BACKGROUND: Resting-state electroencephalography (rsEEG) is usually obtained to assess seizures in comatose patients with traumatic brain injury (TBI). We aim to investigate rsEEG measures and their prediction of early recovery of consciousness in patients with TBI. METHODS: This is a retrospective study of comatose patients with TBI who were admitted to a trauma center (October 2013 to January 2022). Demographics, basic clinical data, imaging characteristics, and EEGs were collected. We calculated the following using 10-min rsEEGs: power spectral density, permutation entropy (complexity measure), weighted symbolic mutual information (wSMI, global information sharing measure), Kolmogorov complexity (Kolcom, complexity measure), and heart-evoked potentials (the averaged EEG signal relative to the corresponding QRS complex on electrocardiography). We evaluated the prediction of consciousness recovery before hospital discharge using clinical, imaging, and rsEEG data via a support vector machine. RESULTS: We studied 113 of 134 (84%) patients with rsEEGs. A total of 73 (65%) patients recovered consciousness before discharge. Patients who recovered consciousness were younger (40 vs. 50 years, p = 0.01). Patients who recovered also had higher Kolcom (U = 1688, p = 0.01), increased beta power (U = 1,652 p = 0.003) with higher variability across channels (U = 1534, p = 0.034) and epochs (U = 1711, p = 0.004), lower delta power (U = 981, p = 0.04), and higher connectivity across time and channels as measured by wSMI in the theta band (U = 1636, p = 0.026; U = 1639, p = 0.024) than those who did not recover. The area under the receiver operating characteristic curve for rsEEG was higher than that for clinical data (using age, motor response, pupil reactivity) and higher than that for the Marshall computed tomography classification (0.69 vs. 0.66 vs. 0.56, respectively; p < 0.001). CONCLUSIONS: We describe the rsEEG signature in recovery of consciousness prior to discharge in comatose patients with TBI. rsEEG measures performed modestly better than the clinical and imaging data in predicting recovery.
Background Resting-state electroencephalogram (rsEEG) is usually obtained to assess seizures in comatose patients with traumatic brain injury (TBI) patients. We aim to investigate rsEEG measures and their prediction of early recovery of consciousness in comatose TBI patients. Methods This is a retrospective study of comatose TBI patients who were admitted to a level-1 trauma center (10/2013-1/2022). Demographics, basic clinical data, imaging characteristics, and EEG data were collected. We calculated using 10-minute rsEEGs: power spectral density (PSD), permutation entropy (PE - complexity measure), weighted symbolic-mutual-information (wSMI - global information sharing measure), Kolmogorov complexity (Kolcom - complexity measure), and heart-evoked potentials (HEP - the averaged EEG signal relative to the corresponding QRS complex on electrocardiogram). We evaluated the prediction of consciousness recovery before hospital discharge using clinical, imaging, rsEEG data via Support Vector Machine with a linear kernel (SVM). Results We studied 113 (out of 134, 84%) patients with rsEEGs. A total of 73 (65%) patients recovered consciousness before discharge. Patients who recovered consciousness were younger (40 vs. 50, p .01). Patients who recovered consciousness had higher Kolcom (U = 1688, p = 0.01,), increased beta power (U = 1652 p = 0.003), with higher variability across channels ( U = 1534, p = 0.034), and epochs (U = 1711, p = 0.004), lower delta power (U = 981, p = 0.04) and showed higher connectivity across time and channels as measured by wSMI in the theta band (U = 1636, p = .026, U = 1639, p = 0.024) than those who didn't recover. The ROC-AUC improved from 0.66 (using age, motor response, pupils' reactivity, and CT Marshall classification) to 0.69 (p < 0.001) when adding rsEEG measures. Conclusion We describe the rsEEG EEG signature in recovery of consciousness prior to discharge in comatose TBI patients. Resting-state EEG measures improved prediction beyond the clinical and imaging data.
Eye tracking assessments are clinician dependent and can contribute to misclassification of coma. We investigated responsiveness to videos with and without audio in traumatic brain injury (TBI) subjects using video eye-tracking (VET). We recruited 20 healthy volunteers and 10 unresponsive TBI subjects. Clinicians were surveyed whether the subject was tracking on their bedside assessment. The Coma Recovery Scale-Revised (CRS-R) was also performed. Eye movements in response to three different 30-second videos with and without sound were recorded using VET. The videos consisted of moving characters (a dancer, a person skateboarding, and Spiderman). Tracking on VET was defined as visual fixation on the character and gaze movement in the same direction of the character on two separate occasions. Subjects were classified as "covert tracking" (tracking using VET only), "overt tracking" (VET and clinical exam by clinicians), and "no tracking". A k-nearest-neighbors model was also used to identify tracking computationally. Thalamocortical connectivity and structural integrity were evaluated with EEG and MRI. The ability to obey commands was evaluated at 6- and 12-month follow-up. The average age was 29 (± 17) years old. Three subjects demonstrated "covert tracking" (CRS-R of 6, 8, 7), two "overt tracking" (CRS-R 22, 11), and five subjects "no tracking" (CRS-R 8, 6, 5, 6, 7). Among the 84 tested trials in all subjects, 11 trials (13%) met the criteria for "covert tracking". Using the k-nearest approach, 14 trials (17%) were classified as "covert tracking". Subjects with "tracking" had higher thalamocortical connectivity, and had fewer structures injured in the eye-tracking network than those without tracking. At follow-up, 2 out of 3 "covert" and all "overt" subjects recovered consciousness versus only 2 subjects in the "no tracking" group. Immersive stimuli may serve as important objective tools to differentiate subtle tracking using VET.
Brain Injuries, Traumatic , Coma , Humans , Adult , Consciousness , Consciousness Disorders/diagnostic imaging , Consciousness Disorders/etiology , Brain Injuries, Traumatic/diagnostic imaging , Cluster Analysis
Temporal trends and factors associated with the withdrawal of life-sustaining therapy (WLST) after acute stroke are not well determined. DESIGN: Observational study (2008-2021). SETTING: Florida Stroke Registry (152 hospitals). PATIENTS: Acute ischemic stroke (AIS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH) patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Importance plots were performed to generate the most predictive factors of WLST. Area under the curve (AUC) for the receiver operating curve were generated for the performance of logistic regression (LR) and random forest (RF) models. Regression analysis was applied to evaluate temporal trends. Among 309,393 AIS patients, 47,485 ICH patients, and 16,694 SAH patients; 9%, 28%, and 19% subsequently had WLST. Patients who had WLST were older (77 vs 70 yr), more women (57% vs 49%), White (76% vs 67%), with greater stroke severity on the National Institutes of Health Stroke Scale greater than or equal to 5 (29% vs 19%), more likely hospitalized in comprehensive stroke centers (52% vs 44%), had Medicare insurance (53% vs 44%), and more likely to have impaired level of consciousness (38% vs 12%). Most predictors associated with the decision to WLST in AIS were age, stroke severity, region, insurance status, center type, race, and level of consciousness (RF AUC of 0.93 and LR AUC of 0.85). Predictors in ICH included age, impaired level of consciousness, region, race, insurance status, center type, and prestroke ambulation status (RF AUC of 0.76 and LR AUC of 0.71). Factors in SAH included age, impaired level of consciousness, region, insurance status, race, and stroke center type (RF AUC of 0.82 and LR AUC of 0.72). Despite a decrease in the rates of early WLST (< 2 d) and mortality, the overall rates of WLST remained stable. CONCLUSIONS: In acute hospitalized stroke patients in Florida, factors other than brain injury alone contribute to the decision to WLST. Potential predictors not measured in this study include education, culture, faith and beliefs, and patient/family and physician preferences. The overall rates of WLST have not changed in the last 2 decades.
OBJECTIVES: This study investigated video eye tracking (VET) in comatose patients with traumatic brain injury (TBI). METHODS: We recruited healthy participants and unresponsive patients with TBI. We surveyed the patients' clinicians on whether the patient was tracking and performed the Coma Recovery Scale-Revised (CRS-R). We recorded eye movements in response to motion of a finger, a face, a mirror, and an optokinetic stimulus using VET glasses. Patients were classified as covert tracking (tracking on VET alone) and overt tracking (VET and clinical examination). The ability to obey commands was evaluated at 6-month follow-up. RESULTS: We recruited 20 healthy participants and 10 patients with TBI. The use of VET was feasible in all participants and patients. Two patients demonstrated covert tracking (CRS-R of 6 and 8), 2 demonstrated overt tracking (CRS-R of 22 and 11), and 6 patients had no tracking (CRS-R of 8, 6, 5, 7, 6, and 7). Five of 56 (9%) tracking assessments were missed on clinical examination. All patients with tracking recovered consciousness at follow-up, whereas only 2 of 6 patients without tracking recovered at follow-up. DISCUSSION: VET is a feasible method to measure covert tracking. Future studies are needed to confirm the prognostic value of covert tracking.
Brain Injuries, Traumatic , Coma , Humans , Coma/etiology , Brain Injuries, Traumatic/complications , Consciousness/physiology , Prognosis , Physical Examination
BACKGROUND: The objective of this study was to evaluate the accuracy of seizure burden in patients with super-refractory status epilepticus (SRSE) by using quantitative electroencephalography (qEEG). METHODS: EEG recordings from 69 patients with SRSE (2009-2019) were reviewed and annotated for seizures by three groups of reviewers: two board-certified neurophysiologists using only raw EEG (gold standard), two neurocritical care providers with substantial experience in qEEG analysis (qEEG experts), and two inexperienced qEEG readers (qEEG novices) using only a qEEG trend panel. RESULTS: Raw EEG experts identified 35 (51%) patients with seizures, accounting for 2950 seizures (3,126 min). qEEG experts had a sensitivity of 93%, a specificity of 61%, a false positive rate of 6.5 per day, and good agreement (κ = 0.64) between both qEEG experts. qEEG novices had a sensitivity of 98.5%, a specificity of 13%, a false positive rate of 15 per day, and fair agreement (κ = 0.4) between both qEEG novices. Seizure burden was not different between the qEEG experts and the gold standard (3,257 vs. 3,126 min), whereas qEEG novices reported higher burden (6066 vs. 3126 min). CONCLUSIONS: Both qEEG experts and novices had a high sensitivity but a low specificity for seizure detection in patients with SRSE. qEEG could be a useful tool for qEEG experts to estimate seizure burden in patients with SRSE.
Seizures , Status Epilepticus , Certification , Data Collection , Electroencephalography , Humans , Seizures/diagnosis , Status Epilepticus/diagnosis
OBJECTIVE: To test ketamine infusion efficacy in the treatment of super-refractory status epilepticus (SRSE), we studied patients with SRSE who were treated with ketamine retrospectively. We also studied the effect of high doses of ketamine on brain physiology as reflected by invasive multimodality monitoring (MMM). METHODS: We studied a consecutive series of 68 patients with SRSE who were admitted between 2009 and 2018, treated with ketamine, and monitored with scalp EEG. Eleven of these patients underwent MMM at the time of ketamine administration. We compared patients who had seizure cessation after ketamine initiation to those who did not. RESULTS: Mean age was 53 ± 18 years and 46% of patients were female. Seizure burden decreased by at least 50% within 24 hours of starting ketamine in 55 (81%) patients, with complete cessation in 43 (63%). Average dose of ketamine infusion was 2.2 ± 1.8 mg/kg/h, with median duration of 2 (1-4) days. Average dose of midazolam was 1.0 ± 0.8 mg/kg/h at the time of ketamine initiation and was started at a median of 0.4 (0.1-1.0) days before ketamine. Using a generalized linear mixed effect model, ketamine was associated with stable mean arterial pressure (odds ratio 1.39, 95% confidence interval 1.38-1.40) and with decreased vasopressor requirements over time. We found no effect on intracranial pressure, cerebral blood flow, or cerebral perfusion pressure. CONCLUSION: Ketamine treatment was associated with a decrease in seizure burden in patients with SRSE. Our data support the notion that high-dose ketamine infusions are associated with decreased vasopressor requirements without increased intracranial pressure. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that ketamine decreases seizures in patients with SRSE.
Anticonvulsants/therapeutic use , Drug Resistant Epilepsy/drug therapy , Ketamine/therapeutic use , Status Epilepticus/drug therapy , Brain/physiopathology , Electroencephalography , Female , Humans , Male , Middle Aged , Retrospective Studies , Treatment Outcome
OBJECTIVE: To better understand the heterogeneous population of patients with new-onset refractory status epilepticus (NORSE), we studied the most severe cases in patients who presented with new-onset super-refractory status epilepticus (NOSRSE). METHODS: We report a retrospective case series of 26 adults admitted to the Columbia University Irving Medical Center neurologic intensive care unit (NICU) from February 2009 to February 2016 with NOSRSE. We evaluated demographics, diagnostic studies, and treatment course. Outcomes were modified Rankin Scale score (mRS) at hospital discharge and most recent follow-up visit (minimum of 2 months post discharge), NICU and hospital length of stay, and long-term antiepileptic drug use. RESULTS: Of the 252 patients with refractory status epilepticus, 27/252 had NORSE and 26/27 of those had NOSRSE. Age was bimodally distributed with peaks at 27 and 63 years. The majority (96%) had an infectious or psychiatric prodrome. Etiology was cryptogenic in 73%, autoimmune in 19%, and infectious in 8%. Seven patients (27%) underwent brain biopsy, autopsy, or both; 3 (12%) were diagnostic (herpes simplex encephalitis, candida encephalitis, and acute demyelinating encephalomyelitis). On discharge, 6 patients (23%) had good or fair outcome (mRS 0-3). Of the patients with long-term follow-up data (median 9 months, interquartile range 2-22 months), 12 patients (71%) had mRS 0-3. CONCLUSION: Among our cohort, nearly all patients with NORSE had NOSRSE. The majority were cryptogenic with few antibody-positive cases identified. Neuropathology was diagnostic in 12% of cases. Although only 23% of patients had good or fair outcome on discharge, 71% met these criteria at follow-up.
Drug Resistant Epilepsy/epidemiology , Status Epilepticus/epidemiology , Adult , Aged , Female , Humans , Male , Middle Aged , Retrospective Studies , Severity of Illness Index
