Resting-State EEG Signature of Early Consciousness Recovery in Comatose Patients with Traumatic Brain Injury.

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.

Resting-State EEG Signature of Early Consciousness Recovery in Comatose Traumatic Brain Injury Patients.

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.

Covert Tracking to Immersive Stimuli in Traumatic Brain Injury Subjects With Disorders of Consciousness.

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.

Predictors and Temporal Trends of Withdrawal of Life-Sustaining Therapy After Acute Stroke in the Florida Stroke Registry.

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.

Covert Tracking to Visual Stimuli in Comatose Patients With Traumatic Brain Injury.

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.