Duration of Device-Based Fever Prevention after Cardiac Arrest.

BACKGROUND: Guidelines recommend active fever prevention for 72 hours after cardiac arrest. Data from randomized clinical trials of this intervention have been lacking. METHODS: We randomly assigned comatose patients who had been resuscitated after an out-of-hospital cardiac arrest of presumed cardiac cause to device-based temperature control targeting 36°C for 24 hours followed by targeting of 37°C for either 12 or 48 hours (for total intervention times of 36 and 72 hours, respectively) or until the patient regained consciousness. The primary outcome was a composite of death from any cause or hospital discharge with a Cerebral Performance Category of 3 or 4 (range, 1 to 5, with higher scores indicating more severe disability; a category of 3 or 4 indicates severe cerebral disability or coma) within 90 days after randomization. Secondary outcomes included death from any cause and the Montreal Cognitive Assessment score (range, 0 to 30, with higher scores indicating better cognitive ability) at 3 months. RESULTS: A total of 393 patients were randomly assigned to temperature control for 36 hours, and 396 patients were assigned to temperature control for 72 hours. At 90 days after randomization, a primary end-point event had occurred in 127 of 393 patients (32.3%) in the 36-hour group and in 133 of 396 patients (33.6%) in the 72-hour group (hazard ratio, 0.99; 95% confidence interval, 0.77 to 1.26; P = 0.70) and mortality was 29.5% in the 36-hour group and 30.3% in the 72-hour group. At 3 months, the median Montreal Cognitive Assessment score was 26 (interquartile range, 24 to 29) and 27 (interquartile range, 24 to 28), respectively. There was no significant between-group difference in the incidence of adverse events. CONCLUSIONS: Active device-based fever prevention for 36 or 72 hours after cardiac arrest did not result in significantly different percentages of patients dying or having severe disability or coma. (Funded by the Novo Nordisk Foundation; BOX ClinicalTrials.gov number, NCT03141099.).

Prevalence and characteristics of rapid eye movement sleep behaviour disorder in adults with migraine: a cross-sectional screening study.

BACKGROUND AND PURPOSE: Migraine and sleep disorders share a bidirectional relationship, but little is known about the specific association between migraine and rapid eye movement (REM) sleep behaviour disorder (RBD). The aim was to assess the prevalence of RBD and associated clinical characteristics in adults with migraine. METHODS: This analysis is part of a cross-sectional survey study conducted at the Headache Centre of the Charité-Universitätsmedizin Berlin between August 2020 and March 2023. At the end of their regular medical consultation, patients with migraine filled out (1) the validated RBD Screening Questionnaire (RBDSQ), (2) a questionnaire on REM sleep intrusions and (3) the Depression, Anxiety and Stress Scale 21. The primary endpoint was the percentage of patients with a positive RBD screening. A multivariate analysis was performed to identify characteristics independently associated with features of RBD. RESULTS: A total of 751 patients (44.1 ± 13.2 years; 87.4% female) with complete RBDSQ were included in this analysis, of which 443 (58.9%) screened positive for RBD. In multivariate analysis, a positive screening for RBD was associated with younger age (odds ratio [OR] 0.9, 95% confidence interval [CI] 0.8-0.9 per 10-year increase; p = 0.005) and with features suggestive of REM sleep intrusions (OR 4.3, 95% CI 1.8-10.4; p = 0.001). Migraine aura remained in the model without reaching statistical significance (OR 1.3, 95% CI 0.9-1.8; p = 0.079). DISCUSSION: Symptoms of RBD are frequent in adults with migraine. Further studies including polysomnography are required to confirm this association, and to explore potential common pathophysiological mechanisms.

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 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.

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

BACKGROUND: Identifying 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. METHODS: We 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). RESULTS: We 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. CONCLUSIONS: Automated pupillometry combined with mental arithmetic can identify cognitive efforts, and hence covert consciousness, in ICU patients with acute DoC.

Cognitive Motor Dissociation: Gap Analysis and Future Directions.

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.

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

BACKGROUND: 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. METHODS: 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 1.5 T or 3 T. Healthy controls were investigated with both 1.5 T and 3 T ASL-MRI. RESULTS: We obtained 84 ASL-MRI scans from 59 participants, comprising 36 scans from 35 patients (11 women [31.4%]; median age 56 years, range 18-82 years; 24 ≤ UWS patients, 12 ≥ MCS patients; 32 nontraumatic brain injuries) and 48 scans from 24 healthy controls (12 women [50%]; median age 50 years, range 21-77 years). In linear mixed-effects models of whole-brain cortical CBF, patients had 16.2 mL/100 g/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. CONCLUSIONS: 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.

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

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.

Near-death experiences are associated with rapid eye movement (REM) sleep intrusions in migraine patients, independent of migraine aura.

BACKGROUND AND PURPOSE: Migraine aura, near-death experiences (NDEs), and rapid eye movement (REM) sleep intrusions might share common mechanisms. Here, we investigated the prevalence of NDEs and REM sleep intrusions in people with migraine. We hypothesized that NDEs and REM sleep intrusions are more prevalent in migraine patients with aura than in those without. METHODS: We conducted a prospective cross-sectional cohort study at a tertiary headache center, based on a prespecified sample size (n = 808). Migraine patients completed a series of questionnaires, including questions about demographic and headache characteristics, the 16-item Greyson NDE scale, four questions about REM sleep intrusions, and the Depression, Anxiety, and Stress Scale 21 (DASS-21). RESULTS: Of 808 migraine patients (mean age 44.4 ± 13.3 years, 87.0% women), 353 (43.7%) had a current or previous history of migraine aura. Prevalence of NDE was 2.7% and not different in patients with and without aura (2.8% vs. 2.6%; p > 0.999). REM sleep intrusions were reported by 5.4% of participants and in a similar proportion of patients with and without aura (6.3% vs. 4.9%; p = 0.43). However, participants with REM sleep intrusions had had an NDE more often than participants without REM sleep intrusions (n = 5/44, 11.4% vs. n = 17/754, 2.2%; p = 0.005). Higher DASS-21 scores were associated with REM sleep intrusions (p < 0.001). CONCLUSIONS: In this tertiary center cohort study, the prevalence of NDE and REM sleep intrusions was not influenced by migraine aura status. However, we identified an association between NDE and REM sleep intrusions, which corroborates the notion that they might share pathophysiological mechanisms.

Understanding, detecting, and stimulating consciousness recovery in the ICU.

Coma is a medical and socioeconomic emergency. Although underfunded, research on coma and disorders of consciousness has made impressive progress. Lesion-network-mapping studies have delineated the precise brainstem regions that consistently produce coma when damaged. Functional neuroimaging has revealed how mechanisms like "communication through coherence" and "inhibition by gating" work in synergy to enable cortico-cortical processing and how this information transfer is disrupted in brain injury. On the cellular level, break-down of intracellular communication between the layer 5 pyramidal cell soma and the apical dendritic part impairs dendritic information integration, with up-stream effects on microcircuits in local neuronal populations and on large-scale fronto-parietal networks, which correlates with loss of consciousness. A breakthrough in clinical concepts occurred when fMRI, and later EEG, studies revealed that 15% of clinically unresponsive patients in acute and chronic settings are in fact awake and aware, as shown by their command following abilities revealed by brain activation during motor and locomotion imagery tasks. This condition is now termed "cognitive motor dissociation." Furthermore, epidemiological data on coma were literally non-existent until recently because of difficulties related to case ascertainment with traditional methods, but crowdsourcing of family observations enabled the first estimates of how frequent coma is in the general population (pooled annual incidence of 201 coma cases per 100,000 population in the UK and the USA). Diagnostic guidelines on coma and disorders of consciousness by the American Academy of Neurology and the European Academy of Neurology provide ambitious clinical frameworks to accommodate these achievements. As for therapy, a broad range of medical and non-medical treatment options is now being tested in increasingly larger trials; in particular, amantadine and transcranial direct current stimulation appear promising in this regard. Major international initiatives like the Curing Coma Campaign aim to raise awareness for coma and disorders of consciousness in the public, with the ultimate goal to make more brain-injured patients recover consciousness after a coma. To highlight all these accomplishments, this paper provides a comprehensive overview of recent progress and future challenges related to understanding, detecting, and stimulating consciousness recovery in the ICU.

Brimonidine eye drops reveal diminished sympathetic pupillary tone in comatose patients with brain injury.

BACKGROUND: There is an urgent need for easy-to-perform bedside measures to detect residual consciousness in clinically unresponsive patients with acute brain injury. Interestingly, the sympathetic control of pupil size is thought to be lost in states of unconsciousness. We therefore hypothesized that administration of brimonidine (an alpha-2-adrenergic agonist) eye drops into one eye should produce a pharmacologic Horner's syndrome if the clinically unresponsive patient is conscious, but not if the patient is unconscious. Here, in a first step to explore this hypothesis, we investigated the potential of brimonidine eye drops to distinguish preserved sympathetic pupillary function in awake volunteers from impairment of sympathetic tone in patients in a coma. METHODS: We enrolled comatose patients admitted for acute brain injury to one of the intensive care units (ICU) of a tertiary referral center, in whom EEG and/or neuroimaging for all practical purposes had ruled out residual consciousness. Exclusion criteria were deep sedation, medications with known drug interactions with brimonidine, and a history of eye disease. Age- and sex-matched healthy and awake volunteers served as controls. We measured pupils of both eyes, under scotopic conditions, at baseline and five times 5-120 min after administering brimonidine into the right eye, using automated pupillometry. Primary outcomes were miosis and anisocoria at the individual and group levels. RESULTS: We included 15 comatose ICU patients (seven women, mean age 59 ± 13.8 years) and 15 controls (seven women, mean age 55 ± 16.3 years). At 30 min, miosis and anisocoria were seen in all 15 controls (mean difference between the brimonidine-treated pupil and the control pupil: - 1.31 mm, 95% CI [- 1.51; - 1.11], p < 0.001), but in none (p < 0.001) of the 15 ICU patients (mean difference: 0.09 mm, 95% CI [- 0.12;0.30], p > 0.99). This effect was unchanged after 120 min and remained robust in sensitivity analyses correcting for baseline pupil size, age, and room illuminance. CONCLUSION: In this proof-of-principle study, brimonidine eye drops produced anisocoria in awake volunteers but not in comatose patients with brain injury. This suggests that automated pupillometry after administration of brimonidine can distinguish between the extremes of the spectrum of consciousness (i.e., fully conscious vs. deeply comatose). A larger study testing the "intermediate zone" of disorders of consciousness in the ICU seems warranted.

Blood-borne extracellular vesicles of bacteria and intestinal cells in patients with psychotic disorders.

BACKGROUND: Human cells and bacteria secrete extracellular vesicles (EV) which play a role in intercellular communication. EV from the host intestinal epithelium are involved in the regulation of bacterial gene expression and growth. Bacterial EV (bactEV) produced in the intestine can pass to various tissues where they deliver biomolecules to many kinds of cells, including neurons. Emerging data indicate that gut microbiota is altered in patients with psychotic disorders. We hypothesized that the amount and content of blood-borne EV from intestinal cells and bactEV in psychotic patients would differ from healthy controls. METHODS: We analyzed for human intestinal proteins by proteomics, for bactEV by metaproteomic analysis, and by measuring the level of lipopolysaccharide (LPS) in blood-borne EV from patients with psychotic disorders (n = 25), tested twice, in the acute phase of psychosis and after improvement, with age- and sex-matched healthy controls (n = 25). RESULTS: Patients with psychotic disorders had lower LPS levels in their EV compared to healthy controls (p = .027). Metaproteome analyses confirmed LPS finding and identified Firmicutes and Bacteroidetes as dominating phyla. Total amounts of human intestine proteins in EV isolated from blood was lower in patients compared to controls (p = .02). CONCLUSIONS: Our results suggest that bactEV and host intestinal EV are decreased in patients with psychosis and that this topic is worthy of further investigation given potential pathophysiological implications. Possible mechanisms involve dysregulation of the gut microbiota by host EV, altered translocation of bactEV to systemic circulation where bactEV can interact with both the brain and the immune system.

Non-invasive quantification of cerebral glucose metabolism using Gjedde-Patlak plot and image-derived input function from the aorta.

INTRODUCTION: We aimed at evaluating a Gjedde-Patlak plot and non-invasive image-derived input functions (IDIF) from the aorta to quantify cerebral glucose metabolic rate (CMRglc) in comparison to the reference standard based on sampling the arterial input function (AIF). METHOD: Six healthy subjects received 200 MBq [18F]FDG simultaneously with the initiation of a three-part dynamic PET recording consisting of a 15 min-recording of the aorta, a 40 min-recording of the brain and finally 2 min-recording of the aorta. Simultaneously, the arterial 18F concentration was measured via arterial cannulation. Regions of interest were drawn in the aorta and the brain and time-activity curves extracted. The IDIF was obtained by fitting a triple exponential function to the aorta time-activity curve after the initial peak including the late aorta frame, thereby interpolating the arterial blood activity concentration during the brain scan. CMRglc was calculated from Gjedde-Patlak plots using AIF and IDIF, respectively and the predictive value was examined. Results from frontal cortex, insula, hippocampus and cerebellum were compared by paired t-test and agreement between the methods was analyzed by Bland-Altman plot statistics. RESULTS: There was a strong linear relationship and an excellent agreement between the methods (mean±SD of CMRglcIDIF (µmol 100 g-1 min-1), mean difference, mean relative difference, 95% limits of agreement): frontal cortex: 30.8 ± 3.3, 0.5, 2.2%, [-1,6:2.5], insula: 25.4 ± 2.2, 0.4, 2.4%, [-1.4:2.2], hippocampus: 16.9 ± 1.2, 0.4, 3.8%, [-1.1:2.0] and cerebellum: 23.4 ± 1.9, 0.5, 3.1%, [-1.4:2.5]). CONCLUSION: We found excellent agreement between CMRglc obtained with an IDIF from the aorta and the reference standard with AIF. A non-invasive three-part dynamic [18F]FDG PET recording is feasible as a non-invasive alternative for reliable quantification of cerebral glucose metabolism in all scanner systems. This is useful in patients with presumed global cerebral changes owing to systemic disease or for the monitoring of treatment effects.

Classifying Disorders of Consciousness: Past, Present, and Future.

With the advent of advanced analytical methods applied to functional neuroimaging and neurophysiological data, cerebral conditions have been defined that challenge the established classification of disorders of consciousness. A subset of brain-damaged patients has been identified who cannot carry out motor commands, but who exhibit patterns of cerebral activation during mental imagery tasks that are indistinguishable from those in healthy controls. This condition, termed "cognitive motor dissociation," has overturned many assumptions regarding the detection, diagnosis, prognosis, and care of patients with brain injury. Three factors are likely to influence efforts to improve the classification of disorders of consciousness in the near future: the types of data that will become available to characterize brain states, the modeling paradigms utilized for data analysis, and the ability to implement classification schemes in the clinical setting. Here we review past achievements, present states, and future projections for the classification of impaired consciousness and responsiveness.

The Curing Coma Campaign International Survey on Coma Epidemiology, Evaluation, and Therapy (COME TOGETHER).

BACKGROUND: Although coma is commonly encountered in critical care, worldwide variability exists in diagnosis and management practices. We aimed to assess variability in coma definitions, etiologies, treatment strategies, and attitudes toward prognosis. METHODS: As part of the Neurocritical Care Society Curing Coma Campaign, between September 2020 and January 2021, we conducted an anonymous, international, cross-sectional global survey of health care professionals caring for patients with coma and disorders of consciousness in the acute, subacute, or chronic setting. Survey responses were solicited by sequential emails distributed by international neuroscience societies and social media. Fleiss κ values were calculated to assess agreement among respondents. RESULTS: The survey was completed by 258 health care professionals from 41 countries. Respondents predominantly were physicians (n = 213, 83%), were from the United States (n = 141, 55%), and represented academic centers (n = 231, 90%). Among eight predefined items, respondents identified the following cardinal features, in various combinations, that must be present to define coma: absence of wakefulness (81%, κ = 0.764); Glasgow Coma Score (GCS) ≤ 8 (64%, κ = 0.588); failure to respond purposefully to visual, verbal, or tactile stimuli (60%, κ = 0.552); and inability to follow commands (58%, κ = 0.529). Reported etiologies of coma encountered included medically induced coma (24%), traumatic brain injury (24%), intracerebral hemorrhage (21%), and cardiac arrest/hypoxic-ischemic encephalopathy (11%). The most common clinical assessment tools used for coma included the GCS (94%) and neurological examination (78%). Sixty-six percent of respondents routinely performed sedation interruption, in the absence of contraindications, for clinical coma assessments in the intensive care unit. Advanced neurological assessment techniques in comatose patients included quantitative electroencephalography (EEG)/connectivity analysis (16%), functional magnetic resonance imaging (7%), single-photon emission computerized tomography (6%), positron emission tomography (4%), invasive EEG (4%), and cerebral microdialysis (4%). The most commonly used neurostimulants included amantadine (51%), modafinil (37%), and methylphenidate (28%). The leading determinants for prognostication included etiology of coma, neurological examination findings, and neuroimaging. Fewer than 20% of respondents reported routine follow-up of coma survivors after hospital discharge; however, 86% indicated interest in future research initiatives that include postdischarge outcomes at six (85%) and 12 months (65%). CONCLUSIONS: There is wide heterogeneity among health care professionals regarding the clinical definition of coma and limited routine use of advanced coma assessment techniques in acute care settings. Coma management practices vary across sites, and mechanisms for coordinated and sustained follow-up after acute treatment are inconsistent. There is an urgent need for the development of evidence-based guidelines and a collaborative, coordinated approach to advance both the science and the practice of coma management globally.

Cerebrospinal fluid test results and associations with subsequent mental disorders, neurological diseases, and CNS infections: A population-based cohort study.

BACKGROUND: Cerebrospinal fluid (CSF) immune alterations have been associated with mental disorders, neurological disease, and CNS infections; however, comprehensive large-scale longitudinal CSF studies are lacking. METHODS: By using the Clinical Laboratory Information System (LABKA) Research Database in the Central Denmark Region (1994-2012), we included 15,030 individuals tested for CSF WBC, CSF/serum albumin ratio, IgG index, total protein, albumin, or IgG with follow-up for the risk of mental disorders, psychotropic prescriptions, neurological diseases, or CNS infections, estimated by Cox regression. RESULTS: Among individuals receiving a mental disorder diagnosis (N = 1,147) after a CSF test, 30·0% had an abnormal CSF test result, while for those with a neurological disease (N = 3,201), 39·9% had abnormal test results, and among individuals with CNS infections (N = 1,276), 73·0% had abnormal test results. Individuals with abnormal CSF test results had an increased risk of mental disorders (HR = 3·20; 95%CI = 2·86-3·59), neurological diseases (HR = 12·40; 95%CI = 11·65-13·20), and CNS infections (HR = 338·59; 95%CI = 299·06-383·35) compared to individuals not registered with a CSF test. However, the risk of mental disorders was higher (P < 0·001) after CSF test results within the normal range (HR = 4·45; 95%CI = 4·08-4·86), whereas for neurological diseases (HR = 9·72; 95%CI = 9·19-10·29) and CNS infections (HR = 55·17; 95%CI = 47·12-64·60), the risk was highest after abnormal CSF test results (all P < 0·001). The risk of organic mental disorders tended to be highest in individuals with abnormal CSF test results (HR = 19·30; 95%CI = 13·44-27·71) even though not significantly different from the risk in the group of individuals with CSF test results in the normal range (HR = 13·55; 95%CI = 9·36-19·60) (P ≥ 0·05). Abnormal CSF test results were associated with an elevated risk of psychotropic prescriptions (HR = 3·91; 95%CI = 3·66-4·18), as were CSF test results within the normal range (HR = 4·26; 95%CI = 4·03-4·51) (P < 0·05). CONCLUSIONS: Immunological CSF abnormalities are associated with an increased risk of mental disorders, neurological disease, and particularly CNS infections; however, the included CSF parameters were not specific for mental disorders and the relevant CSF biomarkers in psychiatry are yet to be discovered.

Does continuous electroencephalography influence therapeutic decisions in neurocritical care?

OBJECTIVES: In the neurocritical care unit (neuro-ICU), the impact of continuous EEG (cEEG) on therapeutic decisions and prognostication, including outcome prediction using the Status Epilepticus Severity Score (STESS), is poorly investigated. We studied to what extent cEEG contributes to treatment decisions, and how this relates to clinical outcome and the use of STESS in neurocritical care. METHODS: We included patients admitted to the neuro-ICU or neurological step-down unit of a tertiary referral hospital between 05/2013 and 06/2015. Inclusion criteria were ≥20 h of cEEG monitoring and age ≥15 years. Exclusion criteria were primary epileptic and post-cardiac arrest encephalopathies. RESULTS: Ninety-eight patients met inclusion criteria, 80 of which had status epilepticus, including 14 with super-refractory status. Median length of cEEG monitoring was 50 h (range 21-374 h). Mean STESS was lower in patients with favorable outcome 1 year after discharge (modified Rankin Scale [mRS] 0-2) compared to patients with unfavorable outcome (mRS 3-6), albeit not statistically significant (mean STESS 2.3 ± 2.1 vs 3.6 ± 1.7, p = 0.09). STESS had a sensitivity of 80%, a specificity of 42%, and a negative predictive value of 93% for outcome. cEEG results changed treatment decisions in 76 patients, including escalation of antiepileptic treatment in 65 and reduction in 11 patients. CONCLUSION: Status Epilepticus Severity Score had a high negative predictive value but low sensitivity, suggesting that STESS should be used cautiously. Of note, cEEG results altered clinical decision-making in three of four patients, irrespective of the presence or absence of status epilepticus, confirming the clinical value of cEEG in neurocritical care.

Resting-State NIRS-EEG in Unresponsive Patients with Acute Brain Injury: A Proof-of-Concept Study.

BACKGROUND: Neurovascular-based imaging techniques such as functional MRI (fMRI) may reveal signs of consciousness in clinically unresponsive patients but are often subject to logistical challenges in the intensive care unit (ICU). Near-infrared spectroscopy (NIRS) is another neurovascular imaging technique but low cost, can be performed serially at the bedside, and may be combined with electroencephalography (EEG), which are important advantages compared to fMRI. Combined NIRS-EEG, however, has never been evaluated for the assessment of neurovascular coupling and consciousness in acute brain injury. METHODS: We explored resting-state oscillations in eight-channel NIRS oxyhemoglobin and eight-channel EEG band-power signals to assess neurovascular coupling, the prerequisite for neurovascular-based imaging detection of consciousness, in patients with acute brain injury in the ICU (n = 9). Conscious neurological patients from step-down units and wards served as controls (n = 14). Unsupervised adaptive mixture-independent component analysis (AMICA) was used to correlate NIRS-EEG data with levels of consciousness and clinical outcome. RESULTS: Neurovascular coupling between NIRS oxyhemoglobin (0.07-0.13 Hz) and EEG band-power (1-12 Hz) signals at frontal areas was sensitive and prognostic to changing consciousness levels. AMICA revealed a mixture of five models from EEG data, with the relative probabilities of these models reflecting levels of consciousness over multiple days, although the accuracy was less than 85%. However, when combined with two channels of bilateral frontal neurovascular coupling, weighted k-nearest neighbor classification of AMICA probabilities distinguished unresponsive patients from conscious controls with > 90% accuracy (positive predictive value 93%, false discovery rate 7%) and, additionally, identified patients who subsequently failed to recover consciousness with > 99% accuracy. DISCUSSION: We suggest that NIRS-EEG for monitoring of acute brain injury in the ICU is worthy of further exploration. Normalization of neurovascular coupling may herald recovery of consciousness after acute brain injury.

A Precision Medicine Framework for Classifying Patients with Disorders of Consciousness: Advanced Classification of Consciousness Endotypes (ACCESS).

BACKGROUND: Consciousness in patients with brain injury is traditionally assessed based on semiological evaluation at the bedside. This classification is limited because of low granularity, ill-defined and rigid nomenclatures incompatible with the highly fluctuating nature of consciousness, failure to identify specific brain states like cognitive motor dissociation, and neglect for underlying biological mechanisms. Here, the authors present a pragmatic framework based on consciousness endotypes that combines clinical phenomenology with all essential physiological and biological data, emphasizing recovery trajectories, therapeutic potentials and clinical feasibility. METHODS: The Neurocritical Care Society's Curing Coma Campaign identified an international group of experts who convened in a series of online meetings between May and November 2020 to discuss and propose a novel framework for classifying consciousness. RESULTS: The expert group proposes Advanced Classification of Consciousness Endotypes (ACCESS), a tiered multidimensional framework reflecting increasing complexity and an aspiration to consider emerging and future approaches. Tier 1 is based on clinical phenotypes and structural imaging. Tier 2 adds functional measures including EEG, PET and functional MRI, that can be summarized using the Arousal, Volition, Cognition and Mechanisms (AVCM) score (where "Volition" signifies volitional motor responses). Finally, Tier 3 reflects dynamic changes over time with a (theoretically infinite) number of physiologically distinct states to outline consciousness recovery and identify opportunities for therapeutic interventions. CONCLUSIONS: Whereas Tiers 1 and 2 propose an approach for low-resource settings and state-of-the-art expertise at leading academic centers, respectively, Tier 3 is a visionary multidimensional consciousness paradigm driven by continuous incorporation of new knowledge while addressing the Curing Coma Campaign's aspirational goals.

Proceedings of the First Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness.

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.

Cerebrospinal fluid markers of inflammation and infections in schizophrenia and affective disorders: a systematic review and meta-analysis.

Infections and inflammatory processes have been associated with the development of schizophrenia and affective disorders; however, no study has yet systematically reviewed all available studies on cerebrospinal fluid (CSF) immune alterations. We aimed to systematically review the CSF immunological findings in schizophrenia spectrum and affective disorders. We identified all studies investigating CSF inflammatory markers in persons with schizophrenia or affective disorders published prior to March 23, 2017 searching PubMed, CENTRAL, EMBASE, Psychinfo, and LILACS. Literature search, data extraction and bias assessment were performed by two independent reviewers. Meta-analyses with standardized mean difference (SMD) including 95% confidence intervals (CI) were performed on case-healthy control studies. We identified 112 CSF studies published between 1942-2016, and 32 case-healthy control studies could be included in meta-analyses. Studies varied regarding gender distribution, age, disease duration, treatment, investigated biomarkers, and whether recruitment happened consecutively or based on clinical indication. The CSF/serum albumin ratio was increased in schizophrenia (1 study [54 patients]; SMD = 0.71; 95% CI 0.33-1.09) and affective disorders (4 studies [298 patients]; SMD = 0.41; 95% CI 0.23-0.60, I2 = 0%), compared to healthy controls. Total CSF protein was elevated in both schizophrenia (3 studies [97 patients]; SMD = 0.41; 95% CI 0.15-0.67, I2 = 0%) and affective disorders (2 studies [53 patients]; SMD = 0.80; 95% CI 0.39-1.21, I2 = 0%). The IgG ratio was increased in schizophrenia (1 study [54 patients]; SMD = 0.68; 95% CI 0.30-1.06), whereas the IgG Albumin ratio was decreased (1 study [32 patients]; SMD = -0.62; 95% CI -1.13 to -0.12). Interleukin-6 (IL-6) levels (7 studies [230 patients]; SMD = 0.55; 95% CI 0.35-0.76; I2 = 1%) and IL-8 levels (3 studies [95 patients]; SMD = 0.46; 95% CI 0.17-0.75, I2 = 0%) were increased in schizophrenia but not significantly increased in affective disorders. Most of the remaining inflammatory markers were not significantly different compared to healthy controls in the meta-analyses. However, in the studies which did not include healthy controls, CSF abnormalities were more common, and two studies found CSF dependent re-diagnosis in 3.2-6%. Current findings suggest that schizophrenia and affective disorders may have CSF abnormalities including signs of blood-brain barrier impairment and inflammation. However, the available evidence does not allow any firm conclusion since all studies showed at least some degree of bias and vastly lacked inclusion of confounding factors. Moreover, only few studies investigated the same parameters with healthy controls and high-quality longitudinal CSF studies are lacking, including impact of psychotropic medications, lifestyle factors and potential benefits of anti-inflammatory treatment in subgroups with CSF inflammation.