Acute Disorders Of Consciousness Research Articles

Local Neuronal Activity and the Hippocampal Functional Network Can Predict the Recovery of Consciousness in Individuals With Acute Disorders of Consciousness Caused by Neurological Injury.

There is limited research on predicting the recovery of consciousness in patients with acute disorders of consciousness (aDOC). The purpose of this study is to investigate the altered characteristics of the local neuronal activity indicated by the amplitude of low-frequency fluctuations (ALFF) and functional connectivity (FC) of the hippocampus network in patients with aDOC caused by neurological injury and to explore whether these characteristics can predict the recovery of consciousness. Thirty-seven patients with aDOC were included, all of whom completed resting-state functional magnetic resonance imaging (rsfMRI) scans. The patients were divided into two groups based on prognosis of consciousness recovery, 24 patients were in prolonged disorders of consciousness (pDOC) and 13 in emergence from minimally conscious state (eMCS) at 3 months after neurological injury. Univariable and multivariate logistic regression analyses were used to investigate the clinical indicators affecting patients' recovery of consciousness. The ALFF values and FC of the hippocampal network were compared between patients with pDOC and those with eMCS. Additionally, we employed the support vector machine (SVM) method to construct a predictive model for prognosis of consciousness based on the ALFF and FC values of the aforementioned differential brain regions. The accuracy (ACC), area under the curve (AUC), sensitivity, and specificity were used to evaluate the efficacy of the model. The FOUR score at onset and the length of mechanical ventilation (MV) were found to be significant influential factors for patients who recovered to eMCS at 3 months after onset. Patients who improved to eMCS showed significantly increased ALFF values in the right calcarine gyrus, left lingual gyrus, right middle temporal gyrus, and right precuneus compared to patients in a state of pDOC. Furthermore, significant increases in FC values of the hippocampal network were observed in the eMCS group, primarily involving the right lingual gyrus and bilateral precuneus, compared to the pDOC group. The predictive model constructed using ALFF alone or ALFF combined with FC values from the aforementioned brain regions demonstrated high accuracies of 83.78% and 81.08%, respectively, with AUCs of 95% and 94%, sensitivities of 0.92 for both models, and specificities of 0.92 for both models in predicting the recovery of consciousness in patients with aDOC. The present findings demonstrate significant differences in the local ALFF and FC values of the hippocampus network between different prognostic groups of patients with aDOC. The constructed predictive model, which incorporates ALFF and FC values, has the potential to provide valuable insights for clinical decision-making and identifying potential targets for early intervention.

A Survey of Surrogates and Health Care Professionals Indicates Support of Cognitive Motor Dissociation-Assisted Prognostication.

Prognostication of patients with acute disorders of consciousness is imprecise but more accurate technology-supported predictions, such as cognitive motor dissociation (CMD), are emerging. CMD refers to the detection of willful brain activation following motor commands using functional magnetic resonance imaging or machine learning-supported analysis of the electroencephalogram in clinically unresponsive patients. CMD is associated with long-term recovery, but acceptance by surrogates and health care professionals is uncertain. The objective of this study was to determine receptiveness for CMD to inform goals of care (GoC) decisions and research participation among health care professionals and surrogates of behaviorally unresponsive patients. This was a two-center study of surrogates of and health care professionals caring for unconscious patients with severe neurological injury who were enrolled in two prospective US-based studies. Participants completed a 13-item survey to assess demographics, religiosity, minimal acceptable level of recovery, enthusiasm for research participation, and receptiveness for CMD to support GoC decisions. Completed surveys were obtained from 196 participants (133 health care professionals and 63 surrogates). Across all respondents, 93% indicated that they would want their loved one or the patient they cared for to participate in a research study that supports recovery of consciousness if CMD were detected, compared to 58% if CMD were not detected. Health care professionals were more likely than surrogates to change GoC with a positive (78% vs. 59%, p = 0.005) or negative (83% vs. 59%, p = 0.0002) CMD result. Participants who reported religion was the most important part of their life were least likely to change GoC with or without CMD. Participants who identified as Black (odds ratio [OR] 0.12, 95% confidence interval [CI] 0.04-0.36) or Hispanic/Latino (OR 0.39, 95% CI 0.2-0.75) and those for whom religion was the most important part of their life (OR 0.18, 95% CI 0.05-0.64) were more likely to accept a lower minimum level of recovery. Technology-supported prognostication and enthusiasm for clinical trial participation was supported across a diverse spectrum of health care professionals and surrogate decision-makers. Education for surrogates and health care professionals should accompany integration of technology-supported prognostication.

The Pupillary Light-Off Reflex in Acute Disorders of Consciousness.

In intensive care patients with disorders of consciousness, the pupillary light reflex is a measure of pupillary parasympathetic function. By contrast, the pupillary light-off reflex leads to pupil dilation in response to an abrupt change from light to darkness ("light-off") and reflects combined parasympathetic and sympathetic pupillary function. To our knowledge, this reflex has not been systematically investigated in patients with disorders of consciousness. We hypothesized that the pupillary light-off reflex correlates with consciousness levels after acute brain injury. From November 2022 to March 2023, we enrolled 100 study participants: 25 clinically unresponsive (coma or unresponsive wakefulness syndrome) and 25 clinically low-responsive (minimally conscious state or better) patients from the intensive care units of a tertiary referral center, and 50 age-matched and sex-matched healthy controls. Exclusion criteria were active or chronic eye disease. We used automated pupillometry to assess the pupillary light-off reflex and the pupillary light reflex of both eyes under scotopic conditions in all study participants. The pupillary light-off reflex was strongly correlated with consciousness levels (r = 0.62, p < 0.001), the increase in pupillary diameters being smallest in unresponsive patients (mean ± standard deviation 20% ± 21%), followed by low-responsive patients (mean ± standard deviation 47% ± 26%) and healthy controls (mean ± standard deviation 67% ± 17%; p < 0.001). Similar yet less pronounced patterns were observed for the pupillary light reflex. Twenty-one of 25 (84%) unresponsive patients had preserved pupillary light reflexes, but only seven (28%) had fully preserved pupillary light-off reflexes (p < 0.0001). Of these 7 patients, five (71%) regained awareness. The pupillary light-off reflex may be more sensitive to consciousness levels than the pupillary light reflex. The clinical implications of this finding seem worthy of further investigation, particularly regarding possible benefits for neuromonitoring and prognostication after brain injury.

Arterial Spin Labeling Magnetic Resonance Imaging for Acute Disorders of Consciousness in the Intensive Care Unit.

To investigate patients with disorders of consciousness (DoC) for residual awareness, guidelines recommend quantifying glucose brain metabolism using positron emission tomography. However, this is not feasible in the intensive care unit (ICU). Cerebral blood flow (CBF) assessed by arterial spin labeling magnetic resonance imaging (ASL-MRI) could serve as a proxy for brain metabolism and reflect consciousness levels in acute DoC. We hypothesized that ASL-MRI would show compromised CBF in coma and unresponsive wakefulness states (UWS) but relatively preserved CBF in minimally conscious states (MCS) or better. We consecutively enrolled ICU patients with acute DoC and categorized them as being clinically unresponsive (i.e., coma or UWS [≤ UWS]) or low responsive (i.e., MCS or better [≥ MCS]). ASL-MRI was then acquired on 1.5T or 3T. Healthy controls were investigated with both 1.5T and 3T ASL-MRI. We obtained 84 ASL-MRI scans from 59 participants, comprising 36 scans from 35 patients (11 women [31.4%]; median age 56years, range 18-82years; 24 ≤ UWS patients, 12 ≥ MCS patients; 32 nontraumatic brain injuries) and 48 scans from 24 healthy controls (12 women [50%]; median age 50years, range 21-77years). In linear mixed-effects models of whole-brain cortical CBF, patients had 16.2mL/100g/min lower CBF than healthy controls (p = 0.0041). However, ASL-MRI was unable to discriminate between ≤ UWS and ≥ MCS patients (whole-brain cortical CBF: p = 0.33; best hemisphere cortical CBF: p = 0.41). Numerical differences of regional CBF in the thalamus, amygdala, and brainstem in the two patient groups were statistically nonsignificant. CBF measurement in ICU patients using ASL-MRI is feasible but cannot distinguish between the lower and the upper ends of the acute DoC spectrum. We suggest that pilot testing of diagnostic interventions at the extremes of this spectrum is a time-efficient approach in the continued quest to develop DoC neuroimaging markers in the ICU.

Exploring the Significance of Cognitive Motor Dissociation on Patient Outcome in Acute Disorders of Consciousness.

Cognitive motor dissociation (CMD) is characterized by a dissociation between volitional brain responses and motor control, detectable only through techniques such as electroencephalography (EEG) and functional magnetic resonance imaging. Hence, it has recently emerged as a major challenge in the assessment of patients with disorders of consciousness. Specifically, this review focuses on the prognostic implications of CMD detection during the acute stage of brain injury. CMD patients were identified in each diagnostic category (coma, unresponsive wakefulness syndrome/vegetative state, minimally conscious state minus) with a relatively similar prevalence of around 20%. Current knowledge tends to indicate that the diagnosis of CMD in the acute phase often predicts a more favorable clinical outcome compared with other unresponsive non-CMD patients. Nevertheless, the review underscores the limited research in this domain, probably at least partially explained by its nascent nature and the lack of uniformity in the nomenclature for CMD-related disorders, hindering the impact of the literature in the field.

Covert Consciousness in Acute Brain Injury Revealed by Automated Pupillometry and Cognitive Paradigms

BackgroundIdentifying covert consciousness in intensive care unit (ICU) patients with coma and other disorders of consciousness (DoC) is crucial for treatment decisions, but sensitive low-cost bedside markers are missing. We investigated whether automated pupillometry combined with passive and active cognitive paradigms can detect residual consciousness in ICU patients with DoC.MethodsWe prospectively enrolled clinically low-response or unresponsive patients with traumatic or nontraumatic DoC from ICUs of a tertiary referral center. Age-matched and sex-matched healthy volunteers served as controls. Patients were categorized into clinically unresponsive (coma or unresponsive wakefulness syndrome) or clinically low-responsive (minimally conscious state or better). Using automated pupillometry, we recorded pupillary dilation to passive (visual and auditory stimuli) and active (mental arithmetic) cognitive paradigms, with task-specific success criteria (e.g., ≥ 3 of 5 pupillary dilations on five consecutive mental arithmetic tasks).ResultsWe obtained 699 pupillometry recordings at 178 time points from 91 ICU patients with brain injury (mean age 60 ± 13.8 years, 31% women, and 49.5% nontraumatic brain injuries). Recordings were also obtained from 26 matched controls (59 ± 14.8 years, 38% women). Passive paradigms yielded limited distinctions between patients and controls. However, active paradigms enabled discrimination between different states of consciousness. With mental arithmetic of moderate complexity, ≥ 3 pupillary dilations were seen in 17.8% of clinically unresponsive patients and 50.0% of clinically low-responsive patients (odds ratio 4.56, 95% confidence interval 2.09–10.10; p < 0.001). In comparison, 76.9% healthy controls responded with ≥ 3 pupillary dilations (p = 0.028). Results remained consistent across sensitivity analyses using different thresholds for success. Spearman’s rank analysis underscored the robust association between pupillary dilations during mental arithmetic and consciousness levels (rho = 1, p = 0.017). Notably, one behaviorally unresponsive patient demonstrated persistent command-following behavior 2 weeks before overt signs of awareness, suggesting prolonged cognitive motor dissociation.ConclusionsAutomated pupillometry combined with mental arithmetic can identify cognitive efforts, and hence covert consciousness, in ICU patients with acute DoC.

Multimodal Prediction of 3- and 12-Month Outcomes in ICU Patients with Acute Disorders of Consciousness

BackgroundIn 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.MethodsWe 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.ResultsBetween 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]).ConclusionsOur 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.

Resting State fMRI for Neuroprognostication in Traumatic Brain Injury: Clinical Experience of Evaluation for Covert Consciousness and Epileptogenic Networks in Acute Coma (P14-7.005)

<h3>Objective:</h3> To report the <b><i>clinical</i></b> experience of resting state fMRI (rs-fMRI) for neuroprognostication, consciousness recovery, and epileptogenic networks in acute coma. <h3>Background:</h3> Diagnosis and prognosis in acute disorders of consciousness (DoC) remains a challenge. Early withdrawal of care for traumatic brain injury (TBI) patients with recovery potential and continuation of care for patients with devastating prognosis due to misdiagnosis of DoC have both been reported. The rs-fMRI is an innovative tool that has shown promise in diagnosis and prognosis of DoC but has yet to see widespread clinical use. <h3>Design/Methods:</h3> Case Report. <h3>Results:</h3> We present a case of a previously healthy 38-year-old man who received clinical rs-fMRI in acute coma due to TBI. Initial exam: nonreactive pupils, intact corneal reflexes, absent cough and gag reflexes and no motor response. His Glasgow Coma Scale (GCS) was 3 and Coma Recovery Scale-Revised (CSR-R) score was 0. CT head showed acute left subdural hematoma, rightward midline shift, and uncal herniation. After undergoing emergent hemicraniectomy, MRI brain showed evolving Grade III diffuse axonal injury, severe ventriculomegaly, and protrusion of cortex through the hemicraniectomy. EEG demonstrated bilateral slowing but no seizures. Rs-fMRI (hospital day 36) demonstrated no epileptogenic networks, preserved default mode network, language and subcortical motor networks with moderate impairment. These findings supported return of consciousness, lower-level language comprehension, and motor impairment. Despite the patient’s poor initial examination, the rs-fMRI was useful in supporting the family’s decision to continue care. At three months, the patient’s CSR-R improved to 9, including regained localization to sound, visual fixation, flexion withdrawal, oral reflexive movements, no communication, and eye opening without stimulation, which is consistent with minimally conscious state minus. <h3>Conclusions:</h3> Clinical utilization of rs-fMRI has limitations but can aid in clinical decision-making when evaluating for epileptogenic networks, potential for consciousness recovery, and overall functional outcome in patients with DoC and severe TBI. <b>Disclosure:</b> Dr. Aseem has nothing to disclose. Dr. Strohm has nothing to disclose. Dr. Carlson has nothing to disclose. Dr. Karazanashvili has nothing to disclose. Dr. Gilbert has nothing to disclose. Ms. Gillette has nothing to disclose. Dr. Boerwinkle has nothing to disclose.

Ethical implications of detecting cognitive motor dissociation early after brain injury (P4-7.005)

<h3>Objective:</h3> To determine the impact of cognitive motor disassociation (CMD) in goals of care (GOC) decisions for surrogate decision makers and healthcare professionals (HCPs) of unconscious patients and assess support for clinical research participation. <h3>Background:</h3> Predictions of recovery from acute disorders of consciousness are imprecise but novel diagnostic tools are emerging. CMD refers to the detection of willful brain activation following motor commands in the absence of behavioral command following as detected by machine learning-supported EEG or MRI analysis. This phenomenon has been identified as a predictor of long-term recovery but acceptance of technology-supported prognostication by surrogates and HCPs remains uncertain. <h3>Design/Methods:</h3> We recruited surrogates and HCPs caring for unconscious patients with intracerebral hemorrhage. All participants completed a thirteen-item survey that captured data on demographics, education, religiosity, support for research participation, and receptiveness to technology-assisted prognostication in decision-making. <h3>Results:</h3> A total of 134 participants completed the survey, including 85 HCPs (40 physicians/PAs, 45 RNs) and 49 surrogates. There were no differences in sex between the two groups (67% of HCPs and 61% of surrogates were female). Surrogates reported stronger religious affiliation with 73% indicating religion was “very important” or “the most important part” of their life vs. 29% of HCPs. Both surrogates (73%) and HCPs (93%) indicated a diagnosis of CMD would help in decision-making. There was broad support for clinical trial participation in surrogates (86%) and HCPs (89%). HCPs were more likely than surrogates to change their goals if CMD could not be detected (OR 5.5, 95%-CI 2.4–12.7, p=0.00005). There was only a trend for a higher chance of HCPs to change their goals if CMD could be detected when compared to surrogates (OR 1.9, 95%-CI 0.9–3.8, p=0.08). <h3>Conclusions:</h3> These results demonstrate acceptance of technology-supported prognostication amongst HCPs and surrogate decision-makers. Targeted education to interpret detection and failure of detection of CMD is needed. <b>Disclosure:</b> Mr. Heinonen has nothing to disclose. Miss Carmona has nothing to disclose. Kevin Doyle has nothing to disclose. Ms. Grobois has nothing to disclose. Miss Kruger has nothing to disclose. Dr. Velazquez has nothing to disclose. Ms. Vrosgou has nothing to disclose. Dr. Shen has nothing to disclose. Mrs. Cespedes has nothing to disclose. Ms. Yazdi has nothing to disclose. Dr. Ghoshal has nothing to disclose. Dr. Roh has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Portola Pharmaceuticals. Dr. Agarwal has nothing to disclose. Dr. Park has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Neurocritical Care. The institution of Dr. Park has received research support from National Institutes of Health. The institution of Dr. Dugdale has received research support from McDonald Agape Foundation. Dr. Dugdale has received publishing royalties from a publication relating to health care. Dr. Dugdale has received publishing royalties from a publication relating to health care. Dr. Dugdale has received personal compensation in the range of $500-$4,999 for serving as a Speaking honoraria for various lectures with Multiple organizations. Dr. Claassen has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Marinus. Dr. Claassen has stock in iCE Neurosystems. The institution of Dr. Claassen has received research support from NINDS. The institution of Dr. Claassen has received research support from McDonnel Foundation. Dr. Claassen has received publishing royalties from a publication relating to health care. Dr. Claassen has received publishing royalties from a publication relating to health care.

State-of-the-Art Evaluation of Acute Adult Disorders of Consciousness for the General Intensivist.

To provide a concise review of knowledge and practice pertaining to the diagnosis and initial management of unanticipated adult patient disorders of consciousness (DoC) by the general intensivist. Detailed search strategy using PubMed and OVID Medline for English language articles describing adult patient acute DoC diagnostic evaluation and initial management strategies including indications for transfer. Descriptive and interventional studies that address acute adult DoC, their evaluation and initial management, indications for transfer, as well as outcome prognostication. Relevant descriptions or studies were reviewed, and the following aspects of each manuscript were identified, abstracted, and analyzed: setting, study population, aims, methods, results, and relevant implications for adult critical care practice. Acute adult DoC may be categorized by etiology including structural, functional, infectious, inflammatory, and pharmacologic, the understanding of which drives diagnostic investigation, monitoring, acute therapy, and subsequent specialist care decisions including team-based local care as well as intra- and inter-facility transfer. Acute adult DoC may be initially comprehensively addressed by the general intensivist using an etiology-driven and team-based approach. Certain clinical conditions, procedural expertise needs, or resource limitations inform transfer decision-making within a complex care facility or to one with greater complexity. Emerging collaborative science helps improve our current knowledge of acute DoC to better align therapies with underpinning etiologies.

Functional Neuroimaging as an Assessment Tool in Critically Ill Patients.

Little is known about residual cognitive function in the earliest stages of serious brain injury. Functional neuroimaging has yielded valuable diagnostic and prognostic information in chronic disorders of consciousness, such as the vegetative state (also termed unresponsive wakefulness syndrome). The objective of the current study was to determine if functional neuroimaging could be efficacious in the assessment of cognitive function in acute disorders of consciousness, such as coma, where decisions about the withdrawal of life-sustaining therapies are often made. A hierarchical functional magnetic resonance imaging (fMRI) approach assessed sound perception, speech perception, language comprehension, and covert command following in 17 critically ill patients admitted to the intensive care unit (ICU). Preserved auditory function was observed in 15 patients (88%), whereas 5 (29%) also had preserved higher-order language comprehension. Notably, one patient could willfully modulate his brain activity when instructed to do so, suggesting a level of covert conscious awareness that was entirely inconsistent with his clinical diagnosis at the time of the scan. Across patients, a positive relationship was also observed between fMRI responsivity and the level of functional recovery, such that patients with the greatest functional recovery had neural responses most similar to those observed in healthy control participants. These results suggest that fMRI may provide important diagnostic and prognostic information beyond standard clinical assessment in acutely unresponsive patients, which may aid discussions surrounding the continuation or removal of life-sustaining therapies during the early post-injury period. ANN NEUROL 2023;93:131-141.

Multimodal prediction of residual consciousness in the intensive care unit: the CONNECT-ME study.

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 center 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 were assessed. Next, we used EEG and fMRI data at study enrollment 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 enrollment 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% women), 51 (59%) were ≤ UWS and 36 (41%) were ≥ MCS at study enrollment. Thirty-one (36%) patients died in the ICU, including 28 who had life-sustaining therapy withdrawn. EEG and fMRI predicted consciousness levels at study enrollment 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 enrollment 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.

Conventional and Investigational Approaches Leveraging Clinical EEG for Prognosis in Acute Disorders of Consciousness.

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.

Ultrasonic Deep Brain Neuromodulation in Acute Disorders of Consciousness: A Proof-of-Concept.

The promotion of recovery in patients who have entered a disorder of consciousness (DOC; e.g., coma or vegetative states) following severe brain injury remains an enduring medical challenge despite an ever-growing scientific understanding of these conditions. Indeed, recent work has consistently implicated altered cortical modulation by deep brain structures (e.g., the thalamus and the basal ganglia) following brain damage in the arising of, and recovery from, DOCs. The (re)emergence of low-intensity focused ultrasound (LIFU) neuromodulation may provide a means to selectively modulate the activity of deep brain structures noninvasively for the study and treatment of DOCs. This technique is unique in its combination of relatively high spatial precision and noninvasive implementation. Given the consistent implication of the thalamus in DOCs and prior results inducing behavioral recovery through invasive thalamic stimulation, here we applied ultrasound to the central thalamus in 11 acute DOC patients, measured behavioral responsiveness before and after sonication, and applied functional MRI during sonication. With respect to behavioral responsiveness, we observed significant recovery in the week following thalamic LIFU compared with baseline. With respect to functional imaging, we found decreased BOLD signals in the frontal cortex and basal ganglia during LIFU compared with baseline. In addition, we also found a relationship between altered connectivity of the sonicated thalamus and the degree of recovery observed post-LIFU.

Impact of MRI on decision-making in ICU patients with disorders of consciousness

BackgroundRecovery of consciousness is the most important survival factor in patients with acute brain injury and disorders of consciousness (DoC). Since most deaths in the intensive care unit (ICU) occur after withdrawal of life-support, medical decision-making is crucial for acute DoC patients. Neuroimaging informs decision-making, yet the precise effects of MRI on decision-making in the ICU are poorly understood. We investigated the impact of brain MRI on prognostication, therapeutic decisions and physician confidence in ICU patients with DoC. MethodsIn this simulated decision-making study utilizing a prospective ICU cohort, a panel of neurocritical experts first reviewed clinical information (without MRI) from 75 acute DoC patients and made decisions about diagnosis, prognosis and treatment. Following review of the MRI, the panel then decided if the initial decisions needed revision. In parallel, a blinded neuroradiologist reassessed all neuroimaging. ResultsMRI led to changes in clinical management of 57 (76%) of patients (Number-Needed-to-Test for any change: 1.32), including revised diagnoses (20%), levels of care (21%), diagnostic confidence (43%) and prognostications (33%). Decisions were revised more often with stroke than with other brain injuries (p = 0.02). However, although MRI revealed additional pathology in 81%, this did not predict revised clinical decision-making (p-values ≥0.08). ConclusionMRI results changed decision-making in 3 of 4 ICU patients, but radiological findings were not predictive of clinical decision-making. This highlights the need to better understand the effects of neuroimaging on management decisions. How MRI influences decision-making in the ICU is an important avenue for research to improve acute DoC management.

Structural and functional connectivity of the ascending arousal network for prediction of outcome in patients with acute disorders of consciousness

To determine the role of early acquisition of blood oxygen level-dependent (BOLD) signals and diffusion tensor imaging (DTI) for analysis of the connectivity of the ascending arousal network (AAN) in predicting neurological outcomes after acute traumatic brain injury (TBI), cardiopulmonary arrest (CPA), or stroke. A prospective analysis of 50 comatose patients was performed during their ICU stay. Image processing was conducted to assess structural and functional connectivity of the AAN. Outcomes were evaluated after 3 and 6 months. Nineteen patients (38%) had stroke, 18 (36%) CPA, and 13 (26%) TBI. Twenty-three patients were comatose (44%), 11 were in a minimally conscious state (20%), and 16 had unresponsive wakefulness syndrome (32%). Univariate analysis demonstrated that measurements of diffusivity, functional connectivity, and numbers of fibers in the gray matter, white matter, whole brain, midbrain reticular formation, and pontis oralis nucleus may serve as predictive biomarkers of outcome depending on the diagnosis. Multivariate analysis demonstrated a correlation of the predicted value and the real outcome for each separate diagnosis and for all the etiologies together. Findings suggest that the above imaging biomarkers may have a predictive role for the outcome of comatose patients after acute TBI, CPA, or stroke.

Stability of extemporaneously prepared preservative-free methylphenidate 5 mg/mL intravenous solution.

To advance the implementation of consciousness-promoting therapies in patients with acute disorders of consciousness, the availability of potential therapeutic agents in formulations suitable for administration in hospitalized patients in the presence of complex comorbid conditions is paramount. The purpose of this study is to evaluate the long-term stability of extemporaneously prepared preservative-free methylphenidate hydrochloride (HCl) 5 mg/mL intravenous solution for experimental use. A methylphenidate 5 mg/mL solution was prepared under proper aseptic techniques with Methylphenidate Hydrochloride, USP, powder mixed in sterile water for solution. Methylphenidate HCl 5 mg/mL solution was sterilized by filtration technique under USP <797>-compliant conditions. Samples were stored refrigerated (2-8°C) and analyzed at approximately days 1, 30, 60, 90, 180, and 365. At each time point, chemical and physical stability were evaluated by visual inspection, pH measurement, membrane filtration procedure, turbidometric or photometric technique, and high-performance liquid chromatography analysis. Over the 1-year study period, the samples retained 96.76% to 102.04% of the initial methylphenidate concentration. There was no significant change in the visual appearance, pH level, or particulate matter during the study period. The sterility of samples was maintained and endotoxin levels were undetectable throughout the 1-year stability period. Extemporaneously prepared preservative-free methylphenidate 5 mg/mL intravenous solution was physically and chemically stable at 32, 61, 95, 186, and 365 days when stored in amber glass vials at refrigerated temperatures (2-8°C).

Children, Influenza, Encephalopathy, Clinical Characteristics, Laboratory Index

Background: To explore the early clinical features and laboratory findings of influenza-associated acute necrotizing encephalopathy (IANE). Methods: The demographics data, clinical manifestations, and laboratory indicators of cases diagnosed with IANE and influenza with febrile convulsions (FS), respectively, admitted to Guangzhou Women and Children’s Medical Center from January 2016 to January 2020 were retrospectively analyzed. Results: Among the 25 cases of IANE, there were 9 males and 16 females, aged 3 to 6 years. The mortality rate was 40.00% (10/25). Influenza virus type A in 9 cases (36.00%) and influenza virus type B in 10 cases (40.00%). The main clinical manifestations of children with IANE were acute disorders of consciousness (64.00%, 16/25) and convulsions (72.00%, 18/25), which were statistically significant when compared with the FS group (P Conclusions: Children with influenza present early with acute impairment of consciousness or convulsive seizures, or with elevated AST, ALT, CK-MB, LDH, and CSF protein and CSF LDH, especially if blood LDH is ≥348.5 U/L, should be closely evaluated and alerted to the possibility of IANE.

Autonomic responses to emotional linguistic stimuli and amplitude of low-frequency fluctuations predict outcome after severe brain injury

An accurate prognosis on the outcome of brain-injured patients with disorders of consciousness (DOC) remains a significant challenge, especially in the acute stage. In this study, we applied a multiple-technique approach to provide accurate predictions on functional outcome after 6 months in 15 acute DOC patients. Electrophysiological correlates of implicit cognitive processing of verbal stimuli and data-driven voxel-wise resting-state fMRI signals, such as the fractional amplitude of low-frequency fluctuations (fALFF), were employed. Event-related electrodermal activity, an index of autonomic activation, was recorded in response to emotional words and pseudo-words at baseline (T0). On the same day, patients also underwent a resting-state fMRI scan. Six months later (T1), patients were classified as outcome-negative and outcome-positive using a standard functional outcome scale. We then revisited the baseline measures to test their predictive power for the functional outcome measured at T1. We found that only outcome-positive patients had an earlier, higher autonomic response for words compared to pseudo-words, a pattern similar to that of healthy awake controls. Furthermore, DOC patients showed reduced fALFF in the posterior cingulate cortex (PCC), a brain region that contributes to autonomic regulation and awareness. The event-related electrodermal marker of residual cognitive functioning was found to have a significant correlation with residual local neuronal activity in the PCC. We propose that a residual autonomic response to cognitively salient stimuli, together with a preserved resting-state activity in the PCC, can provide a useful prognostic index in acute DOC.

P14-S Latency of Mismatch Negativity as a predictor of outcome in critically patients with subarachnoid haemorrhage

Background Multimodal neurophysiological markers support clinical assessments in individuals with disorders of consciousness (DoC). Few studies focused on subarachnoid haemorrhage (SAH) related coma. Furthermore, these patients often need sedation during the acute phase, making behavioral and neurophysiological monitoring challenging. We investigated which neurophysiological marker could better predict outcome in acute DoC related to SAH. Methods We studied 14 SAH patients admitted in the Sainte Anne hospital neurological ICU, between Oct 2017 and June 2018. All patients underwent within the first 72 h: clinical evaluation, EEG and multimodal evoked potentials (somatosensory potentials, brainstem auditory evoked potentials (BAEPs), late latency event-related potentials, N100 and mismatch negativity (MMN)). Quantitative EEG analysis using spectral and connectivity analysis was performed. According to the Glascow Outcome scale (GOS), we defined two clinical outcome groups: favorable (F) and unfavorable (UF). Results Clinical examination, EEG visual and quantitative analysis, presence of N20, BAEP, N100 and MMN were not significantly different in the two groups. However, mean latencies of N100 (F = 80 ms; UF = 106 ms;) and of MMN (F = 139 ms; UF = 197msec) were significantly different in the two groups (Mann Whitney test, respectively p = 0.017 and p = 0.035). Conclusions This study suggests that during the acute phase, in sedated patients with DoC related to SAH, latencies of N100 and latencies of MMN could be more discriminatory than the “classical” interpretation of these markers (present/absent) and the EEG analysis, in term of prognosis. These results need to be confirmed in a larger study.