimento di Medicina Sperimentale e Clinica, Università di Firenze, Florence, Italy
| | - Andrea Frosini
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
- Dipartimento di Matematica Ulisse Dini, Università di Firenze, Florence, Italy
| | - Andrea Mannini
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Florence, Italy
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2
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Schiff ND. Toward an interventional science of recovery after coma. Neuron 2024; 112:1595-1610. [PMID: 38754372 DOI: 10.1016/j.neuron.2024.04.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 04/04/2024] [Accepted: 04/24/2024] [Indexed: 05/18/2024]
Abstract
Recovery of consciousness after coma remains one of the most challenging areas for accurate diagnosis and effective therapeutic engagement in the clinical neurosciences. Recovery depends on preservation of neuronal integrity and evolving changes in network function that re-establish environmental responsiveness. It typically occurs in defined steps: it begins with eye opening and unresponsiveness in a vegetative state, then limited recovery of responsiveness characterizes the minimally conscious state, and this is followed by recovery of reliable communication. This review considers several points for novel interventions, for example, in persons with cognitive motor dissociation in whom a hidden cognitive reserve is revealed. Circuit mechanisms underlying restoration of behavioral responsiveness and communication are discussed. An emerging theme is the possibility to rescue latent capacities in partially damaged human networks across time. These opportunities should be exploited for therapeutic engagement to achieve individualized solutions for restoration of communication and environmental interaction across varying levels of recovery.
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Affiliation(s)
- Nicholas D Schiff
- Jerold B. Katz Professor of Neurology and Neuroscience, Weill Cornell Medicine, New York, NY, USA.
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3
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Amiri M, Raimondo F, Fisher PM, Cacic Hribljan M, Sidaros A, Othman MH, Zibrandtsen I, Bergdal O, Fabritius ML, Hansen AE, Hassager C, Højgaard JLS, Jensen HR, Knudsen NV, Laursen EL, Møller JE, Nersesjan V, Nicolic M, Sigurdsson ST, Sitt JD, Sølling C, Welling KL, Willumsen LM, Hauerberg J, Larsen VA, Fabricius ME, Knudsen GM, Kjærgaard J, Møller K, Kondziella D. Multimodal Prediction of 3- and 12-Month Outcomes in ICU Patients with Acute Disorders of Consciousness. Neurocrit Care 2024; 40:718-733. [PMID: 37697124 PMCID: PMC10959792 DOI: 10.1007/s12028-023-01816-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 07/21/2023] [Indexed: 09/13/2023]
Abstract
BACKGROUND In intensive care unit (ICU) patients with coma and other disorders of consciousness (DoC), outcome prediction is key to decision-making regarding prognostication, neurorehabilitation, and management of family expectations. Current prediction algorithms are largely based on chronic DoC, whereas multimodal data from acute DoC are scarce. Therefore, the Consciousness in Neurocritical Care Cohort Study Using Electroencephalography and Functional Magnetic Resonance Imaging (i.e. CONNECT-ME; ClinicalTrials.gov identifier: NCT02644265) investigates ICU patients with acute DoC due to traumatic and nontraumatic brain injuries, using electroencephalography (EEG) (resting-state and passive paradigms), functional magnetic resonance imaging (fMRI) (resting-state) and systematic clinical examinations. METHODS We previously presented results for a subset of patients (n = 87) concerning prediction of consciousness levels in the ICU. Now we report 3- and 12-month outcomes in an extended cohort (n = 123). Favorable outcome was defined as a modified Rankin Scale score ≤ 3, a cerebral performance category score ≤ 2, and a Glasgow Outcome Scale Extended score ≥ 4. EEG features included visual grading, automated spectral categorization, and support vector machine consciousness classifier. fMRI features included functional connectivity measures from six resting-state networks. Random forest and support vector machine were applied to EEG and fMRI features to predict outcomes. Here, random forest results are presented as areas under the curve (AUC) of receiver operating characteristic curves or accuracy. Cox proportional regression with in-hospital death as a competing risk was used to assess independent clinical predictors of time to favorable outcome. RESULTS Between April 2016 and July 2021, we enrolled 123 patients (mean age 51 years, 42% women). Of 82 (66%) ICU survivors, 3- and 12-month outcomes were available for 79 (96%) and 77 (94%), respectively. EEG features predicted both 3-month (AUC 0.79 [95% confidence interval (CI) 0.77-0.82]) and 12-month (AUC 0.74 [95% CI 0.71-0.77]) outcomes. fMRI features appeared to predict 3-month outcome (accuracy 0.69-0.78) both alone and when combined with some EEG features (accuracies 0.73-0.84) but not 12-month outcome (larger sample sizes needed). Independent clinical predictors of time to favorable outcome were younger age (hazard ratio [HR] 1.04 [95% CI 1.02-1.06]), traumatic brain injury (HR 1.94 [95% CI 1.04-3.61]), command-following abilities at admission (HR 2.70 [95% CI 1.40-5.23]), initial brain imaging without severe pathological findings (HR 2.42 [95% CI 1.12-5.22]), improving consciousness in the ICU (HR 5.76 [95% CI 2.41-15.51]), and favorable visual-graded EEG (HR 2.47 [95% CI 1.46-4.19]). CONCLUSIONS Our results indicate that EEG and fMRI features and readily available clinical data predict short-term outcome of patients with acute DoC and that EEG also predicts 12-month outcome after ICU discharge.
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Affiliation(s)
- Moshgan Amiri
- Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Federico Raimondo
- Brain and Behaviour, Institute of Neuroscience and Medicine, Research Center Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Patrick M Fisher
- Neurobiology Research Unit, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Melita Cacic Hribljan
- Department of Neurophysiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Annette Sidaros
- Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark
- Department of Neurophysiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Marwan H Othman
- Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Ivan Zibrandtsen
- Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark
- Department of Neurophysiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Ove Bergdal
- Department of Neurosurgery, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Maria Louise Fabritius
- Department of Neuroanaesthesiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Adam Espe Hansen
- Department of Radiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Christian Hassager
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Joan Lilja S Højgaard
- Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Helene Ravnholt Jensen
- Department of Neuroanaesthesiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Niels Vendelbo Knudsen
- Department of Neuroanaesthesiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Emilie Lund Laursen
- Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark
| | - Jacob E Møller
- Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Vardan Nersesjan
- Biological and Precision Psychiatry, Copenhagen Research Center for Mental Health, Copenhagen University Hospital, Copenhagen, Denmark
| | - Miki Nicolic
- Department of Neurophysiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Sigurdur Thor Sigurdsson
- Department of Neuroanaesthesiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Jacobo D Sitt
- Institut du Cerveau - Paris Brain Institute, Inserm, Centre nationl de la recherche scientifique, Assistance Publique - Hôpitaux de Paris, Sorbonne Université, Hôpital de La Pitié Salpêtrière, Paris, France
| | - Christine Sølling
- Department of Neuroanaesthesiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Karen Lise Welling
- Department of Neuroanaesthesiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Lisette M Willumsen
- Department of Neurosurgery, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - John Hauerberg
- Department of Neurosurgery, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Vibeke Andrée Larsen
- Department of Radiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Martin Ejler Fabricius
- Department of Neurophysiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Gitte Moos Knudsen
- Neurobiology Research Unit, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Jesper Kjærgaard
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Kirsten Møller
- Department of Neuroanaesthesiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Daniel Kondziella
- Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark.
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.
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Wang Y, Liu W, Wang Y, Ouyang G, Guo Y. Long-term HD-tDCS modulates dynamic changes of brain activity on patients with disorders of consciousness: A resting-state EEG study. Comput Biol Med 2024; 170:108084. [PMID: 38295471 DOI: 10.1016/j.compbiomed.2024.108084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/10/2024] [Accepted: 01/27/2024] [Indexed: 02/02/2024]
Abstract
OBJECTIVE High-definition transcranial direct current stimulation (HD-tDCS) has been an effective neurostimulation method in the treatment of disorders of consciousness (DOC). However, the effects and mechanism of HD-tDCS are still unclear. METHODS This study recruited 8 DOC patients and applied 20-min sessions of 2 mA HD-tDCS (central anode electrode at Pz) for 14 consecutive days. We record DOC patients' EEG data and Coma Recovery Scale-Revised (CRS-R) values at four time point: baseline (T0), after 1 day's and 7,14 days' parietal HD-tDCS treatment (T1, T2, T3). Power spectral density (PSD), relative power (RP), spectral entropy and spectral exponent were calculated to evaluate the EEG dynamic changes of DOC patients during long-term parietal HD-tDCS. At last, we calculated the correlation between changes of EEG features and changes of CRS-R values. RESULT After 1 day's parietal HD-tDCS, DOC patients' CRS-R value had not changed (8.25 ± 1.91). HD-tDCS improved DOC patients' CRS-R value at T2 (9.75 ± 1.91, p < 0.05) and at T3 (11.38 ± 2.77, p < 0.05), compared with that at T0 (8.25 ± 1.91). As the treatment time increased, the EEG PSD decayed more slowly. Specifically, the delta frequency band RP decreased, while the alpha, beta, and gamma frequency bands RP increased. EEG oscillation characteristics changed but not significant at T1 (p > 0.05), and showed significant changes at T2 and T3 (p < 0.05). The spectral entropy continuously increased and the spectral exponent continuously decreased from T0 to T3. Specifically, the spectral entropy and spectral exponent of the parietal and occipital regions were significantly higher at T2 and T3 than that at T0 (p < 0.05). In addition, The changes in EEG features of the parietal and occipital lobes were correlated with changes in CRS-R value, especially between T2 and T0. CONCLUSION Long-term parietal HD-tDCS can improve the consciousness level and brain activity in DOC patients. Resting-state EEG can evaluate the dynamic changes of brain activity in DOC patients during HD-tDCS. EEG oscillation and non-oscillatory activity might be used to explain the mechanism of HD-tDCS on DOC patients.
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Affiliation(s)
- Yong Wang
- Zhuhai UM Science & Technology Research Institute, Zhuhai, China
| | - Wanqing Liu
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yingying Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, Normal University, Beijing, China
| | - Gaoxiang Ouyang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, Normal University, Beijing, China.
| | - Yongkun Guo
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Henan Key Laboratory of Brain Science and Brain Computer Interface Technology, Zhengzhou, China.
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5
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Qing K, Forgacs P, Schiff N. EEG Pattern With Spectral Analysis Can Prognosticate Good and Poor Neurologic Outcomes After Cardiac Arrest. J Clin Neurophysiol 2024; 41:236-244. [PMID: 36007069 PMCID: PMC9905375 DOI: 10.1097/wnp.0000000000000958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
PURPOSE To investigate the prognostic value of a simple stratification system of electroencephalographical (EEG) patterns and spectral types for patients after cardiac arrest. METHODS In this prospectively enrolled cohort, using manually selected EEG segments, patients after cardiac arrest were stratified into five independent EEG patterns (based on background continuity and burden of highly epileptiform discharges) and four independent power spectral types (based on the presence of frequency components). The primary outcome is cerebral performance category (CPC) at discharge. Results from multimodal prognostication testing were included for comparison. RESULTS Of a total of 72 patients, 6 had CPC 1-2 by discharge, all of whom had mostly continuous EEG background without highly epileptiform activity at day 3. However, for the same EEG background pattern at day 3, 19 patients were discharged at CPC 3 and 15 patients at CPC 4-5. After adding spectral analysis, overall sensitivity for predicting good outcomes (CPC 1-2) was 83.3% (95% confidence interval 35.9% to 99.6%) and specificity was 97.0% (89.5% to 99.6%). In this cohort, standard prognostication testing all yielded 100% specificity but low sensitivity, with imaging being the most sensitive at 54.1% (36.9% to 70.5%). CONCLUSIONS Adding spectral analysis to qualitative EEG analysis may further improve the diagnostic accuracy of EEG and may aid developing novel measures linked to good outcomes in postcardiac arrest coma.
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Affiliation(s)
- Kurt Qing
- New York-Presbyterian Weill Cornell Medical Center
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Boerwinkle VL, Appavu B, Cediel EG, Erklaurer J, Lalgudi Ganesan S, Gibbons C, Hahn C, LaRovere KL, Moberg D, Natarajan G, Molteni E, Reuther WR, Slomine BS. Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group in the Pediatric Population. Neurocrit Care 2024; 40:65-73. [PMID: 38062304 DOI: 10.1007/s12028-023-01870-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 09/27/2023] [Indexed: 02/15/2024]
Abstract
BACKGROUND The fundamental gap obstructing forward progress of evidenced-based care in pediatric and neonatal disorders of consciousness (DoC) is the lack of defining consensus-based terminology to perform comparative research. This lack of shared nomenclature in pediatric DoC stems from the inherently recursive dilemma of the inability to reliably measure consciousness in the very young. However, recent advancements in validated clinical examinations and technologically sophisticated biomarkers of brain activity linked to future abilities are unlocking this previously formidable challenge to understanding the DoC in the developing brain. METHODS To address this need, the first of its kind international convergence of an interdisciplinary team of pediatric DoC experts was organized by the Neurocritical Care Society's Curing Coma Campaign. The multidisciplinary panel of pediatric DoC experts proposed pediatric-tailored common data elements (CDEs) covering each of the CDE working groups including behavioral phenotyping, biospecimens, electrophysiology, family and goals of care, neuroimaging, outcome and endpoints, physiology and big Data, therapies, and pediatrics. RESULTS We report the working groups' pediatric-focused DoC CDE recommendations and disseminate CDEs to be used in studies of pediatric patients with DoC. CONCLUSIONS The CDEs recommended support the vision of progressing collaborative and successful internationally collaborative pediatric coma research.
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Affiliation(s)
- Varina L Boerwinkle
- Department of Neurology, University of North Carolina in Chapel Hill, Chapel Hill, NC, USA.
| | - Brian Appavu
- Department of Child Health and Neurology, University of Arizona College of Medicine - Phoenix, Phoenix, AZ, USA
| | - Emilio Garzon Cediel
- Department of Neurology, University of North Carolina in Chapel Hill, Chapel Hill, NC, USA
| | - Jennifer Erklaurer
- Divisions of Critical Care Medicine and Child Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Saptharishi Lalgudi Ganesan
- Departments of Paediatrics and Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Christie Gibbons
- Brain Injury Association of America Family Advocate, Phoenix, AZ, USA
| | - Cecil Hahn
- Department of Paediatrics (Neurology), The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Kerri L LaRovere
- Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Dick Moberg
- Moberg Analytics, Inc., Philadelphia, PA, USA
| | - Girija Natarajan
- Discipline of Pediatrics, Children's Hospital of Michigan and Hutzel Women's Hospital, Central Michigan University, Mount Pleasant, MI, USA
| | - Erika Molteni
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - William R Reuther
- Department of Neurology, University of North Carolina in Chapel Hill, Chapel Hill, NC, USA
| | - Beth S Slomine
- Department of Neuropsychology, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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7
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Claassen J, Kondziella D, Alkhachroum A, Diringer M, Edlow BL, Fins JJ, Gosseries O, Hannawi Y, Rohaut B, Schnakers C, Stevens RD, Thibaut A, Monti M. Cognitive Motor Dissociation: Gap Analysis and Future Directions. Neurocrit Care 2024; 40:81-98. [PMID: 37349602 DOI: 10.1007/s12028-023-01769-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 05/26/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND Patients with disorders of consciousness who are behaviorally unresponsive may demonstrate volitional brain responses to motor imagery or motor commands detectable on functional magnetic resonance imaging or electroencephalography. This state of cognitive motor dissociation (CMD) may have prognostic significance. METHODS The Neurocritical Care Society's Curing Coma Campaign identified an international group of experts who convened in a series of monthly online meetings between September 2021 and April 2023 to examine the science of CMD and identify key knowledge gaps and unmet needs. RESULTS The group identified major knowledge gaps in CMD research: (1) lack of information about patient experiences and caregiver accounts of CMD, (2) limited epidemiological data on CMD, (3) uncertainty about underlying mechanisms of CMD, (4) methodological variability that limits testing of CMD as a biomarker for prognostication and treatment trials, (5) educational gaps for health care personnel about the incidence and potential prognostic relevance of CMD, and (6) challenges related to identification of patients with CMD who may be able to communicate using brain-computer interfaces. CONCLUSIONS To improve the management of patients with disorders of consciousness, research efforts should address these mechanistic, epidemiological, bioengineering, and educational gaps to enable large-scale implementation of CMD assessment in clinical practice.
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Affiliation(s)
- Jan Claassen
- Department of Neurology, Neurological Institute, Columbia University Irving Medical Center, NewYork Presbyterian Hospital, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York, NY, 10032, USA.
| | - Daniel Kondziella
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | | | - Michael Diringer
- Department of Neurology, Washington University, St. Louis, MO, USA
| | - Brian L Edlow
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Joseph J Fins
- Division of Medical Ethics, Department of Medicine, Weill Cornell Medical College, NewYork Presbyterian Hospital, New York, NY, 10032, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liege, Liege, Belgium
- Centre du Cerveau, University Hospital of Liege, Liege, Belgium
| | - Yousef Hannawi
- Division of Cerebrovascular Diseases and Neurocritical Care, Department of Neurology, The Ohio State University, Columbus, OH, USA
| | - Benjamin Rohaut
- Sorbonne Université, Assistance Publique-Hôpitaux de Paris (AP-HP) - Pitié Salpêtrière, Paris, France
| | | | - Robert D Stevens
- Department of Anesthesiology and Critical Care Medicine, Neurology, and Radiology, School of Medicine, Secondary Appointment in Biomedical Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Aurore Thibaut
- Coma Science Group, GIGA Consciousness, University of Liege, Liege, Belgium
- Centre du Cerveau, University Hospital of Liege, Liege, Belgium
| | - Martin Monti
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
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8
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Qing K, Alkhachroum A, Claassen J, Forgacs P, Schiff N. The Electrographic Effects of Ketamine on Patients With Refractory Status Epilepticus After Cardiac Arrest: A Single-Center Retrospective Cohort. J Clin Neurophysiol 2024:00004691-990000000-00119. [PMID: 38194637 DOI: 10.1097/wnp.0000000000001065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2024] Open
Abstract
PURPOSE To investigate the effects of ketamine on patients with refractory status epilepticus after cardiac arrest. METHODS In this retrospective cohort, selected EEG segments from patients after cardiac arrest were classified into different EEG patterns (based on background continuity and burden of epileptiform discharges) and spectral profiles (based on the presence of frequency components). For patients who received ketamine, EEG data were compared before, during, and after ketamine infusion; for the no-ketamine group, EEG data were compared at three separated time points during recording. Ketamine usage was determined by clinical providers. Electrographic improvement in epileptiform activity was scored, and the odds ratio was calculated using the Fisher exact test. Functional outcome measures at time of discharge were also examined. RESULTS Of a total of 38 patients with postcardiac arrest refractory status epilepticus, 13 received ketamine and 25 did not. All patients were on ≥2 antiseizure medications including at least one sedative infusion (midazolam). For the ketamine group, eight patients had electrographic improvement, compared with only two patients in the no-ketamine group, with an odds ratio of 7.19 (95% confidence interval 1.16-44.65, P value of 0.0341) for ketamine versus no ketamine. Most of the patients who received ketamine had myoclonic status epilepticus, and overall neurologic outcomes were poor with no patients having a favorable outcome. CONCLUSIONS For postarrest refractory status epilepticus, ketamine use was associated with electrographic improvement, but with the available data, it is unclear whether ketamine use or EEG improvement can be linked to better functional recovery.
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Affiliation(s)
- Kurt Qing
- Department of Neurology, New York-Presbyterian Hospital Weill Cornell, New York, New York, U.S.A
| | - Ayham Alkhachroum
- Department of Neurology, University of Miami, Miami, Florida, U.S.A.; and
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, New York, New York, U.S.A
| | - Peter Forgacs
- Department of Neurology, New York-Presbyterian Hospital Weill Cornell, New York, New York, U.S.A
| | - Nicholas Schiff
- Department of Neurology, New York-Presbyterian Hospital Weill Cornell, New York, New York, U.S.A
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9
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Drążyk D, Przewrocki K, Górska-Klimowska U, Binder M. Distinct Spectral Profiles of Awake Resting EEG in Disorders of Consciousness: The Role of Frequency and Topography of Oscillations. Brain Topogr 2024; 37:138-151. [PMID: 38158511 PMCID: PMC10771586 DOI: 10.1007/s10548-023-01024-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 11/18/2023] [Indexed: 01/03/2024]
Abstract
The prolonged disorders of consciousness (PDOC) pose a challenge for an accurate clinical diagnosis, mainly due to patients' scarce or ambiguous behavioral responsiveness. Measurement of brain activity can support better diagnosis, independent of motor restrictions. Methods based on spectral analysis of resting-state EEG appear as a promising path, revealing specific changes within the internal brain dynamics in PDOC patients. In this study we used a robust method of resting-state EEG power spectrum parameter extraction to identify distinct spectral properties for different types of PDOC. Sixty patients and 37 healthy volunteers participated in this study. Patient group consisted of 22 unresponsive wakefulness patients, 25 minimally conscious patients and 13 patients emerging from the minimally conscious state. Ten minutes of resting EEG was acquired during wakefulness and transformed into individual power spectra. For each patient, using the spectral decomposition algorithm, we extracted maximum peak frequency within 1-14 Hz range in the centro-parietal region, and the antero-posterior (AP) gradient of the maximal frequency peak. All patients were behaviorally diagnosed using coma recovery scale-revised (CRS-R). The maximal peak frequency in the 1-14 Hz range successfully predicted both neurobehavioral capacity of patients as indicated by CRS-R total score and PDOC diagnosis. Additionally, in patients in whom only one peak within the 1-14 Hz range was observed, the AP gradient significantly contributed to the accuracy of prediction. We have identified three distinct spectral profiles of patients, likely representing separate neurophysiological modes of thalamocortical functioning. Etiology did not have significant influence on the obtained results.
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Affiliation(s)
- Dominika Drążyk
- Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium
| | - Karol Przewrocki
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, Netherlands
| | | | - Marek Binder
- Institute of Psychology, Jagiellonian University, Ul. Ingardena 6, 30-060, Krakow, Poland.
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10
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Carroll EE, Der-Nigoghossian C, Alkhachroum A, Appavu B, Gilmore E, Kromm J, Rohaut B, Rosanova M, Sitt JD, Claassen J. Common Data Elements for Disorders of Consciousness: Recommendations from the Electrophysiology Working Group. Neurocrit Care 2023; 39:578-585. [PMID: 37606737 DOI: 10.1007/s12028-023-01795-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 06/22/2023] [Indexed: 08/23/2023]
Abstract
BACKGROUND Electroencephalography (EEG) has long been recognized as an important tool in the investigation of disorders of consciousness (DoC). From inspection of the raw EEG to the implementation of quantitative EEG, and more recently in the use of perturbed EEG, it is paramount to providing accurate diagnostic and prognostic information in the care of patients with DoC. However, a nomenclature for variables that establishes a convention for naming, defining, and structuring data for clinical research variables currently is lacking. As such, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups composed of experts in the field to construct common data elements (CDEs) to provide recommendations for DoC, with the main goal of facilitating data collection and standardization of reporting. This article summarizes the recommendations of the electrophysiology DoC working group. METHODS After assessing previously published pertinent CDEs, we developed new CDEs and categorized them into "disease core," "basic," "supplemental," and "exploratory." Key EEG design elements, defined as concepts that pertained to a methodological parameter relevant to the acquisition, processing, or analysis of data, were also included but were not classified as CDEs. RESULTS After identifying existing pertinent CDEs and developing novel CDEs for electrophysiology in DoC, variables were organized into a framework based on the two primary categories of resting state EEG and perturbed EEG. Using this categorical framework, two case report forms were generated by the working group. CONCLUSIONS Adherence to the recommendations outlined by the electrophysiology working group in the resting state EEG and perturbed EEG case report forms will facilitate data collection and sharing in DoC research on an international level. In turn, this will allow for more informed and reliable comparison of results across studies, facilitating further advancement in the realm of DoC research.
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Affiliation(s)
- Elizabeth E Carroll
- Department of Neurology, Columbia University Medical Center, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York, NY, 10032, USA
- NewYork-Presbyterian Hospital, New York, NY, USA
| | | | | | - Brian Appavu
- Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, AZ, USA
- University of Arizona College of Medicine - Phoenix, Phoenix, AZ, USA
| | - Emily Gilmore
- Divisions of Neurocritical Care and Emergency Neurology and Epilepsy, Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
- Yale New Haven Hospital, New Haven, CT, USA
| | - Julie Kromm
- Departments of Critical Care Medicine and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Benjamin Rohaut
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, Centre national de la recherche scientifique, Assistance Publique-Hôpitaux de Paris, Neurosciences, Hôpital de La Pitié Salpêtrière, Paris, France
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Jacobo Diego Sitt
- Paris Brain Institute (ICM), Centre national de la recherche scientifique, Paris, France
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York, NY, 10032, USA.
- NewYork-Presbyterian Hospital, New York, NY, USA.
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11
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Benedetti GM, Guerriero RM, Press CA. Review of Noninvasive Neuromonitoring Modalities in Children II: EEG, qEEG. Neurocrit Care 2023; 39:618-638. [PMID: 36949358 PMCID: PMC10033183 DOI: 10.1007/s12028-023-01686-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 01/30/2023] [Indexed: 03/24/2023]
Abstract
Critically ill children with acute neurologic dysfunction are at risk for a variety of complications that can be detected by noninvasive bedside neuromonitoring. Continuous electroencephalography (cEEG) is the most widely available and utilized form of neuromonitoring in the pediatric intensive care unit. In this article, we review the role of cEEG and the emerging role of quantitative EEG (qEEG) in this patient population. cEEG has long been established as the gold standard for detecting seizures in critically ill children and assessing treatment response, and its role in background assessment and neuroprognostication after brain injury is also discussed. We explore the emerging utility of both cEEG and qEEG as biomarkers of degree of cerebral dysfunction after specific injuries and their ability to detect both neurologic deterioration and improvement.
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Affiliation(s)
- Giulia M Benedetti
- Division of Pediatric Neurology, Department of Neurology, Seattle Children's Hospital and the University of Washington School of Medicine, Seattle, WA, USA.
- Division of Pediatric Neurology, Department of Pediatrics, C.S. Mott Children's Hospital and the University of Michigan, 1540 E Hospital Drive, Ann Arbor, MI, 48109-4279, USA.
| | - Rejéan M Guerriero
- Division of Pediatric and Developmental Neurology, Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Craig A Press
- Departments of Neurology and Pediatric, Children's Hospital of Philadelphia and Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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12
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Liuzzi P, Mannini A, Hakiki B, Campagnini S, Romoli AM, Draghi F, Burali R, Scarpino M, Cecchi F, Grippo A. Brain microstate spatio-temporal dynamics as a candidate endotype of consciousness. Neuroimage Clin 2023; 41:103540. [PMID: 38101096 PMCID: PMC10727951 DOI: 10.1016/j.nicl.2023.103540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 10/02/2023] [Accepted: 11/09/2023] [Indexed: 12/17/2023]
Abstract
Consciousness can be defined as a phenomenological experience continuously evolving. Current research showed how conscious mental activity can be subdivided into a series of atomic brain states converging to a discrete spatiotemporal pattern of global neuronal firing. Using the high temporal resolution of EEG recordings in patients with a severe Acquired Brain Injury (sABI) admitted to an Intensive Rehabilitation Unit (IRU), we detected a novel endotype of consciousness from the spatiotemporal brain dynamics identified via microstate analysis. Also, we investigated whether microstate features were associated with common neurophysiological alterations. Finally, the prognostic information comprised in such descriptors was analysed in a sub-cohort of patients with prolonged Disorder of Consciousness (pDoC). Occurrence of frontally-oriented microstates (C microstate), likelihood of maintaining such brain state or transitioning to the C topography and complexity were found to be indicators of consciousness presence and levels. Features of left-right asymmetric microstates and transitions toward them were found to be negatively correlated with antero-posterior brain reorganization and EEG symmetry. Substantial differences in microstates' sequence complexity and presence of C topography were found between groups of patients with alpha dominant background, cortical reactivity and antero-posterior gradient. Also, transitioning from left-right to antero-posterior microstates was found to be an independent predictor of consciousness recovery, stronger than consciousness levels at IRU's admission. In conclusions, global brain dynamics measured with scale-free estimators can be considered an indicator of consciousness presence and a candidate marker of short-term recovery in patients with a pDoC.
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Affiliation(s)
- Piergiuseppe Liuzzi
- IRCCS Don Carlo Gnocchi ONLUS, Firenze, Italy; Istituto di BioRobotica, Scuola Superiore Sant'Anna, Pontedera, Italy
| | | | | | | | | | | | | | | | - Francesca Cecchi
- IRCCS Don Carlo Gnocchi ONLUS, Firenze, Italy; Dipartimento di Medicina Sperimentale e Clinica, Università di Firenze, Firenze, Italy
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13
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Franzova E, Shen Q, Doyle K, Chen JM, Egbebike J, Vrosgou A, Carmona JC, Grobois L, Heinonen GA, Velazquez A, Gonzales IJ, Egawa S, Agarwal S, Roh D, Park S, Connolly ES, Claassen J. Injury patterns associated with cognitive motor dissociation. Brain 2023; 146:4645-4658. [PMID: 37574216 PMCID: PMC10629765 DOI: 10.1093/brain/awad197] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/14/2023] [Accepted: 05/28/2023] [Indexed: 08/15/2023] Open
Abstract
In unconscious appearing patients with acute brain injury, wilful brain activation to motor commands without behavioural signs of command following, known as cognitive motor dissociation (CMD), is associated with functional recovery. CMD can be detected by applying machine learning to EEG recorded during motor command presentation in behaviourally unresponsive patients. Identifying patients with CMD carries clinical implications for patient interactions, communication with families, and guidance of therapeutic decisions but underlying mechanisms of CMD remain unknown. By analysing structural lesion patterns and network level dysfunction we tested the hypothesis that, in cases with preserved arousal and command comprehension, a failure to integrate comprehended motor commands with motor outputs underlies CMD. Manual segmentation of T2-fluid attenuated inversion recovery and diffusion weighted imaging sequences quantifying structural injury was performed in consecutive unresponsive patients with acute brain injury (n = 107) who underwent EEG-based CMD assessments and MRI. Lesion pattern analysis was applied to identify lesion patterns common among patients with (n = 21) and without CMD (n = 86). Thalamocortical and cortico-cortical network connectivity were assessed applying ABCD classification of power spectral density plots and weighted pairwise phase consistency (WPPC) to resting EEG, respectively. Two distinct structural lesion patterns were identified on MRI for CMD and three for non-CMD patients. In non-CMD patients, injury to brainstem arousal pathways including the midbrain were seen, while no CMD patients had midbrain lesions. A group of non-CMD patients was identified with injury to the left thalamus, implicating possible language comprehension difficulties. Shared lesion patterns of globus pallidus and putamen were seen for a group of CMD patients, which have been implicated as part of the anterior forebrain mesocircuit in patients with reversible disorders of consciousness. Thalamocortical network dysfunction was less common in CMD patients [ABCD-index 2.3 (interquartile range, IQR 2.1-3.0) versus 1.4 (IQR 1.0-2.0), P < 0.0001; presence of D 36% versus 3%, P = 0.0006], but WPPC was not different. Bilateral cortical lesions were seen in patients with and without CMD. Thalamocortical disruption did not differ for those with CMD, but long-range WPPC was decreased in 1-4 Hz [odds ratio (OR) 0.8; 95% confidence interval (CI) 0.7-0.9] and increased in 14-30 Hz frequency ranges (OR 1.2; 95% CI 1.0-1.5). These structural and functional data implicate a failure of motor command integration at the anterior forebrain mesocircuit level with preserved thalamocortical network function for CMD patients with subcortical lesions. Amongst patients with bilateral cortical lesions preserved cortico-cortical network function is associated with CMD detection. These data may allow screening for CMD based on widely available structural MRI and resting EEG.
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Affiliation(s)
- Eva Franzova
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Qi Shen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Kevin Doyle
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Justine M Chen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Jennifer Egbebike
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Athina Vrosgou
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Jerina C Carmona
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Lauren Grobois
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Gregory A Heinonen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Angela Velazquez
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | | | - Satoshi Egawa
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Sachin Agarwal
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - David Roh
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Soojin Park
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - E Sander Connolly
- Department of Neurological Surgery, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
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14
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Gao Q, Hao J, Kang X, Yuan F, Liu Y, Chen R, Liu X, Li R, Jiang W. EEG dynamics induced by zolpidem forecast consciousness evolution in prolonged disorders of consciousness. Clin Neurophysiol 2023; 153:46-56. [PMID: 37454563 DOI: 10.1016/j.clinph.2023.06.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 05/19/2023] [Accepted: 06/11/2023] [Indexed: 07/18/2023]
Abstract
OBJECTIVE To explore whether the EEG dynamics induced by zolpidem can predict consciousness evolution in patients with prolonged disorders of consciousness (PDOC). METHODS We conducted a prospective explorative analysis on thirty-six patients with PDOC and eleven healthy controls. The EEG power spectrum was analyzed and categorized into 'ABCD' patterns at baseline and one hour after zolpidem administration at 10 mg. The clinical outcome was defined as consciousness improvement and no improvement six months after enrollment using the Coma Recovery Scale-Revised (CRS-R) score. RESULTS Zolpidem administration significantly increased the EEG power in the delta & theta bands and decreased EEG power in the beta bands in healthy controls. Further follow-up studies indicated that the increased EEG beta-band power induced by zolpidem can predict an improved consciousness six months after enrollment with an area under the receiver operating characteristic curve (AUC) of 0.829, the sensitivity of 94.38% and an accuracy of 81.48%. CONCLUSIONS Our work revealed that the specific EEG responses to zolpidem can predict consciousness recovery in PDOC patients. SIGNIFICANCE The zolpidem-induced specific EEG responses could potentially predict the recovery of PDOC patients, which may help clinicians and patients' families in their decision-making process.
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Affiliation(s)
- Qiong Gao
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China.
| | - Jianmin Hao
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Xiaogang Kang
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Fang Yuan
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China; Department of Neurology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510000, China.
| | - Yu Liu
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China.
| | - Rong Chen
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Xiuyun Liu
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.
| | - Rui Li
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China.
| | - Wen Jiang
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China.
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15
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Annen J, Frasso G, van der Lande GJM, Bonin EAC, Vitello MM, Panda R, Sala A, Cavaliere C, Raimondo F, Bahri MA, Schiff ND, Gosseries O, Thibaut A, Laureys S. Cerebral electrometabolic coupling in disordered and normal states of consciousness. Cell Rep 2023; 42:112854. [PMID: 37498745 DOI: 10.1016/j.celrep.2023.112854] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 06/02/2023] [Accepted: 07/08/2023] [Indexed: 07/29/2023] Open
Abstract
We assess cerebral integrity with cortical and subcortical FDG-PET and cortical electroencephalography (EEG) within the mesocircuit model framework in patients with disorders of consciousness (DoCs). The mesocircuit hypothesis proposes that subcortical activation facilitates cortical function. We find that the metabolic balance of subcortical mesocircuit areas is informative for diagnosis and is associated with four EEG-based power spectral density patterns, cortical metabolism, and α power in healthy controls and patients with a DoC. Last, regional electrometabolic coupling at the cortical level can be identified in the θ and α ranges, showing positive and negative relations with glucose uptake, respectively. This relation is inverted in patients with a DoC, potentially related to altered orchestration of neural activity, and may underlie suboptimal excitability states in patients with a DoC. By understanding the neurobiological basis of the pathophysiology underlying DoCs, we foresee translational value for diagnosis and treatment of patients with a DoC.
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Affiliation(s)
- Jitka Annen
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium.
| | | | - Glenn J M van der Lande
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium
| | - Estelle A C Bonin
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium
| | - Marie M Vitello
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium
| | - Rajanikant Panda
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium
| | - Arianna Sala
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium
| | | | - Federico Raimondo
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Mohamed Ali Bahri
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
| | | | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium
| | - Aurore Thibaut
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium; Joint International Research Unit on Consciousness, CERVO Brain Research Centre, University Laval, Quebec City, QC, Canada
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16
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Amorim E, Zheng WL, Jing J, Ghassemi MM, Lee JW, Wu O, Herman ST, Pang T, Sivaraju A, Gaspard N, Hirsch L, Ruijter BJ, Tjepkema-Cloostermans MC, Hofmeijer J, van Putten MJAM, Westover MB. Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest. Neurology 2023; 101:e940-e952. [PMID: 37414565 PMCID: PMC10501085 DOI: 10.1212/wnl.0000000000207537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 05/04/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury after cardiac arrest. We aimed to delineate the evolution of coma neurophysiology feature ensembles associated with recovery from coma after cardiac arrest. METHODS Adults in acute coma after cardiac arrest were included in a retrospective database involving 7 hospitals. The combination of 3 quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon entropy [En]) was used to define 5 distinct neurophysiology states: epileptiform high entropy (EHE: SpF ≥4 per minute and En ≥5); epileptiform low entropy (ELE: SpF ≥4 per minute and <5 En); nonepileptiform high entropy (NEHE: SpF <4 per minute and ≥5 En); nonepileptiform low entropy (NELE: SpF <4 per minute and <5 En), and burst suppression (BSup ≥50% and SpF <4 per minute). State transitions were measured at consecutive 6-hour blocks between 6 and 84 hours after return of spontaneous circulation. Good neurologic outcome was defined as best cerebral performance category 1-2 at 3-6 months. RESULTS One thousand thirty-eight individuals were included (50,224 hours of EEG), and 373 (36%) had good outcome. Individuals with EHE state had a 29% rate of good outcome, while those with ELE had 11%. Transitions out of an EHE or BSup state to an NEHE state were associated with good outcome (45% and 20%, respectively). No individuals with ELE state lasting >15 hours had good recovery. DISCUSSION Transition to high entropy states is associated with an increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury.
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Affiliation(s)
- Edilberto Amorim
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands.
| | - Wei-Long Zheng
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Jin Jing
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Mohammad M Ghassemi
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Jong Woo Lee
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Ona Wu
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Susan T Herman
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Trudy Pang
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Adithya Sivaraju
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Nicolas Gaspard
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Lawrence Hirsch
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Barry J Ruijter
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Marleen C Tjepkema-Cloostermans
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Jeannette Hofmeijer
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - Michel J A M van Putten
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
| | - M Brandon Westover
- From the Department of Neurology (E.A.), Weill Institute for Neurosciences, University of California, San Francisco; Department of Neurology (E.A., W.-L.Z., J.J., M.B.W.), Massachusetts General Hospital, Boston; Department of Computer Science and Engineering (W.-L.Z.), Shanghai Jiao Tong University, China; Department of Neurology (J.J., T.P., M.B.W.), Beth Israel Deaconess Medical Center, Boston, MA; Department of Computer Science and Engineering (M.M.G.), Michigan State University, East Lansing; Department of Neurology (J.W.L.), Brigham and Women's Hospital; Athinoula A. Martinos Center for Biomedical Imaging (O.W.), Department of Radiology, Massachusetts General Hospital, Boston; Department of Neurology (S.T.H.), Barrow Neurological Institute Comprehensive Epilepsy Center, Phoenix, AZ; Department of Neurology (A.S., N.G., L.H.), Yale School of Medicine, New Haven, CT; Department of Neurology (N.G.), Universite Libre de Bruxelles, Belgium; Clinical Neurophysiology Group (B.J.R., M.C.T.-C., J.H., M.J.A.M.v.P.), University of Twente, Enschede; Department of Neurology (J.H.), Rijnstate Hospital, Arnhem; and Department of Neurology and Clinical Neurophysiology (M.J.A.M.v.P.), Medisch Spectrum Twente, Enschede, the Netherlands
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17
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Pelentritou A, Nguissi NAN, Iten M, Haenggi M, Zubler F, Rossetti AO, De Lucia M. The effect of sedation and time after cardiac arrest on coma outcome prognostication based on EEG power spectra. Brain Commun 2023; 5:fcad190. [PMID: 37469860 PMCID: PMC10353761 DOI: 10.1093/braincomms/fcad190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 05/11/2023] [Accepted: 06/27/2023] [Indexed: 07/21/2023] Open
Abstract
Early prognostication of long-term outcome of comatose patients after cardiac arrest remains challenging. Electroencephalography-based power spectra after cardiac arrest have been shown to help with the identification of patients with favourable outcome during the first day of coma. Here, we aim at comparing the power spectra prognostic value during the first and second day after coma onset following cardiac arrest and to investigate the impact of sedation on prognostication. In this cohort observational study, we included comatose patients (N = 91) after cardiac arrest for whom resting-state electroencephalography was collected on the first and second day after cardiac arrest in four Swiss hospitals. We evaluated whether the average power spectra values at 4.6-15.2 Hz were predictive of patients' outcome based on the best cerebral performance category score at 3 months, with scores ranging from 1 to 5 and dichotomized as favourable (1-2) and unfavourable (3-5). We assessed the effect of sedation and its interaction with the electroencephalography-based power spectra on patient outcome prediction through a generalized linear mixed model. Power spectra values provided 100% positive predictive value (95% confidence intervals: 0.81-1.00) on the first day of coma, with correctly predicted 18 out of 45 favourable outcome patients. On the second day, power spectra values were not predictive of patients' outcome (positive predictive value: 0.46, 95% confidence intervals: 0.19-0.75). On the first day, we did not find evidence of any significant contribution of sedative infusion rates to the patient outcome prediction (P > 0.05). Comatose patients' outcome prediction based on electroencephalographic power spectra is higher on the first compared with the second day after cardiac arrest. Sedation does not appear to impact patient outcome prediction.
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Affiliation(s)
| | | | - Manuela Iten
- Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Matthias Haenggi
- Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Frederic Zubler
- Department of Neurology, Spitalzentrum Biel, University of Bern, 2501 Biel, Switzerland
| | - Andrea O Rossetti
- Department of Clinical Neurosciences, University Hospital (CHUV) & University of Lausanne, 1011 Lausanne, Switzerland
| | - Marzia De Lucia
- Correspondence to: Marzia De Lucia, Laboratoire de Recherche en Neuroimagerie (LREN), Centre Hospitalier Universitaire Vaudois (CHUV), MP16 05 559, Chemin de Mont-Paisible 16, Lausanne 1010, Switzerland. E-mail:
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18
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Zhang Y, Feng Y, Chen F, Yu J, Liu X, Liu Y, Ouyang J, Liang M, Zhu Y, Zou L. Insight into the mechanisms of therapeutic hypothermia for asphyxia cardiac arrest using a comprehensive approach of GC-MS/MS and UPLC-Q-TOF-MS/MS based on serum metabolomics. Heliyon 2023; 9:e16247. [PMID: 37274716 PMCID: PMC10238693 DOI: 10.1016/j.heliyon.2023.e16247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 05/08/2023] [Accepted: 05/10/2023] [Indexed: 06/06/2023] Open
Abstract
Cardiac arrest (CA) is a severe worldwide health problem. Therapeutic hypothermia is widely used to reduce the cardiac injury and improve the neurological outcomes after CA. However, a few studies have reported the changes of serum metabolic characteristics after CA. The healthy male New Zealand Rabbits successfully resuscitated from 10-min asphyxia-induced CA were divided randomly into the normothermia (NT) group and mild therapeutic hypothermia (HT) group. The sham group underwent sham-operation. Survival was recorded and neurological deficit score (NDS) was assessed. The serum non-targeted metabolomics were detected using ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS) and gas chromatography tandem mass spectrometry (GC-MS/MS) at 15 min, 3 h, 6 h and 24 h after return of spontaneous circulation (ROSC). Our study showed that the heart rate (HR) significantly slowed down during 0.5-6 h post ROSC, consistent with the decreasing trend of body temperature in the HT group. Compared with the NT group, the levels of Lac and PCO2 at 24 h post ROSC were lower, while a significant increase in PO2 level at 24 h post ROSC was observed in the HT group. The survival rate of the HT group was significantly higher than that of the NT group, and NDS scores were remarkably increased at 24 h post ROSC in the NT group. Significant differences in metabolic profiles at 15 min, 3 h, 6 h and 24 h post ROSC were observed among the Sham, NT and HT groups. The differential metabolites detected by UPLC-Q-TOF-MS/MS and GC-MS/MS were screened for further study between every two groups (NT vs sham, HT vs sham and HT vs NT) at 15 min, 3 h, 6 h and 24 h post ROSC. Phenylalanine metabolism, alanine, aspartate and glutamate metabolism and tricarboxylic acid (TCA) cycle were enriched in NT vs sham, HT vs sham and HT vs NT respectively. Our study demonstrated that therapeutic hypothermia improves the survival and neurological outcomes in rabbit model of cardiac arrest, and firstly represents the dynamic metabolic changes in the hypothermia therapy for CA by comprehensive UPLC-Q-TOF-MS/MS- and GC-MS/MS-based metabolomics.
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Affiliation(s)
- Yiyuan Zhang
- The First Affiliated Hospital of Hunan Normal University, Hunan Provincial Key Laboratory of Molecular Epidemiology, Changsha, Hunan, China
| | - Yang Feng
- The First Affiliated Hospital of Hunan Normal University, Hunan Provincial Key Laboratory of Molecular Epidemiology, Changsha, Hunan, China
- Department of Emergency Medicine, Hunan Provincial People's Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
| | - Fang Chen
- Hunan Provincial People's Hospital, Hunan Provincial Key Laboratory of Emergency and Critical Care Metabolomics,Changsha, Hunan, China
| | - Jiang Yu
- Hunan Provincial People's Hospital, Hunan Provincial Key Laboratory of Emergency and Critical Care Metabolomics,Changsha, Hunan, China
| | - Xiehong Liu
- Hunan Provincial People's Hospital, Hunan Provincial Key Laboratory of Emergency and Critical Care Metabolomics,Changsha, Hunan, China
| | - Yanjuan Liu
- Hunan Provincial People's Hospital, Hunan Provincial Key Laboratory of Emergency and Critical Care Metabolomics,Changsha, Hunan, China
| | - Jielin Ouyang
- The First Affiliated Hospital of Hunan Normal University, Hunan Provincial Key Laboratory of Molecular Epidemiology, Changsha, Hunan, China
- Department of Emergency Medicine, Hunan Provincial People's Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
| | - Mingyu Liang
- The First Affiliated Hospital of Hunan Normal University, Hunan Provincial Key Laboratory of Molecular Epidemiology, Changsha, Hunan, China
- Department of Emergency Medicine, Hunan Provincial People's Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
| | - Yiming Zhu
- Hunan Provincial People's Hospital, Hunan Provincial Key Laboratory of Emergency and Critical Care Metabolomics,Changsha, Hunan, China
| | - Lianhong Zou
- The First Affiliated Hospital of Hunan Normal University, Hunan Provincial Key Laboratory of Molecular Epidemiology, Changsha, Hunan, China
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19
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Kumar A, Ridha M, Claassen J. Prognosis of consciousness disorders in the intensive care unit. Presse Med 2023; 52:104180. [PMID: 37805070 PMCID: PMC10995112 DOI: 10.1016/j.lpm.2023.104180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 10/03/2023] [Indexed: 10/09/2023] Open
Abstract
Assessments of consciousness are a critical part of prognostic algorithms for critically ill patients suffering from severe brain injuries. There have been significant advances in the field of coma science over the past two decades, providing clinicians with more advanced and precise tools for diagnosing and prognosticating disorders of consciousness (DoC). Advanced neuroimaging and electrophysiological techniques have vastly expanded our understanding of the biological mechanisms underlying consciousness, and have helped identify new states of consciousness. One of these, termed cognitive motor dissociation, can predict functional recovery at 1 year post brain injury, and is present in up to 15-20% of patients with DoC. In this chapter, we review several tools that are used to predict DoC, describing their strengths and limitations, from the neurological examination to advanced imaging and electrophysiologic techniques. We also describe multimodal assessment paradigms that can be used to identify covert consciousness and thus help recognize patients with the potential for future recovery and improve our prognostication practices.
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Affiliation(s)
- Aditya Kumar
- Department of Neurology, Columbia University Medical Center, New York-Presbyterian Hospital, New York, NY, USA
| | - Mohamed Ridha
- Department of Neurology, Columbia University Medical Center, New York-Presbyterian Hospital, New York, NY, USA
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, New York-Presbyterian Hospital, New York, NY, USA.
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20
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Schiff ND. Mesocircuit mechanisms in the diagnosis and treatment of disorders of consciousness. Presse Med 2023; 52:104161. [PMID: 36563999 DOI: 10.1016/j.lpm.2022.104161] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 11/14/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
The 'mesocircuit hypothesis' proposes mechanisms underlying the recovery of consciousness following severe brain injuries. The model builds up from a single premise that multifocal brain injuries resulting in coma and subsequent disorders of consciousness produce widespread neuronal death and dysfunction. Considering the general properties of cortical, thalamic, and striatal neurons, a lawful and specific circuit-level mechanism is constructed based on these known anatomical and physiological specializations of neuronal subtypes. The mesocircuit model generates many testable predictions at the mesocircuit, local circuit, and cellular level across multiple cerebral structures to correlate diagnostic measurements and interpret therapeutic interventions. The anterior forebrain mesocircuit is integrally related to the frontal-parietal network, another network demonstrated to show strong correlation with levels of recovery in disorders of consciousness. A further extension known as the "ABCD" model has been used to examine interaction of these models in recovery of consciousness using electrophysiological data types. Many studies have examined predictions of the mesocircuit model; here we first present the model and review the accumulated evidence for several predictions of model across multiple stages of recovery function in human subjects. Recent studies linking the mesocircuit model, the ABCD model, and interactions with the frontoparietal network are reviewed. Finally, theoretical implications of the mesocircuit model at the neuronal level are considered to interpret recent studies of deep brain stimulation in the central lateral thalamus in patients recovering from coma and in new experimental models in the context of emerging understanding of neuronal and local circuit mechanisms underlying conscious brain states.
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Affiliation(s)
- Nicholas D Schiff
- Jerold B. Katz Professor of Neurology and Neuroscience, Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, United States.
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21
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Maschke C, Duclos C, Owen AM, Jerbi K, Blain-Moraes S. Aperiodic brain activity and response to anesthesia vary in disorders of consciousness. Neuroimage 2023; 275:120154. [PMID: 37209758 DOI: 10.1016/j.neuroimage.2023.120154] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 03/28/2023] [Accepted: 05/02/2023] [Indexed: 05/22/2023] Open
Abstract
In the human electroencephalogram (EEG), oscillatory power peaks co-exist with non-oscillatory, aperiodic activity. Although EEG analysis has traditionally focused exclusively on oscillatory power, recent investigations have shown that the aperiodic EEG component can distinguish conscious wakefulness from sleep and anesthetic-induced unconsciousness. This study investigates the aperiodic EEG component of individuals in a disorder of consciousness (DOC); how it changes in response to exposure to anesthesia; and how it relates to the brain's information richness and criticality. High-density EEG was recorded from 43 individuals in a DOC, with 16 of these individuals undergoing a protocol of propofol anesthesia. The aperiodic component was defined by the spectral slope of the power spectral density. Our results demonstrate that the EEG aperiodic component is more informative about the participants' level of consciousness than the oscillatory component, especially for patients that suffered from a stroke. Importantly, the pharmacologically induced change in the spectral slope from 30-45 Hz positively correlated with individual's pre-anesthetic level of consciousness. The pharmacologically induced loss of information-richness and criticality was associated with individual's pre-anesthetic aperiodic component. During exposure to anesthesia, the aperiodic component was correlated with 3-month recovery status for individuals with DOC. The aperiodic EEG component has been historically neglected; this research highlights the necessity of considering this measure for the assessment of individuals in DOC and future research that seeks to understand the neurophysiological underpinnings of consciousness.
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Affiliation(s)
- Charlotte Maschke
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Canada
| | - Catherine Duclos
- Hôpital du Sacré-Cœur de Montréal, Centre intégré universitaire de Santé et de Services Sociaux du Nord-de-l'île-de-Montréal, Montréal, Québec Canada; Department of Anesthesiology and Pain Medicine, Université de Montréal, Montréal, Québec Canada
| | - Adrian M Owen
- Department of Physiology and Pharmacology, Western University, London, Ontario, Canada; Western Institute for Neuroscience, Western University, London, Ontario, Canada; Department of Psychology, Western University, London, Ontario, Canada
| | - Karim Jerbi
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada; MILA (Québec Artificial Intelligence Institute), Montréal, Québec, Canada; Centre UNIQUE (Union Neurosciences & Intelligence Artificielle), Montréal, Québec, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada; School of Physical and Occupational Therapy, McGill University, Montreal, Canada.
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22
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Buccellato A, Zang D, Zilio F, Gomez-Pilar J, Wang Z, Qi Z, Zheng R, Xu Z, Wu X, Bisiacchi P, Felice AD, Mao Y, Northoff G. Disrupted relationship between intrinsic neural timescales and alpha peak frequency during unconscious states - A high-density EEG study. Neuroimage 2023; 265:119802. [PMID: 36503159 DOI: 10.1016/j.neuroimage.2022.119802] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 11/22/2022] [Accepted: 12/07/2022] [Indexed: 12/13/2022] Open
Abstract
Our brain processes the different timescales of our environment's temporal input stochastics. Is such a temporal input processing mechanism key for consciousness? To address this research question, we calculated measures of input processing on shorter (alpha peak frequency, APF) and longer (autocorrelation window, ACW) timescales on resting-state high-density EEG (256 channels) recordings and compared them across different consciousness levels (awake/conscious, ketamine and sevoflurane anaesthesia, unresponsive wakefulness, minimally conscious state). We replicate and extend previous findings of: (i) significantly longer ACW values, consistently over all states of unconsciousness, as measured with ACW-0 (an unprecedented longer version of the well-know ACW-50); (ii) significantly slower APF values, as measured with frequency sliding, in all four unconscious states. Most importantly, we report a highly significant correlation of ACW-0 and APF in the conscious state, while their relationship is disrupted in the unconscious states. In sum, we demonstrate the relevance of the brain's capacity for input processing on shorter (APF) and longer (ACW) timescales - including their relationship - for consciousness. Albeit indirectly, e.g., through the analysis of electrophysiological activity at rest, this supports the mechanism of temporo-spatial alignment to the environment's temporal input stochastics, through relating different neural timescales, as one key predisposing factor of consciousness.
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Affiliation(s)
- Andrea Buccellato
- Padova Neuroscience Center, University of Padova, Padova, Italy; Department of General Psychology, University of Padova, Padova, Italy.
| | - Di Zang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padova, Padua, Italy
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, Valladolid 47011, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid, Spain
| | - Zhe Wang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Zengxin Qi
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Ruizhe Zheng
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Zeyu Xu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Xuehai Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Patrizia Bisiacchi
- Padova Neuroscience Center, University of Padova, Padova, Italy; Department of General Psychology, University of Padova, Padova, Italy
| | - Alessandra Del Felice
- Padova Neuroscience Center, University of Padova, Padova, Italy; Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China.
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Ontario K1Z7K4, Canada; Mental Health Center, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang Province, China; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 310013, Zhejiang Province, China.
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23
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Transcutaneous vagal nerve stimulation to treat disorders of consciousness: Protocol for a double-blind randomized controlled trial. Int J Clin Health Psychol 2023; 23:100360. [PMCID: PMC9712558 DOI: 10.1016/j.ijchp.2022.100360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 11/21/2022] [Indexed: 12/03/2022] Open
Abstract
Background Patients with disorders of consciousness (DoC) are a challenging population prone to misdiagnosis with limited effective treatment options. Among neuromodulation techniques, transcutaneous auricular vagal nerve stimulation (taVNS) may act through a bottom-up manner to modulate thalamo-cortical connectivity and promote patients’ recovery. In this clinical trial, we aim to (1) assess the therapeutic clinical effects of taVNS in patients with DoC; (2) investigate the neural mechanisms underlying the effects of its action; (3) assess the feasibility and safety of the procedure in this challenging population; (4) define the phenotype of clinical responders; and (5) assess the long-term efficacy of taVNS in terms of functional outcomes. Methods We will conduct a prospective parallel randomized controlled double-blind clinical trial investigating the effects of taVNS as a treatment in DoC patients. Forty-four patients in the early period post-injury (7 to 90 days following the injury) will randomly receive 5 days of either active bilateral vagal stimulation (45 min duration with 30s alternative episodes of active/rest periods; 3mA; 200-300μs current width, 25Hz.) or sham stimulation. Behavioural (i.e., Coma Recovery Scale-Revised, CRS-R) and neurophysiological (i.e., high-density electroencephalography, hd-EEG) measures will be collected at baseline and at the end of the 5-day treatment. Analyses will seek for changes in the CRS-R and the EEG metrics (e.g., alpha band power spectrum, functional connectivity) at the group and individual (i.e., responders) levels. Discussion These results will allow us to investigate the vagal afferent network and will contribute towards a definition of the role of taVNS for the treatment of patients with DoC. We aim to identify the neural correlates of its action and pave the way to novel targeted therapeutic strategies. Clinical trial registration Clinicaltrials.gov n° NCT04065386.
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24
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Bibineyshvili Y, Schiff ND, Calderon DP. Dexmedetomidine-mediated sleep phase modulation ameliorates motor and cognitive performance in a chronic blast-injured mouse model. Front Neurol 2022; 13:1040975. [DOI: 10.3389/fneur.2022.1040975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 10/17/2022] [Indexed: 11/13/2022] Open
Abstract
Multiple studies have shown that blast injury is followed by sleep disruption linked to functional sequelae. It is well established that improving sleep ameliorates such functional deficits. However, little is known about longitudinal brain activity changes after blast injury. In addition, the effects of directly modulating the sleep/wake cycle on learning task performance after blast injury remain unclear. We hypothesized that modulation of the sleep phase cycle in our injured mice would improve post-injury task performance. Here, we have demonstrated that excessive sleep electroencephalographic (EEG) patterns are accompanied by prominent motor and cognitive impairment during acute stage after secondary blast injury (SBI) in a mouse model. Over time we observed a transition to more moderate and prolonged sleep/wake cycle disturbances, including changes in theta and alpha power. However, persistent disruptions of the non-rapid eye movement (NREM) spindle amplitude and intra-spindle frequency were associated with lasting motor and cognitive deficits. We, therefore, modulated the sleep phase of injured mice using subcutaneous (SC) dexmedetomidine (Dex), a common, clinically used sedative. Dex acutely improved intra-spindle frequency, theta and alpha power, and motor task execution in chronically injured mice. Moreover, dexmedetomidine ameliorated cognitive deficits a week after injection. Our results suggest that SC Dex might potentially improve impaired motor and cognitive behavior during daily tasks in patients that are chronically impaired by blast-induced injuries.
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25
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Alkhachroum A, Appavu B, Egawa S, Foreman B, Gaspard N, Gilmore EJ, Hirsch LJ, Kurtz P, Lambrecq V, Kromm J, Vespa P, Zafar SF, Rohaut B, Claassen J. Electroencephalogram in the intensive care unit: a focused look at acute brain injury. Intensive Care Med 2022; 48:1443-1462. [PMID: 35997792 PMCID: PMC10008537 DOI: 10.1007/s00134-022-06854-3] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 07/31/2022] [Indexed: 02/04/2023]
Abstract
Over the past decades, electroencephalography (EEG) has become a widely applied and highly sophisticated brain monitoring tool in a variety of intensive care unit (ICU) settings. The most common indication for EEG monitoring currently is the management of refractory status epilepticus. In addition, a number of studies have associated frequent seizures, including nonconvulsive status epilepticus (NCSE), with worsening secondary brain injury and with worse outcomes. With the widespread utilization of EEG (spot and continuous EEG), rhythmic and periodic patterns that do not fulfill strict seizure criteria have been identified, epidemiologically quantified, and linked to pathophysiological events across a wide spectrum of critical and acute illnesses, including acute brain injury. Increasingly, EEG is not just qualitatively described, but also quantitatively analyzed together with other modalities to generate innovative measurements with possible clinical relevance. In this review, we discuss the current knowledge and emerging applications of EEG in the ICU, including seizure detection, ischemia monitoring, detection of cortical spreading depolarizations, assessment of consciousness and prognostication. We also review some technical aspects and challenges of using EEG in the ICU including the logistics of setting up ICU EEG monitoring in resource-limited settings.
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Affiliation(s)
- Ayham Alkhachroum
- Department of Neurology, University of Miami, Miami, FL, USA
- Department of Neurology, Jackson Memorial Hospital, Miami, FL, USA
| | - Brian Appavu
- Department of Child Health and Neurology, University of Arizona College of Medicine-Phoenix, Phoenix, AZ, USA
- Department of Neurosciences, Phoenix Children's Hospital, Phoenix, AZ, USA
| | - Satoshi Egawa
- Neurointensive Care Unit, Department of Neurosurgery, and Stroke and Epilepsy Center, TMG Asaka Medical Center, Saitama, Japan
| | - Brandon Foreman
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, 231 Albert Sabin Way, Cincinnati, OH, USA
| | - Nicolas Gaspard
- Department of Neurology, Erasme Hospital, Free University of Brussels, Brussels, Belgium
| | - Emily J Gilmore
- Comprehensive Epilepsy Center, Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
- Neurocritical Care and Emergency Neurology, Department of Neurology, Ale University School of Medicine, New Haven, CT, USA
| | - Lawrence J Hirsch
- Comprehensive Epilepsy Center, Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - Pedro Kurtz
- Department of Intensive Care Medicine, D'or Institute for Research and Education, Rio de Janeiro, Brazil
- Neurointensive Care, Paulo Niemeyer State Brain Institute, Rio de Janeiro, Brazil
| | - Virginie Lambrecq
- Department of Clinical Neurophysiology and Epilepsy Unit, AP-HP, Pitié Salpêtrière Hospital, Reference Center for Rare Epilepsies, 75013, Paris, France
| | - Julie Kromm
- Departments of Critical Care Medicine and Clinical Neurosciences, Cumming School of Medicine, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, Calgary, AB, Canada
| | - Paul Vespa
- Brain Injury Research Center, Department of Neurosurgery, University of California, Los Angeles, USA
| | - Sahar F Zafar
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Benjamin Rohaut
- Department of Neurology, Sorbonne Université, Pitié-Salpêtrière-AP-HP and Paris Brain Institute, ICM, Inserm, CNRS, Paris, France
| | - Jan Claassen
- Department of Neurology, Neurological Institute, Columbia University, New York Presbyterian Hospital, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York, NY, 10032, USA.
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26
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Amiri M, Fisher PM, Raimondo F, Sidaros A, Cacic Hribljan M, Othman MH, Zibrandtsen I, Albrechtsen SS, Bergdal O, Hansen AE, Hassager C, Højgaard JLS, Jakobsen EW, Jensen HR, Møller J, Nersesjan V, Nikolic M, Olsen MH, Sigurdsson ST, Sitt JD, Sølling C, Welling KL, Willumsen LM, Hauerberg J, Larsen VA, Fabricius M, Knudsen GM, Kjaergaard J, Møller K, Kondziella D. Multimodal prediction of residual consciousness in the intensive care unit: the CONNECT-ME study. Brain 2022; 146:50-64. [PMID: 36097353 PMCID: PMC9825454 DOI: 10.1093/brain/awac335] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 07/25/2022] [Accepted: 08/14/2022] [Indexed: 01/15/2023] Open
Abstract
Functional MRI (fMRI) and EEG may reveal residual consciousness in patients with disorders of consciousness (DoC), as reflected by a rapidly expanding literature on chronic DoC. However, acute DoC is rarely investigated, although identifying residual consciousness is key to clinical decision-making in the intensive care unit (ICU). Therefore, the objective of the prospective, observational, tertiary centre cohort, diagnostic phase IIb study 'Consciousness in neurocritical care cohort study using EEG and fMRI' (CONNECT-ME, NCT02644265) was to assess the accuracy of fMRI and EEG to identify residual consciousness in acute DoC in the ICU. Between April 2016 and November 2020, 87 acute DoC patients with traumatic or non-traumatic brain injury were examined with repeated clinical assessments, fMRI and EEG. Resting-state EEG and EEG with external stimulations were evaluated by visual analysis, spectral band analysis and a Support Vector Machine (SVM) consciousness classifier. In addition, within- and between-network resting-state connectivity for canonical resting-state fMRI networks was assessed. Next, we used EEG and fMRI data at study enrolment in two different machine-learning algorithms (Random Forest and SVM with a linear kernel) to distinguish patients in a minimally conscious state or better (≥MCS) from those in coma or unresponsive wakefulness state (≤UWS) at time of study enrolment and at ICU discharge (or before death). Prediction performances were assessed with area under the curve (AUC). Of 87 DoC patients (mean age, 50.0 ± 18 years, 43% female), 51 (59%) were ≤UWS and 36 (41%) were ≥ MCS at study enrolment. Thirty-one (36%) patients died in the ICU, including 28 who had life-sustaining therapy withdrawn. EEG and fMRI predicted consciousness levels at study enrolment and ICU discharge, with maximum AUCs of 0.79 (95% CI 0.77-0.80) and 0.71 (95% CI 0.77-0.80), respectively. Models based on combined EEG and fMRI features predicted consciousness levels at study enrolment and ICU discharge with maximum AUCs of 0.78 (95% CI 0.71-0.86) and 0.83 (95% CI 0.75-0.89), respectively, with improved positive predictive value and sensitivity. Overall, both machine-learning algorithms (SVM and Random Forest) performed equally well. In conclusion, we suggest that acute DoC prediction models in the ICU be based on a combination of fMRI and EEG features, regardless of the machine-learning algorithm used.
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Affiliation(s)
| | | | | | - Annette Sidaros
- Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark,Department of Neurophysiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Melita Cacic Hribljan
- Department of Neurophysiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Marwan H Othman
- Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Ivan Zibrandtsen
- Department of Neurophysiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Simon S Albrechtsen
- Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Ove Bergdal
- Department of Neurosurgery, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Adam Espe Hansen
- Department of Radiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Christian Hassager
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark,Department of Cardiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Joan Lilja S Højgaard
- Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | | | - Helene Ravnholt Jensen
- Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Jacob Møller
- Department of Cardiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Vardan Nersesjan
- Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark,Biological and Precision Psychiatry, Copenhagen Research Center for Mental Health, Copenhagen University Hospital, Copenhagen, Denmark
| | - Miki Nikolic
- Department of Neurophysiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Markus Harboe Olsen
- Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Sigurdur Thor Sigurdsson
- Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Jacobo D Sitt
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
| | - Christine Sølling
- Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Karen Lise Welling
- Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Lisette M Willumsen
- Department of Neurosurgery, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - John Hauerberg
- Department of Neurosurgery, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Vibeke Andrée Larsen
- Department of Radiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Martin Fabricius
- Department of Neurophysiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Gitte Moos Knudsen
- Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Jesper Kjaergaard
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark,Department of Cardiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Kirsten Møller
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark,Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Daniel Kondziella
- Correspondence to: Daniel Kondziella, MD, MSc, PhD FEBN Department of Neurology Copenhagen University Hospital, Rigshospitalet Blegdamsvej 9, DK-2100 Copenhagen E-mail:
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27
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Curley WH, Bodien YG, Zhou DW, Conte MM, Foulkes AS, Giacino JT, Victor JD, Schiff ND, Edlow BL. Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury. Cortex 2022; 152:136-152. [PMID: 35569326 PMCID: PMC9759728 DOI: 10.1016/j.cortex.2022.04.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 01/26/2022] [Accepted: 04/04/2022] [Indexed: 12/26/2022]
Abstract
Tools assaying the neural networks that modulate consciousness may facilitate tracking of recovery after acute severe brain injury. The ABCD framework classifies resting-state EEG into categories reflecting levels of thalamocortical network function that correlate with outcome in post-cardiac arrest coma. In this longitudinal cohort study, we applied the ABCD framework to 20 patients with acute severe traumatic brain injury requiring intensive care (12 of whom were also studied at ≥6-months post-injury) and 16 healthy controls. We tested four hypotheses: 1) EEG ABCD classifications are spatially heterogeneous and temporally variable; 2) ABCD classifications improve longitudinally, commensurate with the degree of behavioral recovery; 3) ABCD classifications correlate with behavioral level of consciousness; and 4) the Coma Recovery Scale-Revised arousal facilitation protocol yields improved ABCD classifications. Channel-level EEG power spectra were classified based on spectral peaks within pre-defined frequency bands: 'A' = no peaks above delta (<4 Hz) range (complete thalamocortical disruption); 'B' = theta (4-8 Hz) peak (severe thalamocortical disruption); 'C' = theta and beta (13-24 Hz) peaks (moderate thalamocortical disruption); or 'D' = alpha (8-13 Hz) and beta peaks (normal thalamocortical function). Acutely, 95% of patients demonstrated 'D' signals in at least one channel but exhibited within-session temporal variability and spatial heterogeneity in the proportion of different channel-level ABCD classifications. By contrast, healthy participants and patients at follow-up consistently demonstrated signals corresponding to intact thalamocortical network function. Patients demonstrated longitudinal improvement in ABCD classifications (p < .05) and ABCD classification distinguished patients with and without command-following in the subacute-to-chronic phase of recovery (p < .01). In patients studied acutely, ABCD classifications improved after the Coma Recovery Scale-Revised arousal facilitation protocol (p < .05) but did not correspond with behavioral level of consciousness. These findings support the use of the ABCD framework to characterize channel-level EEG dynamics and track fluctuations in functional thalamocortical network integrity in spatial detail.
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Affiliation(s)
- William H Curley
- Harvard Medical School, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA, USA
| | - David W Zhou
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Mary M Conte
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY, USA
| | - Andrea S Foulkes
- Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA, USA; Department of Physical Medicine and Rehabilitation, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jonathan D Victor
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY, USA; Department of Neurology, New York Presbyterian Hospital, New York, NY, USA
| | - Nicholas D Schiff
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY, USA; Department of Neurology, New York Presbyterian Hospital, New York, NY, USA
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
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28
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Kim MJ, Kim YJ, Yum MS, Kim WY. Alpha-power in electroencephalography as good outcome predictor for out-of-hospital cardiac arrest survivors. Sci Rep 2022; 12:10907. [PMID: 35764807 PMCID: PMC9240023 DOI: 10.1038/s41598-022-15144-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 06/20/2022] [Indexed: 11/09/2022] Open
Abstract
This study aimed to investigate the utility of quantitative EEG biomarkers for predicting good neurologic outcomes in OHCA survivors treated with targeted temperature management (TTM) using power spectral density (PSD), event-related spectral perturbation (ERSP), and spectral entropy (SE). This observational registry-based study was conducted at a tertiary care hospital in Korea using data of adult nontraumatic comatose OHCA survivors who underwent standard EEG and treated with TTM between 2010 and 2018. Good neurological outcome at 1 month (Cerebral Performance Category scores 1 and 2) was the primary outcome. The linear mixed model analysis was performed for PSD, ESRP, and SE values of all and each frequency band. Thirteen of the 54 comatose OHCA survivors with TTM and EEG were excluded due to poor EEG quality or periodic/rhythmic pattern, and EEG data of 41 patients were used for analysis. The median time to EEG was 21 h, and the rate of the good neurologic outcome at 1 month was 52.5%. The good neurologic outcome group was significantly younger and showed higher PSD and ERSP and lower SE features for each frequency than the poor outcome group. After age adjustment, only the alpha-PSD was significantly higher in the good neurologic outcome group (1.13 ± 1.11 vs. 0.09 ± 0.09, p = 0.031) and had best performance with 0.903 of the area under the curve for predicting good neurologic outcome. Alpha-PSD best predicts good neurologic outcome in OHCA survivors and is an early biomarker for prognostication. Larger studies are needed to conclusively confirm these findings.
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Affiliation(s)
- Min-Jee Kim
- Division of Pediatric Neurology, Department of Pediatrics, Asan Medical Center Children's Hospital, Ulsan University College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea
| | - Youn-Jung Kim
- Department of Emergency Medicine, Asan Medical Center, Ulsan University College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea
| | - Mi-Sun Yum
- Division of Pediatric Neurology, Department of Pediatrics, Asan Medical Center Children's Hospital, Ulsan University College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea.
| | - Won Young Kim
- Department of Emergency Medicine, Asan Medical Center, Ulsan University College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea.
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29
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Curley WH, Comanducci A, Fecchio M. Conventional and Investigational Approaches Leveraging Clinical EEG for Prognosis in Acute Disorders of Consciousness. Semin Neurol 2022; 42:309-324. [PMID: 36100227 DOI: 10.1055/s-0042-1755220] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
Prediction of recovery of consciousness after severe brain injury is difficult and limited by a lack of reliable, standardized biomarkers. Multiple approaches for analysis of clinical electroencephalography (EEG) that shed light on prognosis in acute severe brain injury have emerged in recent years. These approaches fall into two major categories: conventional characterization of EEG background and quantitative measurement of resting state or stimulus-induced EEG activity. Additionally, a small number of studies have associated the presence of electrophysiologic sleep features with prognosis in the acute phase of severe brain injury. In this review, we focus on approaches for the analysis of clinical EEG that have prognostic significance and that could be readily implemented with minimal additional equipment in clinical settings, such as intensive care and intensive rehabilitation units, for patients with acute disorders of consciousness.
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Affiliation(s)
- William H Curley
- Harvard Medical School, Boston, Massachusetts.,Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, Massachusetts
| | - Angela Comanducci
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.,Università Campus Bio-Medico di Roma, Rome, Italy
| | - Matteo Fecchio
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, Massachusetts
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30
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Duszyk-Bogorodzka A, Zieleniewska M, Jankowiak-Siuda K. Brain Activity Characteristics of Patients With Disorders of Consciousness in the EEG Resting State Paradigm: A Review. Front Syst Neurosci 2022; 16:654541. [PMID: 35720438 PMCID: PMC9198636 DOI: 10.3389/fnsys.2022.654541] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Accepted: 04/25/2022] [Indexed: 11/13/2022] Open
Abstract
The assessment of the level of consciousness in disorders of consciousness (DoC) is still one of the most challenging problems in contemporary medicine. Nevertheless, based on the multitude of studies conducted over the last 20 years on resting states based on electroencephalography (EEG) in DoC, it is possible to outline the brain activity profiles related to both patients without preserved consciousness and minimally conscious ones. In the case of patients without preserved consciousness, the dominance of low, mostly delta, frequency, and the marginalization of the higher frequencies were observed, both in terms of the global power of brain activity and in functional connectivity patterns. In turn, the minimally conscious patients revealed the opposite brain activity pattern—the characteristics of higher frequency bands were preserved both in global power and in functional long-distance connections. In this short review, we summarize the state of the art of EEG-based research in the resting state paradigm, in the context of providing potential support to the traditional clinical assessment of the level of consciousness.
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Affiliation(s)
- Anna Duszyk-Bogorodzka
- Behavioural Neuroscience Lab, Institute of Psychology, SWPS University of Social Sciences and Humanities, Warsaw, Poland
- *Correspondence: Anna Duszyk-Bogorodzka
| | | | - Kamila Jankowiak-Siuda
- Behavioural Neuroscience Lab, Institute of Psychology, SWPS University of Social Sciences and Humanities, Warsaw, Poland
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31
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Osińska A, Rynkiewicz A, Binder M, Komendziński T, Borowicz A, Leszczyński A. Non-invasive Vagus Nerve Stimulation in Treatment of Disorders of Consciousness – Longitudinal Case Study. Front Neurosci 2022; 16:834507. [PMID: 35600632 PMCID: PMC9120963 DOI: 10.3389/fnins.2022.834507] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 03/29/2022] [Indexed: 11/16/2022] Open
Abstract
Neuromodulatory electroceuticals such as vagus nerve stimulation have been recently gaining traction as potential rehabilitation tools for disorders of consciousness (DoC). We present a longitudinal case study of non-invasive auricular vagus nerve stimulation (taVNS) in a patient diagnosed with chronic unresponsive wakefulness syndrome (previously known as vegetative state). Over a period of 6 months we applied taVNS daily and regularly evaluated the patient’s behavioral outcomes using Coma Recovery Scale – Revised. We also took electrophysiological measures: resting state electroencephalography (EEG), heart rate (HR) and heart rate variability (HRV). All these methods revealed signs of improvement in the patient’s condition. The total CRS-R scores fluctuated but rose from 4 and 6 at initial stages to the heights of 12 and 13 in the 3rd and 5th month, which would warrant a change in diagnosis to a Minimally Conscious State. Scores obtained in a 2 months follow-up period, though, suggest this may not have been a lasting improvement. Behavioral signs of recovery are triangulated by EEG frequency spectrum profiles with re-emergence of a second oscillatory peak in the alpha range, which has been shown to characterize aware people. However, sustained spontaneous theta oscillations did not predictably diminish, which most likely reflects structural brain damage. ECG measures revealed a steady decrease in pre-stimulation HR combined with an increase in HRV-HR. This suggests a gradual withdrawal of sympathetic and an increase in parasympathetic control of the heart, which the previous literature has also linked with DoC improvements. Together, this study suggests that taVNS stimulation holds promise as a DoC treatment.
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Affiliation(s)
- Albertyna Osińska
- Faculty of Psychology, University of Warsaw, Warsaw, Poland
- *Correspondence: Albertyna Osińska,
| | - Andrzej Rynkiewicz
- Faculty of Psychology, University of Warsaw, Warsaw, Poland
- Andrzej Rynkiewicz,
| | - Marek Binder
- Institute of Psychology, Jagiellonian University, Kraków, Poland
| | - Tomasz Komendziński
- Department of Cognitive Science, Faculty of Humanities, Nicolaus Copernicus University in Toruń, Toruń, Poland
| | - Anna Borowicz
- Department of Cognitive Science, Faculty of Humanities, Nicolaus Copernicus University in Toruń, Toruń, Poland
| | - Antoni Leszczyński
- Department of Cognitive Science, Faculty of Humanities, Nicolaus Copernicus University in Toruń, Toruń, Poland
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32
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Cosgrove ME, Saadon JR, Mikell CB, Stefancin PL, Alkadaa L, Wang Z, Saluja S, Servider J, Razzaq B, Huang C, Mofakham S. Thalamo-Prefrontal Connectivity Correlates With Early Command-Following After Severe Traumatic Brain Injury. Front Neurol 2022; 13:826266. [PMID: 35250829 PMCID: PMC8895046 DOI: 10.3389/fneur.2022.826266] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/25/2022] [Indexed: 12/19/2022] Open
Abstract
Recovery of consciousness after traumatic brain injury (TBI) is heterogeneous and difficult to predict. Structures such as the thalamus and prefrontal cortex are thought to be important in facilitating consciousness. We sought to investigate whether the integrity of thalamo-prefrontal circuits, assessed via diffusion tensor imaging (DTI), was associated with the return of goal-directed behavior after severe TBI. We classified a cohort of severe TBI patients (N = 25, 20 males) into Early and Late/Never outcome groups based on their ability to follow commands within 30 days post-injury. We assessed connectivity between whole thalamus, and mediodorsal thalamus (MD), to prefrontal cortex (PFC) subregions including dorsolateral PFC (dlPFC), medial PFC (mPFC), anterior cingulate (ACC), and orbitofrontal (OFC) cortices. We found that the integrity of thalamic projections to PFC subregions (L OFC, L and R ACC, and R mPFC) was significantly associated with Early command-following. This association persisted when the analysis was restricted to prefrontal-mediodorsal (MD) thalamus connectivity. In contrast, dlPFC connectivity to thalamus was not significantly associated with command-following. Using the integrity of thalamo-prefrontal connections, we created a linear regression model that demonstrated 72% accuracy in predicting command-following after a leave-one-out analysis. Together, these data support a role for thalamo-prefrontal connectivity in the return of goal-directed behavior following TBI.
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Affiliation(s)
- Megan E. Cosgrove
- Department of Neurosurgery, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States
| | - Jordan R. Saadon
- Department of Neurosurgery, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States
| | - Charles B. Mikell
- Department of Neurosurgery, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States
| | | | - Leor Alkadaa
- Department of Neurosurgery, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States
| | - Zhe Wang
- Department of Neurosurgery, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States
| | - Sabir Saluja
- Department of Neurosurgery, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States
| | - John Servider
- Department of Neurosurgery, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States
| | - Bayan Razzaq
- Department of Neurosurgery, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States
| | - Chuan Huang
- Department of Radiology, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States
- Department of Psychiatry, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States
| | - Sima Mofakham
- Department of Neurosurgery, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States
- Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, United States
- *Correspondence: Sima Mofakham
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33
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Frohlich J, Crone JS, Johnson MA, Lutkenhoff ES, Spivak NM, Dell'Italia J, Hipp JF, Shrestha V, Ruiz Tejeda JE, Real C, Vespa PM, Monti MM. Neural oscillations track recovery of consciousness in acute traumatic brain injury patients. Hum Brain Mapp 2022; 43:1804-1820. [PMID: 35076993 PMCID: PMC8933330 DOI: 10.1002/hbm.25725] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 10/26/2021] [Accepted: 11/07/2021] [Indexed: 11/25/2022] Open
Abstract
Electroencephalography (EEG), easily deployed at the bedside, is an attractive modality for deriving quantitative biomarkers of prognosis and differential diagnosis in severe brain injury and disorders of consciousness (DOC). Prior work by Schiff has identified four dynamic regimes of progressive recovery of consciousness defined by the presence or absence of thalamically‐driven EEG oscillations. These four predefined categories (ABCD model) relate, on a theoretical level, to thalamocortical integrity and, on an empirical level, to behavioral outcome in patients with cardiac arrest coma etiologies. However, whether this theory‐based stratification of patients might be useful as a diagnostic biomarker in DOC and measurably linked to thalamocortical dysfunction remains unknown. In this work, we relate the reemergence of thalamically‐driven EEG oscillations to behavioral recovery from traumatic brain injury (TBI) in a cohort of N = 38 acute patients with moderate‐to‐severe TBI and an average of 1 week of EEG recorded per patient. We analyzed an average of 3.4 hr of EEG per patient, sampled to coincide with 30‐min periods of maximal behavioral arousal. Our work tests and supports the ABCD model, showing that it outperforms a data‐driven clustering approach and may perform equally well compared to a more parsimonious categorization. Additionally, in a subset of patients (N = 11), we correlated EEG findings with functional magnetic resonance imaging (fMRI) connectivity between nodes in the mesocircuit—which has been theoretically implicated by Schiff in DOC—and report a trend‐level relationship that warrants further investigation in larger studies.
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Affiliation(s)
- Joel Frohlich
- Department of Psychology University of California Los Angeles Los Angeles California USA
| | - Julia S. Crone
- Department of Psychology University of California Los Angeles Los Angeles California USA
- Vienna Cognitive Science Hub University of Vienna Vienna Austria
| | - Micah A. Johnson
- Department of Psychology University of California Los Angeles Los Angeles California USA
| | - Evan S. Lutkenhoff
- Department of Psychology University of California Los Angeles Los Angeles California USA
| | - Norman M. Spivak
- Department of Neurosurgery UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles Los Angeles California USA
| | - John Dell'Italia
- Department of Psychology University of California Los Angeles Los Angeles California USA
| | - Joerg F. Hipp
- Roche Pharma Research and Early Development Roche Innovation Center Basel Basel Switzerland
| | - Vikesh Shrestha
- Department of Neurosurgery UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles Los Angeles California USA
| | - Jesús E. Ruiz Tejeda
- Department of Neurosurgery UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles Los Angeles California USA
| | - Courtney Real
- Department of Neurosurgery UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles Los Angeles California USA
| | - Paul M. Vespa
- Department of Neurosurgery UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles Los Angeles California USA
| | - Martin M. Monti
- Department of Psychology University of California Los Angeles Los Angeles California USA
- Department of Neurosurgery UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles Los Angeles California USA
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34
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Guo Y, Cho SM, Wei Z, Wang Q, Modi HR, Gharibani P, Lu H, Thakor NV, Geocadin RG. Early Thalamocortical Reperfusion Leads to Neurologic Recovery in a Rodent Cardiac Arrest Model. Neurocrit Care 2022; 37:60-72. [PMID: 35072925 DOI: 10.1007/s12028-021-01432-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 12/29/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Cerebral blood flow (CBF) plays an important role in neurological recovery after cardiac arrest (CA) resuscitation. However, the variations of CBF recovery in distinct brain regions and its correlation with neurologic recovery after return of spontaneous circulation (ROSC) have not been characterized. This study aimed to investigate the characteristics of regional cerebral reperfusion following resuscitation in predicting neurological recovery. METHODS Twelve adult male Wistar rats were studied, ten resuscitated from 7-min asphyxial CA and two uninjured rats, which were designated as healthy controls (HCs). Dynamic changes in CBF in the cerebral cortex, hippocampus, thalamus, brainstem, and cerebellum were assessed by pseudocontinuous arterial spin labeling magnetic resonance imaging, starting at 60 min after ROSC to 156 min (or time to spontaneous arousal). Neurologic outcomes were evaluated by the neurologic deficit scale at 24 h post-ROSC in a blinded manner. Correlations between regional CBF (rCBF) and neurological recovery were undertaken. RESULTS All post-CA animals were found to be nonresponsive during the 60-156 min post ROSC, with reductions in rCBF by 24-42% compared with HC. Analyses of rCBF during the post-ROSC time window from 60 to 156 min showed the rCBF recovery of hippocampus and thalamus were positively associated with better neurological outcomes (rs = 0.82, p = 0.004 and rs = 0.73, p < 0.001, respectively). During 96 min before arousal, thalamic and cortical rCBF exhibited positive correlations with neurological recovery (rs = 0.80, p < 0.001 and rs = 0.65, p < 0.001, respectively); for predicting a favorable neurological outcome, the thalamic rCBF threshold was above 50.84 ml/100 g/min (34% of HC) (area under the curve of 0.96), whereas the cortical rCBF threshold was above 60.43 ml/100 g/min (38% of HC) (area under the curve of 0.88). CONCLUSIONS Early magnetic resonance imaging analyses showed early rCBF recovery in thalamus, hippocampus, and cortex post ROSC was positively correlated with neurological outcomes at 24 h. Our findings suggest new translational insights into the regional reperfusion and the time window that may be critical in neurological recovery and warrant further validation.
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Affiliation(s)
- Yu Guo
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sung-Min Cho
- Departments of Neurology, Anesthesiology, Critical Care Medicine and Neurosurgery, Johns Hopkins University School of Medicine, 600 N Wolfe Street, Phipps 455, Baltimore, MD, 21287, USA
| | - Zhiliang Wei
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Qihong Wang
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hiren R Modi
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Payam Gharibani
- Departments of Neurology, Division of Neuroimmunology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hanzhang Lu
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nitish V Thakor
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Romergryko G Geocadin
- Departments of Neurology, Anesthesiology, Critical Care Medicine and Neurosurgery, Johns Hopkins University School of Medicine, 600 N Wolfe Street, Phipps 455, Baltimore, MD, 21287, USA.
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35
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Frohlich J, Johnson MA, McArthur DL, Lutkenhoff ES, Dell'Italia J, Real C, Shrestha V, Spivak NM, Ruiz Tejeda JE, Vespa PM, Monti MM. Sedation-Induced Burst Suppression Predicts Positive Outcome Following Traumatic Brain Injury. Front Neurol 2022; 12:750667. [PMID: 35002918 PMCID: PMC8727767 DOI: 10.3389/fneur.2021.750667] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 11/19/2021] [Indexed: 11/24/2022] Open
Abstract
While electroencephalogram (EEG) burst-suppression is often induced therapeutically using sedatives in the intensive care unit (ICU), there is hitherto no evidence with respect to its association to outcome in moderate-to-severe neurological patients. We examined the relationship between sedation-induced burst-suppression (SIBS) and outcome at hospital discharge and at 6-month follow up in patients surviving moderate-to-severe traumatic brain injury (TBI). For each of 32 patients recovering from coma after moderate-to-severe TBI, we measured the EEG burst suppression ratio (BSR) during periods of low responsiveness as assessed with the Glasgow Coma Scale (GCS). The maximum BSR was then used to predict the Glasgow Outcome Scale extended (GOSe) at discharge and at 6 months post-injury. A multi-model inference approach was used to assess the combination of predictors that best fit the outcome data. We found that BSR was positively associated with outcomes at 6 months (P = 0.022) but did not predict outcomes at discharge. A mediation analysis found no evidence that BSR mediates the effects of barbiturates or propofol on outcomes. Our results provide initial observational evidence that burst suppression may be neuroprotective in acute patients with TBI etiologies. SIBS may thus be useful in the ICU as a prognostic biomarker.
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Affiliation(s)
- Joel Frohlich
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Micah A Johnson
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States
| | - David L McArthur
- Department of Neurosurgery, Brain Injury Research Center (BIRC), UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Evan S Lutkenhoff
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States
| | - John Dell'Italia
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Courtney Real
- Department of Neurosurgery, Brain Injury Research Center (BIRC), UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Vikesh Shrestha
- Department of Neurosurgery, Brain Injury Research Center (BIRC), UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Norman M Spivak
- Department of Neurosurgery, Brain Injury Research Center (BIRC), UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Jesús E Ruiz Tejeda
- Department of Neurosurgery, Brain Injury Research Center (BIRC), UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Paul M Vespa
- Department of Neurosurgery, Brain Injury Research Center (BIRC), UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Martin M Monti
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Neurosurgery, Brain Injury Research Center (BIRC), UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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36
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Mofakham S, Liu Y, Hensley A, Saadon JR, Gammel T, Cosgrove ME, Adachi J, Mohammad S, Huang C, Djurić PM, Mikell CB. Injury to thalamocortical projections following traumatic brain injury results in attractor dynamics for cortical networks. Prog Neurobiol 2022; 210:102215. [PMID: 34995694 DOI: 10.1016/j.pneurobio.2022.102215] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 12/29/2021] [Accepted: 01/03/2022] [Indexed: 12/11/2022]
Abstract
Major theories of consciousness predict that complex electroencephalographic (EEG) activity is required for consciousness, yet it is not clear how such activity arises in the corticothalamic system. The thalamus is well-known to control cortical excitability via interlaminar projections, but whether thalamic input is needed for complexity is not known. We hypothesized that the thalamus facilitates complex activity by adjusting synaptic connectivity, thereby increasing the availability of different configurations of cortical neurons (cortical "states"), as well as the probability of state transitions. To test this hypothesis, we characterized EEG activity from prefrontal cortex (PFC) in traumatic brain injury (TBI) patients with and without injuries to thalamocortical projections, measured with diffusion tensor imaging (DTI). We found that injury to thalamic projections (especially from the mediodorsal thalamus) was strongly associated with unconsciousness and delta-band EEG activity. Using advanced signal processing techniques, we found that lack of thalamic input led to 1.) attractor dynamics for cortical networks with a tendency to visit the same states, 2.) a reduced repertoire of possible states, and 3.) high predictability of transitions between states. These results imply that complex PFC activity associated with consciousness depends on thalamic input. Our model implies that restoration of cortical connectivity is a critical function of the thalamus after brain injury. We draw a critical connection between thalamic input and complex cortical activity associated with consciousness.
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Affiliation(s)
- Sima Mofakham
- Department of Neurosurgery, Stony Brook University Hospital, Stony Brook, NY, USA; Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA.
| | - Yuhao Liu
- Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Asher Hensley
- Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Jordan R Saadon
- Department of Neurosurgery, Stony Brook University Hospital, Stony Brook, NY, USA
| | - Theresa Gammel
- Department of Neurosurgery, Stony Brook University Hospital, Stony Brook, NY, USA
| | - Megan E Cosgrove
- Department of Neurosurgery, Stony Brook University Hospital, Stony Brook, NY, USA
| | - Joseph Adachi
- Department of Neurosurgery, Stony Brook University Hospital, Stony Brook, NY, USA
| | - Selma Mohammad
- Department of Neurosurgery, Stony Brook University Hospital, Stony Brook, NY, USA
| | - Chuan Huang
- Department of Radiology, Stony Brook University Hospital, Stony Brook, NY, USA; Department of Psychiatry, Stony Brook University Hospital, Stony Brook, NY, USA
| | - Petar M Djurić
- Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Charles B Mikell
- Department of Neurosurgery, Stony Brook University Hospital, Stony Brook, NY, USA
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37
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Forgacs PB, Allen BB, Wu X, Gerber LM, Boddu S, Fakhar M, Stieg PE, Schiff ND, Mangat HS. Corticothalamic Connectivity in Aneurysmal Subarachnoid Hemorrhage: Relationship with Disordered Consciousness and Clinical Outcomes. Neurocrit Care 2021; 36:760-771. [PMID: 34669180 DOI: 10.1007/s12028-021-01354-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 09/10/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND We present an exploratory analysis of the occurrence of early corticothalamic connectivity disruption after aneurysmal subarachnoid hemorrhage (SAH) and its correlation with clinical outcomes. METHODS We conducted a retrospective study of patients with acute SAH who underwent continuous electroencephalography (EEG) for impairment of consciousness. Only patients undergoing endovascular aneurysm treatment were included. Continuous EEG tracings were reviewed to obtain artifact-free segments. Power spectral analyses were performed, and segments were classified as A (only delta power), B (predominant delta and theta), C (predominant theta and beta), or D (predominant alpha and beta). Each incremental category from A to D implies greater preservation of corticothalamic connectivity. We dichotomized categories as AB for poor connectivity and CD for good connectivity. The modified Rankin Scale score at follow-up and in-hospital mortality were used as outcome measures. RESULTS Sixty-nine patients were included, of whom 58 had good quality EEG segments for classification: 28 were AB and 30 were CD. Hunt and Hess and World Federation of Neurological Surgeons grades were higher and the initial Glasgow Coma Scale score was lower in the AB group compared with the CD group. AB classification was associated with an adjusted odds ratio of 5.71 (95% confidence interval 1.61-20.30; p < 0.01) for poor outcome (modified Rankin Scale score 4-6) at a median follow-up of 4 months (interquartile range 2-6) and an odds ratio of 5.6 (95% confidence interval 0.98-31.95; p = 0.03) for in-hospital mortality, compared with CD. CONCLUSIONS EEG spectral-power-based classification demonstrates early corticothalamic connectivity disruption following aneurysmal SAH and may be a mechanism involved in early brain injury. Furthermore, the extent of this disruption appears to be associated with functional outcome and in-hospital mortality in patients with aneurysmal SAH and appears to be a potentially useful predictive tool that must be validated prospectively.
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Affiliation(s)
- Peter B Forgacs
- Department of Neurology, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, 525 E 68 Street, 610, New York, NY, 10065, USA
| | - Baxter B Allen
- Department of Neurology, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, 525 E 68 Street, 610, New York, NY, 10065, USA
| | - Xian Wu
- Department of Population Health Sciences, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, New York, NY, USA
| | - Linda M Gerber
- Department of Population Health Sciences, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, New York, NY, USA
| | - Srikanth Boddu
- Department of Neurological Surgery, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, New York, NY, USA
| | - Malik Fakhar
- Department of Neurology, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, 525 E 68 Street, 610, New York, NY, 10065, USA.,Department of Neurology, University of Arizona College of Medicine, Phoenix, AZ, USA
| | - Philip E Stieg
- Department of Neurological Surgery, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, New York, NY, USA
| | - Nicholas D Schiff
- Department of Neurology, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, 525 E 68 Street, 610, New York, NY, 10065, USA
| | - Halinder S Mangat
- Department of Neurology, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, 525 E 68 Street, 610, New York, NY, 10065, USA. .,Department of Neurological Surgery, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, New York, NY, USA.
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Complementary roles of neural synchrony and complexity for indexing consciousness and chances of surviving in acute coma. Neuroimage 2021; 245:118638. [PMID: 34624502 DOI: 10.1016/j.neuroimage.2021.118638] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 09/28/2021] [Accepted: 10/05/2021] [Indexed: 11/23/2022] Open
Abstract
An open challenge in consciousness research is understanding how neural functions are altered by pathological loss of consciousness. To maintain consciousness, the brain needs synchronized communication of information across brain regions, and sufficient complexity in neural activity. Coordination of brain activity, typically indexed through measures of neural synchrony, has been shown to decrease when consciousness is lost and to reflect the clinical state of patients with disorders of consciousness. Moreover, when consciousness is lost, neural activity loses complexity, while the levels of neural noise, indexed by the slope of the electroencephalography (EEG) spectral exponent decrease. Although these properties have been well investigated in resting state activity, it remains unknown whether the sensory processing network, which has been shown to be preserved in coma, suffers from a loss of synchronization or information content. Here, we focused on acute coma and hypothesized that neural synchrony in response to auditory stimuli would reflect coma severity, while complexity, or neural noise, would reflect the presence or loss of consciousness. Results showed that neural synchrony of EEG signals was stronger for survivors than non-survivors and predictive of patients' outcome, but indistinguishable between survivors and healthy controls. Measures of neural complexity and neural noise were not informative of patients' outcome and had high or low values for patients compared to controls. Our results suggest different roles for neural synchrony and complexity in acute coma. Synchrony represents a precondition for consciousness, while complexity needs an equilibrium between high or low values to support conscious cognition.
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Bauerschmidt A, Eliseyev A, Doyle KW, Velasquez A, Egbebike J, Chiu W, Kumar V, Alkhachroum A, Der Nigoghossian C, Al-Mufti F, Rabbani L, Brodie D, Rubinos C, Park S, Roh D, Agarwal S, Claassen J. Predicting early recovery of consciousness after cardiac arrest supported by quantitative electroencephalography. Resuscitation 2021; 165:130-137. [PMID: 34166746 PMCID: PMC10008439 DOI: 10.1016/j.resuscitation.2021.06.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 06/03/2021] [Accepted: 06/16/2021] [Indexed: 01/27/2023]
Abstract
OBJECTIVE To determine the ability of quantitative electroencephalography (QEEG) to improve the accuracy of predicting recovery of consciousness by post-cardiac arrest day 10. METHODS Unconscious survivors of cardiac arrest undergoing daily clinical and EEG assessments through post-cardiac arrest day 10 were studied in a prospective observational cohort study. Power spectral density, local coherence, and permutation entropy were calculated from daily EEG clips following a painful stimulus. Recovery of consciousness was defined as following at least simple commands by day 10. We determined the impact of EEG metrics to predict recovery when analyzed with established predictors of recovery using partial least squares regression models. Explained variance analysis identified which features contributed most to the predictive model. RESULTS 367 EEG epochs from 98 subjects were analyzed in conjunction with clinical measures. Highest prediction accuracy was achieved when adding QEEG features from post-arrest days 4-6 to established predictors (area under the receiver operating curve improved from 0.81 ± 0.04 to 0.86 ± 0.05). Prediction accuracy decreased from 0.84 ± 0.04 to 0.79 ± 0.04 when adding QEEG features from post-arrest days 1-3. Patients with recovery of command-following by day 10 showed higher coherence across the frequency spectrum and higher centro-occipital delta-frequency spectral power by days 4-6, and globally-higher theta range permutation entropy by days 7-10. CONCLUSIONS Adding quantitative EEG metrics to established predictors of recovery allows modest improvement of prediction accuracy for recovery of consciousness, when obtained within a week of cardiac arrest. Further research is needed to determine the best strategy for integration of QEEG data into prognostic models in this patient population.
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Affiliation(s)
- Andrew Bauerschmidt
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Andrey Eliseyev
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Kevin W Doyle
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Angela Velasquez
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Jennifer Egbebike
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Wendy Chiu
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Vedika Kumar
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Ayham Alkhachroum
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | | | - Fawaz Al-Mufti
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - LeRoy Rabbani
- Cardiac Care Unit, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Daniel Brodie
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Clio Rubinos
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Soojin Park
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - David Roh
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Sachin Agarwal
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, New York, NY, USA.
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40
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Claassen J, Akbari Y, Alexander S, Bader MK, Bell K, Bleck TP, Boly M, Brown J, Chou SHY, Diringer MN, Edlow BL, Foreman B, Giacino JT, Gosseries O, Green T, Greer DM, Hanley DF, Hartings JA, Helbok R, Hemphill JC, Hinson HE, Hirsch K, Human T, James ML, Ko N, Kondziella D, Livesay S, Madden LK, Mainali S, Mayer SA, McCredie V, McNett MM, Meyfroidt G, Monti MM, Muehlschlegel S, Murthy S, Nyquist P, Olson DM, Provencio JJ, Rosenthal E, Sampaio Silva G, Sarasso S, Schiff ND, Sharshar T, Shutter L, Stevens RD, Vespa P, Videtta W, Wagner A, Ziai W, Whyte J, Zink E, Suarez JI. Proceedings of the First Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness. Neurocrit Care 2021; 35:4-23. [PMID: 34236619 PMCID: PMC8264966 DOI: 10.1007/s12028-021-01260-x] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 04/15/2021] [Indexed: 01/04/2023]
Abstract
Coma and disorders of consciousness (DoC) are highly prevalent and constitute a burden for patients, families, and society worldwide. As part of the Curing Coma Campaign, the Neurocritical Care Society partnered with the National Institutes of Health to organize a symposium bringing together experts from all over the world to develop research targets for DoC. The conference was structured along six domains: (1) defining endotype/phenotypes, (2) biomarkers, (3) proof-of-concept clinical trials, (4) neuroprognostication, (5) long-term recovery, and (6) large datasets. This proceedings paper presents actionable research targets based on the presentations and discussions that occurred at the conference. We summarize the background, main research gaps, overall goals, the panel discussion of the approach, limitations and challenges, and deliverables that were identified.
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Affiliation(s)
- Jan Claassen
- Department of Neurology, Columbia University and New York-Presbyterian Hospital, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York City, NY, 10032, USA.
| | - Yama Akbari
- Departments of Neurology, Neurological Surgery, and Anatomy & Neurobiology and Beckman Laser Institute and Medical Clinic, University of California, Irvine, Irvine, CA, USA
| | - Sheila Alexander
- Acute and Tertiary Care, School of Nursing and Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Kathleen Bell
- Department of Physical Medicine and Rehabilitation, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Thomas P Bleck
- Davee Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Melanie Boly
- Department of Neurology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Jeremy Brown
- Office of Emergency Care Research, Division of Clinical Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Sherry H-Y Chou
- Departments of Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael N Diringer
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Brian L Edlow
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Harvard University, Boston, MA, USA
| | - Brandon Foreman
- Departments of Neurology and Rehabilitation Medicine, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Olivia Gosseries
- GIGA Consciousness After Coma Science Group, University of Liege, Liege, Belgium
| | - Theresa Green
- School of Nursing, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - David M Greer
- Department of Neurology, School of Medicine, Boston University, Boston, MA, USA
| | - Daniel F Hanley
- Division of Brain Injury Outcomes, Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jed A Hartings
- Department of Neurosurgery, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Raimund Helbok
- Neurocritical Care Unit, Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - J Claude Hemphill
- Department of Neurology, Weill Institute for Neurosciences, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - H E Hinson
- Department of Neurology, School of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Karen Hirsch
- Department of Neurology, Stanford University, Palo Alto, CA, USA
| | - Theresa Human
- Department of Pharmacy, Barnes Jewish Hospital, St. Louis, MO, USA
| | - Michael L James
- Departments of Anesthesiology and Neurology, Duke University, Durham, NC, USA
| | - Nerissa Ko
- Department of Neurology, Weill Institute for Neurosciences, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Daniel Kondziella
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Sarah Livesay
- College of Nursing, Rush University, Chicago, IL, USA
| | - Lori K Madden
- Center for Nursing Science, University of California, Davis, Sacramento, CA, USA
| | - Shraddha Mainali
- Department of Neurology, The Ohio State University, Columbus, OH, USA
| | - Stephan A Mayer
- Department of Neurology, New York Medical College, Valhalla, NY, USA
| | - Victoria McCredie
- Interdepartmental Division of Critical Care, Department of Respirology, University of Toronto, Toronto, ON, Canada
| | - Molly M McNett
- College of Nursing, The Ohio State University, Columbus, OH, USA
| | - Geert Meyfroidt
- Department of Intensive Care Medicine, University Hospitals Leuven and University of Leuven, Leuven, Belgium
| | - Martin M Monti
- Departments of Neurosurgery and Psychology, Brain Injury Research Center, University of California, Los Angeles, Los Angeles, CA, USA
| | - Susanne Muehlschlegel
- Departments of Neurology, Anesthesiology/Critical Care, and Surgery, Medical School, University of Massachusetts, Worcester, MA, USA
| | - Santosh Murthy
- Department of Neurology, Weill Cornell Medical College, New York City, NY, USA
| | - Paul Nyquist
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - DaiWai M Olson
- Departments of Neurology and Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - J Javier Provencio
- Departments of Neurology and Neuroscience, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Eric Rosenthal
- Department of Neurology, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Gisele Sampaio Silva
- Department of Neurology, Albert Einstein Israelite Hospital and Universidade Federal de São Paulo, São Paulo, Brazil
| | - Simone Sarasso
- Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan, Italy
| | - Nicholas D Schiff
- Department of Neurology and Brain Mind Research Institute, Weill Cornell Medicine, Cornell University, New York City, NY, USA
| | - Tarek Sharshar
- Department of Intensive Care, Paris Descartes University, Paris, France
| | - Lori Shutter
- Departments of Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert D Stevens
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Paul Vespa
- Departments of Neurosurgery and Neurology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Walter Videtta
- National Hospital Alejandro Posadas, Buenos Aires, Argentina
| | - Amy Wagner
- Department of Physical Medicine and Rehabilitation, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wendy Ziai
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - John Whyte
- Moss Rehabilitation Research Institute, Elkins Park, PA, USA
| | - Elizabeth Zink
- Division of Neurosciences Critical Care, Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jose I Suarez
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
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41
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Edlow BL, Claassen J, Schiff ND, Greer DM. Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies. Nat Rev Neurol 2021; 17:135-156. [PMID: 33318675 PMCID: PMC7734616 DOI: 10.1038/s41582-020-00428-x] [Citation(s) in RCA: 238] [Impact Index Per Article: 79.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/23/2020] [Indexed: 12/16/2022]
Abstract
Substantial progress has been made over the past two decades in detecting, predicting and promoting recovery of consciousness in patients with disorders of consciousness (DoC) caused by severe brain injuries. Advanced neuroimaging and electrophysiological techniques have revealed new insights into the biological mechanisms underlying recovery of consciousness and have enabled the identification of preserved brain networks in patients who seem unresponsive, thus raising hope for more accurate diagnosis and prognosis. Emerging evidence suggests that covert consciousness, or cognitive motor dissociation (CMD), is present in up to 15-20% of patients with DoC and that detection of CMD in the intensive care unit can predict functional recovery at 1 year post injury. Although fundamental questions remain about which patients with DoC have the potential for recovery, novel pharmacological and electrophysiological therapies have shown the potential to reactivate injured neural networks and promote re-emergence of consciousness. In this Review, we focus on mechanisms of recovery from DoC in the acute and subacute-to-chronic stages, and we discuss recent progress in detecting and predicting recovery of consciousness. We also describe the developments in pharmacological and electrophysiological therapies that are creating new opportunities to improve the lives of patients with DoC.
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Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, New York Presbyterian Hospital, New York, NY, USA
| | - Nicholas D Schiff
- Feil Family Brain Mind Research Institute, Weill Cornell Medical College, New York, NY, USA
| | - David M Greer
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA.
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42
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Calderon DP, Schiff ND. Objective and graded calibration of recovery of consciousness in experimental models. Curr Opin Neurol 2021; 34:142-149. [PMID: 33278146 PMCID: PMC7866679 DOI: 10.1097/wco.0000000000000895] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE OF REVIEW Experimental preclinical models of recovery of consciousness (ROC) and anesthesia emergence are crucial for understanding the neuronal circuits restoring arousal during coma emergence. Such models can also potentially help to better understand how events during coma emergence facilitate or hinder recovery from brain injury. Here we provide an overview of current methods used to assess ROC/level of arousal in animal models. This exposes the need for objective approaches to calibrate arousal levels. We outline how correlation of measured behaviors and their reestablishment at multiple stages with cellular, local and broader neuronal networks, gives a fuller understanding of ROC. RECENT FINDINGS Animals emerging from diverse coma-like states share a dynamic process of cortical and behavioral recovery that reveals distinct states consistently sequenced from low-to-high arousal level and trackable in nonhuman primates and rodents. Neuronal activity modulation of layer V-pyramidal neurons and neuronal aggregates within the brainstem and thalamic nuclei play critical roles at specific stages to promote restoration of a conscious state. SUMMARY A comprehensive, graded calibration of cortical, physiological, and behavioral changes in animal models is undoubtedly needed to establish an integrative framework. This approach reveals the contribution of local and systemic neuronal circuits to the underlying mechanisms for recovering consciousness.
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Affiliation(s)
| | - Nicholas D Schiff
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, New York, USA
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43
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Comanducci A, Boly M, Claassen J, De Lucia M, Gibson RM, Juan E, Laureys S, Naccache L, Owen AM, Rosanova M, Rossetti AO, Schnakers C, Sitt JD, Schiff ND, Massimini M. Clinical and advanced neurophysiology in the prognostic and diagnostic evaluation of disorders of consciousness: review of an IFCN-endorsed expert group. Clin Neurophysiol 2020; 131:2736-2765. [PMID: 32917521 DOI: 10.1016/j.clinph.2020.07.015] [Citation(s) in RCA: 91] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 07/06/2020] [Accepted: 07/26/2020] [Indexed: 12/13/2022]
Abstract
The analysis of spontaneous EEG activity and evoked potentialsis a cornerstone of the instrumental evaluation of patients with disorders of consciousness (DoC). Thepast few years have witnessed an unprecedented surge in EEG-related research applied to the prediction and detection of recovery of consciousness after severe brain injury,opening up the prospect that new concepts and tools may be available at the bedside. This paper provides a comprehensive, critical overview of bothconsolidated and investigational electrophysiological techniquesfor the prognostic and diagnostic assessment of DoC.We describe conventional clinical EEG approaches, then focus on evoked and event-related potentials, and finally we analyze the potential of novel research findings. In doing so, we (i) draw a distinction between acute, prolonged and chronic phases of DoC, (ii) attempt to relate both clinical and research findings to the underlying neuronal processes and (iii) discuss technical and conceptual caveats.The primary aim of this narrative review is to bridge the gap between standard and emerging electrophysiological measures for the detection and prediction of recovery of consciousness. The ultimate scope is to provide a reference and common ground for academic researchers active in the field of neurophysiology and clinicians engaged in intensive care unit and rehabilitation.
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Affiliation(s)
- A Comanducci
- IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy
| | - M Boly
- Department of Neurology and Department of Psychiatry, University of Wisconsin, Madison, USA; Wisconsin Institute for Sleep and Consciousness, Department of Psychiatry, University of Wisconsin-Madison, Madison, USA
| | - J Claassen
- Department of Neurology, Columbia University Medical Center, New York Presbyterian Hospital, New York, NY, USA
| | - M De Lucia
- Laboratoire de Recherche en Neuroimagerie, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - R M Gibson
- The Brain and Mind Institute and the Department of Physiology and Pharmacology, Western Interdisciplinary Research Building, N6A 5B7 University of Western Ontario, London, Ontario, Canada
| | - E Juan
- Wisconsin Institute for Sleep and Consciousness, Department of Psychiatry, University of Wisconsin-Madison, Madison, USA; Amsterdam Brain and Cognition, Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
| | - S Laureys
- Coma Science Group, Centre du Cerveau, GIGA-Consciousness, University and University Hospital of Liège, 4000 Liège, Belgium; Fondazione Europea per la Ricerca Biomedica Onlus, Milan 20063, Italy
| | - L Naccache
- Inserm U 1127, CNRS UMR 7225, Institut du Cerveau et de la Moelle épinière, ICM, Paris, France; Sorbonne Université, UPMC Université Paris 06, Faculté de Médecine Pitié-Salpêtrière, Paris, France
| | - A M Owen
- The Brain and Mind Institute and the Department of Physiology and Pharmacology, Western Interdisciplinary Research Building, N6A 5B7 University of Western Ontario, London, Ontario, Canada
| | - M Rosanova
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, Italy; Fondazione Europea per la Ricerca Biomedica Onlus, Milan 20063, Italy
| | - A O Rossetti
- Neurology Service, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - C Schnakers
- Research Institute, Casa Colina Hospital and Centers for Healthcare, Pomona, CA, USA
| | - J D Sitt
- Inserm U 1127, CNRS UMR 7225, Institut du Cerveau et de la Moelle épinière, ICM, Paris, France
| | - N D Schiff
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA
| | - M Massimini
- IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy; Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, Italy
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44
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Provencio JJ, Hemphill JC, Claassen J, Edlow BL, Helbok R, Vespa PM, Diringer MN, Polizzotto L, Shutter L, Suarez JI, Stevens RD, Hanley DF, Akbari Y, Bleck TP, Boly M, Foreman B, Giacino JT, Hartings JA, Human T, Kondziella D, Ling GSF, Mayer SA, McNett M, Menon DK, Meyfroidt G, Monti MM, Park S, Pouratian N, Puybasset L, Rohaut B, Rosenthal ES, Schiff ND, Sharshar T, Wagner A, Whyte J, Olson DM. The Curing Coma Campaign: Framing Initial Scientific Challenges-Proceedings of the First Curing Coma Campaign Scientific Advisory Council Meeting. Neurocrit Care 2020; 33:1-12. [PMID: 32578124 PMCID: PMC7392933 DOI: 10.1007/s12028-020-01028-9] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Coma and disordered consciousness are common manifestations of acute neurological conditions and are among the most pervasive and challenging aspects of treatment in neurocritical care. Gaps exist in patient assessment, outcome prognostication, and treatment directed specifically at improving consciousness and cognitive recovery. In 2019, the Neurocritical Care Society (NCS) launched the Curing Coma Campaign in order to address the "grand challenge" of improving the management of patients with coma and decreased consciousness. One of the first steps was to bring together a Scientific Advisory Council including coma scientists, neurointensivists, neurorehabilitationists, and implementation experts in order to address the current scientific landscape and begin to develop a framework on how to move forward. This manuscript describes the proceedings of the first Curing Coma Campaign Scientific Advisory Council meeting which occurred in conjunction with the NCS Annual Meeting in October 2019 in Vancouver. Specifically, three major pillars were identified which should be considered: endotyping of coma and disorders of consciousness, biomarkers, and proof-of-concept clinical trials. Each is summarized with regard to current approach, benefits to the patient, family, and clinicians, and next steps. Integration of these three pillars will be essential to the success of the Curing Coma Campaign as will expanding the "curing coma community" to ensure broad participation of clinicians, scientists, and patient advocates with the goal of identifying and implementing treatments to fundamentally improve the outcome of patients.
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Affiliation(s)
- J Javier Provencio
- Department of Neurology and Neuroscience, University of Virginia, Charlottesville, VA, USA
| | - J Claude Hemphill
- Department of Neurology, Zuckerberg San Francisco General Hospital, University of California, San Francisco, Building 1, Room 101, 1001 Potrero Avenue, San Francisco, CA, 94110, USA.
| | - Jan Claassen
- Department of Neurology, Columbia University Irving Medical Center/New York Presbyterian Hospital, New York, NY, USA
| | - Brian L Edlow
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Raimund Helbok
- Department of Neurology, Neurocritical Care, Medical University of Innsbruck, Innsbruck, Austria
| | - Paul M Vespa
- Departments of Neurology and Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Michael N Diringer
- Department of Neurology, Washington University, Barnes-Jewish Hospital, St Louis, MO, USA
| | - Len Polizzotto
- Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Lori Shutter
- Departments of Critical Care Medicine, Neurology, and Neurosurgery, University of Pittsburgh/UPMC Health System, Pittsburgh, PA, USA
| | - Jose I Suarez
- Departments of Anesthesiology and Critical Care Medicine, Neurology and Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Robert D Stevens
- Departments of Anesthesiology and Critical Care Medicine, Neurology and Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel F Hanley
- Division of Brain Injury Outcomes, Johns Hopkins University, Baltimore, MD, USA
| | - Yama Akbari
- Departments of Neurology, Neurosurgery and the Beckman Laser Institute, University of California-Irvine, Irvine, CA, USA
| | - Thomas P Bleck
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Melanie Boly
- Department of Neurology, University of Wisconsin-Madison, Madison, WI, USA
| | - Brandon Foreman
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati Gardner Neuroscience Institute, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USA
| | - Jed A Hartings
- Department of Neurosurgery, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Theresa Human
- Departments of Neurology and Neurosurgery, Washington University, Barnes-Jewish Hospital, St Louis, MO, USA
| | - Daniel Kondziella
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Geoffrey S F Ling
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Stephan A Mayer
- Departments of Neurology and Neurosurgery, New York Medical College, Valhalla, NY, USA
| | - Molly McNett
- College of Nursing, The Ohio State University, Columbus, OH, USA
| | - David K Menon
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
| | - Geert Meyfroidt
- Department and Laboratory of Intensive Care Medicine, University Hospitals Leuven and KU Leuven, Leuven, Belgium
| | - Martin M Monti
- Department of Psychology, University of California, Los Angeles, CA, USA
| | - Soojin Park
- Department of Neurology, Columbia University Irving Medical Center/New York Presbyterian Hospital, New York, NY, USA
| | - Nader Pouratian
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Louis Puybasset
- Department of Anesthesiology and Critical Care, Sorbonne University, GRC 29, AP-HP, DMU DREAM, Pitié-Salpêtrière Hospital, 75013, Paris, France
| | - Benjamin Rohaut
- Department of Neurology, Neuro-ICU, Sorbonne University, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric S Rosenthal
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Nicholas D Schiff
- Departments of Neurology, Neuroscience, and Medical Ethics, Weill Cornell Medicine, New York, NY, USA
| | - Tarek Sharshar
- Neuro-anesthesiology and Intensive Care Medicine, Sainte-Anne Hospital, Paris-Descartes University, Paris, France
- Experimental Neuropathology, Infection and Epidemiology Department, Institut Pasteur, Paris, France
| | - Amy Wagner
- Department of Physical Medicine and Rehabilitation, Department of Neuroscience, Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA
| | - John Whyte
- Moss Rehabilitation Research Institute, Elkins Park, PA, USA
| | - DaiWai M Olson
- Department of Neurology and Neurotherapeutics, University of Texas Southwestern, Dallas, TX, USA
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45
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Beuchat I, Novy J, Barbella G, Oddo M, Rossetti AO. EEG patterns associated with present cortical SSEP after cardiac arrest. Acta Neurol Scand 2020; 142:181-185. [PMID: 32392619 DOI: 10.1111/ane.13264] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 04/23/2020] [Accepted: 05/05/2020] [Indexed: 11/29/2022]
Abstract
BACKGROUND After cardiac arrest (CA), present cortical somatosensory evoked potentials (N20 response of SSEPs) have low predictive value for good outcome and might be redundant with EEG. AIMS To determine whether specific features, or rather global, standardized EEG assessments, are reliably associated with cortical SSEP occurrence after cardiac arrest (CA). METHODS In a prospective CA registry, EEGs recorded within 72 hours were scored according to the ACNS nomenclature, and also categorized into "benign," "malignant," and "highly malignant." Correlations between EEGs and SSEPs (bilaterally absent vs present), and between EEGs/SSEPs and outcome (good: CPC 1-2) were assessed. RESULTS Among 709 CA episodes, 532 had present N20 and 366 "benign EEGs." While EEG categories as well as background, epileptiform features, and reactivity differed significantly between patients with and without N20 (each P < .001), only "benign EEG" was almost universally associated with present N20: 99.5% (95%CI: 97.9%-99.9%) PPV. The combination of "benign EEG" and present N20 showed similar PPV for good outcome as "benign" EEG alone: 69.0% (95% CI: 65.2-72.4) vs 68.6% (95% CI: 64.9-72.0). CONCLUSION Global EEG ("benign") assessment, rather than single EEG features, can reliably predict cortical SSEP occurrence. SSEP adjunction does not increase EEG prognostic performance toward good outcome. SSEP could therefore be omitted in patients with "benign EEG."
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Affiliation(s)
- Isabelle Beuchat
- Department of Neurology Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne Lausanne Switzerland
- Department of Neurology Brigham and Women's Hospital Harvard Medical School Boston MAUSA
| | - Jan Novy
- Department of Neurology Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne Lausanne Switzerland
| | - Giuseppina Barbella
- Department of Neurology Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne Lausanne Switzerland
- Neurology Unit IRCCS Policlinico San Donato Milan Italy
| | - Mauro Oddo
- Department of Intensive Care Medicine Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne Lausanne Switzerland
| | - Andrea O. Rossetti
- Department of Neurology Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne Lausanne Switzerland
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46
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Alkhachroum A, Eliseyev A, Der-Nigoghossian CA, Rubinos C, Kromm JA, Mathews E, Bauerschmidt A, Doyle K, Velasquez A, Egbebike JA, Calderon AR, Roh DJ, Park S, Agarwal S, Connolly ES, Claassen J. EEG to detect early recovery of consciousness in amantadine-treated acute brain injury patients. J Neurol Neurosurg Psychiatry 2020; 91:675-676. [PMID: 32241920 PMCID: PMC7883843 DOI: 10.1136/jnnp-2019-322645] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 02/24/2020] [Accepted: 03/09/2020] [Indexed: 11/04/2022]
Affiliation(s)
- Ayham Alkhachroum
- Neurology, Columbia University, New York, New York, USA.,Neurology, University of Miami, Miami, Florida, United States.,Neurology, Jackson Memorial Health System, Miami, Florida, United States
| | | | | | - Clio Rubinos
- Neurology, University of North Carolina System, Chapel Hill, North Carolina, USA
| | | | | | | | - Kevin Doyle
- Neurology, Columbia University, New York, New York, USA
| | | | | | - Anna R Calderon
- Neurology, Columbia University, New York, New York, United States
| | - David J Roh
- Neurology, Columbia University, New York, New York, USA
| | - Soojin Park
- Neurocritical Care, Columbia University, New York, New York, USA
| | - Sachin Agarwal
- Neurocritical Care, Columbia University, New York, New York, USA
| | | | - Jan Claassen
- Neurorology, Columbia University, New York, New York, USA
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47
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Kustermann T, Ata Nguepnjo Nguissi N, Pfeiffer C, Haenggi M, Kurmann R, Zubler F, Oddo M, Rossetti AO, De Lucia M. Brain functional connectivity during the first day of coma reflects long-term outcome. NEUROIMAGE-CLINICAL 2020; 27:102295. [PMID: 32563037 PMCID: PMC7305428 DOI: 10.1016/j.nicl.2020.102295] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 04/30/2020] [Accepted: 05/04/2020] [Indexed: 01/02/2023]
Abstract
Coma patients show different connectivity patterns depending on long-term outcome. Time-variance of functional connectivity is an early prognostic marker for coma patients. Connectivity patterns observed in chronic patients may develop early after coma onset.
Objective In patients with disorders of consciousness (DOC), properties of functional brain networks at rest are informative of the degree of consciousness impairment and of long-term outcome. Here we investigate whether connectivity differences between patients with favorable and unfavorable outcome are already present within 24 h of coma onset. Methods We prospectively recorded 63-channel electroencephalography (EEG) at rest during the first day of coma after cardiac arrest. We analyzed 98 adults, of whom 57 survived beyond unresponsive wakefulness. Functional connectivity was estimated by computing the ‘debiased weighted phase lag index’ over epochs of five seconds duration. We evaluated the network’s topological features, including clustering coefficient, path length, modularity and participation coefficient and computed their variance over time. Finally, we estimated the predictive value of these topological features for patients’ outcomes by splitting the patient sample in training and test datasets. Results Group-level analysis revealed lower clustering coefficient, higher modularity and path length variance in patients with favorable compared to those with unfavorable outcomes (p < 0.01). Within all features, the path length variance in the network provided the best positive predictive value (PPV) for favorable outcome and specificity for unfavorable outcome in the test dataset (PPV: 0.83, p < 0.01; specificity: 0.86, p < 0.01) with above-chance negative predictive value and accuracy. Of note, the exclusion of patients with epileptiform activity (20 in total) eliminates all false positive predictions (n = 6) for path length variance. Interpretation Topological features of functional connectivity differ as a function of long-term outcome in patients on the first day of coma. These differences are not interpretable in terms of consciousness levels as all patients were in a deep unconscious state. The time variance of path length is informative of comatose patients’ outcome, as patients with favorable outcome exhibit a richer repertoire of path length than those with unfavorable outcomes.
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Affiliation(s)
- Thomas Kustermann
- Laboratoire de Recherche en Neuroimagerie (LREN), University Hospital (CHUV) & University of Lausanne, Switzerland.
| | | | | | - Matthias Haenggi
- Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Rebekka Kurmann
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Frédéric Zubler
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Mauro Oddo
- Department of Intensive Care Medicine, University Hospital (CHUV) & University of Lausanne, Switzerland
| | - Andrea O Rossetti
- Department of Neurology, University Hospital (CHUV) & University of Lausanne, Switzerland
| | - Marzia De Lucia
- Laboratoire de Recherche en Neuroimagerie (LREN), University Hospital (CHUV) & University of Lausanne, Switzerland
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48
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Ghassemi MM, Amorim E, Alhanai T, Lee JW, Herman ST, Sivaraju A, Gaspard N, Hirsch LJ, Scirica BM, Biswal S, Moura Junior V, Cash SS, Brown EN, Mark RG, Westover MB. Quantitative Electroencephalogram Trends Predict Recovery in Hypoxic-Ischemic Encephalopathy. Crit Care Med 2020; 47:1416-1423. [PMID: 31241498 DOI: 10.1097/ccm.0000000000003840] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
OBJECTIVES Electroencephalogram features predict neurologic recovery following cardiac arrest. Recent work has shown that prognostic implications of some key electroencephalogram features change over time. We explore whether time dependence exists for an expanded selection of quantitative electroencephalogram features and whether accounting for this time dependence enables better prognostic predictions. DESIGN Retrospective. SETTING ICUs at four academic medical centers in the United States. PATIENTS Comatose patients with acute hypoxic-ischemic encephalopathy. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS We analyzed 12,397 hours of electroencephalogram from 438 subjects. From the electroencephalogram, we extracted 52 features that quantify signal complexity, category, and connectivity. We modeled associations between dichotomized neurologic outcome (good vs poor) and quantitative electroencephalogram features in 12-hour intervals using sequential logistic regression with Elastic Net regularization. We compared a predictive model using time-varying features to a model using time-invariant features and to models based on two prior published approaches. Models were evaluated for their ability to predict binary outcomes using area under the receiver operator curve, model calibration (how closely the predicted probability of good outcomes matches the observed proportion of good outcomes), and sensitivity at several common specificity thresholds of interest. A model using time-dependent features outperformed (area under the receiver operator curve, 0.83 ± 0.08) one trained with time-invariant features (0.79 ± 0.07; p < 0.05) and a random forest approach (0.74 ± 0.13; p < 0.05). The time-sensitive model was also the best-calibrated. CONCLUSIONS The statistical association between quantitative electroencephalogram features and neurologic outcome changed over time, and accounting for these changes improved prognostication performance.
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Affiliation(s)
- Mohammad M Ghassemi
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA
| | - Edilberto Amorim
- Department of Neurology, Massachusetts General Hospital, Boston, MA.,Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA
| | - Tuka Alhanai
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA
| | - Jong W Lee
- Department of Neurology, Brigham and Women's Hospital, Boston, MA
| | - Susan T Herman
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA
| | | | - Nicolas Gaspard
- Department of Neurology, Universite Libre de Bruxelles, Brussels, Belgium
| | | | - Benjamin M Scirica
- Division of Cardiology, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Siddharth Biswal
- School of Computer Science, Georgia Institute of Technology, Atlanta, GA
| | | | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Emery N Brown
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA
| | - Roger G Mark
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA.,Information Systems, Beth Israel Deaconess Medical Center, Boston, MA
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49
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Forgacs PB, Devinsky O, Schiff ND. Independent Functional Outcomes after Prolonged Coma following Cardiac Arrest: A Mechanistic Hypothesis. Ann Neurol 2020; 87:618-632. [PMID: 31994749 PMCID: PMC7393600 DOI: 10.1002/ana.25690] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 01/23/2020] [Accepted: 01/23/2020] [Indexed: 01/26/2023]
Abstract
OBJECTIVE Survivors of prolonged (>2 weeks) post-cardiac arrest (CA) coma are expected to remain permanently disabled. We aimed to investigate 3 outlier patients who ultimately achieved independent functional outcomes after prolonged post-CA coma to identify electroencephalographic (EEG) markers of their recovery potential. For validation purposes, we also aimed to evaluate these markers in an independent cohort of post-CA patients. METHODS We identified 3 patients with late recovery from coma (17-37 days) following CA who recovered to functionally independent behavioral levels. We performed spectral power analyses of available EEGs during prominent burst suppression patterns (BSP) present in all 3 patients. Using identical methods, we also assessed the relationship of intraburst spectral power and outcomes in a prospectively enrolled cohort of post-CA patients. We performed chart reviews of common clinical, imaging, and EEG prognostic variables and clinical outcomes for all patients. RESULTS All 3 patients with late recovery from coma lacked evidence of overwhelming cortical injury but demonstrated prominent BSP on EEG. Spectral analyses revealed a prominent theta (~4-7Hz) feature dominating the bursts during BSP in these patients. In the prospective cohort, similar intraburst theta spectral features were evident in patients with favorable outcomes; patients with BSP and unfavorable outcomes showed either no features, transient burst features, or decreasing intraburst frequencies with time. INTERPRETATION BSP with theta (~4-7Hz) peak intraburst spectral power after CA may index a recovery potential. We discuss our results in the context of optimizing metabolic substrate availability and stimulating the corticothalamic system during recovery from prolonged post-CA coma. ANN NEUROL 2020;87:618-632.
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Affiliation(s)
- Peter B. Forgacs
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY 10065, USA
- Department of Neurology, Weill Cornell Medical College, New York, NY 10065, USA
- The Rockefeller University, New York, NY 10065, USA
| | | | - Nicholas D. Schiff
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY 10065, USA
- Department of Neurology, Weill Cornell Medical College, New York, NY 10065, USA
- The Rockefeller University, New York, NY 10065, USA
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50
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Spectral Content of Electroencephalographic Burst-Suppression Patterns May Reflect Neuronal Recovery in Comatose Post-Cardiac Arrest Patients. J Clin Neurophysiol 2019; 36:119-126. [PMID: 30422916 DOI: 10.1097/wnp.0000000000000536] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
PURPOSE To assess the potential biologic significance of variations in burst-suppression patterns (BSPs) after cardiac arrest in relation to recovery of consciousness. In the context of recent theoretical models of BSP, bursting frequency may be representative of underlying network dynamics; discontinuous activation of membrane potential during impaired cellular energetics may promote neuronal rescue. METHODS We reviewed a database of 73 comatose post-cardiac arrest patients who underwent therapeutic hypothermia to assess for the presence of BSP and clinical outcomes. In a subsample of patients with BSP (n = 14), spectral content of burst and suppression periods were quantified using multitaper method. RESULTS Burst-suppression pattern was seen in 45/73 (61%) patients. Comparable numbers of patients with (31.1%) and without (35.7%) BSP regained consciousness by the time of hospital discharge. In addition, in two unique cases, BSP initially resolved and then spontaneously reemerged after completion of therapeutic hypothermia and cessation of sedative medications. Both patients recovered consciousness. Spectral analysis of bursts in all patients regaining consciousness (n = 6) showed a prominent theta frequency (5-7 Hz) feature, but not in age-matched patients with induced BSP who did not recover consciousness (n = 8). CONCLUSIONS The prognostic implications of BSP after hypoxic brain injury may vary based on the intrinsic properties of the underlying brain state itself. The presence of theta activity within bursts may index potential viability of neuronal networks underlying recovery of consciousness; emergence of spontaneous BSP in some cases may indicate an innate neuroprotective mechanism. This study highlights the need for better characterization of various BSP patterns after cardiac arrest.
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