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 Thirty-one (36%) patients died in the ICU, including 28 who had life-sustaining therapy withdrawn.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.

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.

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.

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.

Detecting signatures of consciousness in acute brain injury after stimulation with apomorphine and methylphenidate: protocol for a placebo-controlled, randomized, cross-over study.

Introduction: Acute brain injury can lead to states of decreased consciousness, that is, disorder of consciousness (DoC). Detecting signs of consciousness early is vital for DoC management in the intensive care unit (ICU), neurorehabilitation and long-term prognosis. Our primary objective is to investigate the potential of pharmacological stimulant therapies in eliciting signs of consciousness among unresponsive or low-responsive acute DoC patients. Methods: In a placebo-controlled, randomised, cross-over setting, we evaluate the effect of methylphenidate and apomorphine in 50 DoC patients with acute traumatic or non-traumatic brain injury admitted to the ICU. Patients are examined before and after administration of the trial drugs using (1) neurobehavioural scales to determine the clinical level of consciousness, (2) automated pupillometry to record pupillary responses as a signature for awareness and (3) near-infrared spectroscopy combined with electroencephalography to record neurovascular coupling as a measure for cortical activity. Primary outcomes include pupillary dilations and increase in cortical activity during passive and active paradigms. Ethics: The study has been approved by the ethics committee (Journal-nr: H-21022096) and follows the principles of the Declaration of Helsinki. It is deemed to pose minimal risks and to hold a significant potential to improve treatment options for DoC patients. If the stimulants are shown to enhance cortical modulation of pupillary function and neurovascular coupling, this would warrant a large multicentre trial to evaluate their clinical impact. Dissemination: Results will be available on EudraCT, clinicaltrialsregister.eu and published in an international peer-reviewed journal. Trial registration number: EudraCT Number: 2021-001453-31.

Validating quantitative pupillometry thresholds for neuroprognostication after out-of-hospital cardiac arrest. A predefined substudy of the Blood Pressure and Oxygenations Targets After Cardiac Arrest (BOX)-trial.

PURPOSE: Out-of-hospital cardiac arrest (OHCA) survivors face significant risks of complications and death from hypoxic-ischemic brain injury leading to withdrawal of life-sustaining treatment (WLST). Accurate multimodal neuroprognostication, including automated pupillometry, is essential to avoid inappropriate WLST. However, inconsistent study results hinder standardized threshold recommendations. We aimed to validate proposed pupillometry thresholds with no false predictions of unfavorable outcomes in comatose OHCA survivors. METHODS: In the multi-center BOX-trial, quantitative measurements of automated pupillometry (quantitatively assessed pupillary light reflex [qPLR] and Neurological Pupil index [NPi]) were obtained at admission (0 h) and after 24, 48, and 72 h in comatose patients resuscitated from OHCA. We aimed to validate qPLR < 4% and NPi ≤ 2, predicting unfavorable neurological conditions defined as Cerebral Performance Category 3-5 at follow-up. Combined with 48-h neuron-specific enolase (NSE) > 60 µg/L, pupillometry was evaluated for multimodal neuroprognostication in comatose patients with Glasgow Motor Score (M) ≤ 3 at ≥ 72 h. RESULTS: From March 2017 to December 2021, we consecutively enrolled 710 OHCA survivors (mean age: 63 ± 14 years; 82% males), and 266 (37%) patients had unfavorable neurological outcomes. An NPi ≤ 2 predicted outcome with 0% false-positive rate (FPR) at all time points (0-72 h), and qPLR < 4% at 24-72 h. In patients with M ≤ 3 at ≥ 72 h, pupillometry thresholds significantly increased the sensitivity of NSE, from 42% (35-51%) to 55% (47-63%) for qPLR and 50% (42-58%) for NPi, maintaining 0% (0-0%) FPR. CONCLUSION: Quantitative pupillometry thresholds predict unfavorable neurological outcomes in comatose OHCA survivors and increase the sensitivity of NSE in a multimodal approach at ≥ 72 h.

Criteria for brain death in Denmark.

In 1990, the Danish brain death legislation was adopted by the Danish Parliament. Each year, around 100 patients in Denmark fulfil criteria for brain death/death by neurological criteria (BD/DNC). In this review of current Danish criteria including the indication for ancillary investigation, which in Denmark is digital subtraction angiography (DSA), we conclude that the time has come to revise the national BD/DNC criteria. We propose that visible anoxic-ischaemic encephalopathy on brain CT after cardiac arrest does not require evaluation by ancillary testing, and that CT-angiography can be used instead of DSA.

Confirmatory digital subtraction angiography after clinical brain death/death by neurological criteria: impact on number of donors and organ transplants.

Background: Demand for organs exceeds the number of transplants available, underscoring the need to optimize organ donation procedures. However, protocols for determining brain death (BD)/death by neurological criteria (DNC) vary considerably worldwide. In Denmark, digital subtraction angiography (DSA) is the only legally approved confirmatory test for diagnosing BD/DNC. We investigated the effect of the time delay caused by (repeat) confirmatory DSA on the number of organs donated by patients meeting clinical criteria for BD/DNC. We hypothesized that, first, patients investigated with ≥2 DSAs donate fewer organs than those investigated with a single DSA; second, radiological interpretation of DSA is subject to interrater variability; and third, residual intracranial circulation is inversely correlated with inotropic blood pressure support. Methods: All DSAs performed over a 7-year period as part of BD/DNC protocols at Rigshospitalet, Copenhagen University Hospital, Denmark, were included. Clinical data were extracted from electronic health records. DSAs were reinterpreted by an independent neurinterventionist blinded to the original radiological reports. Results: We identified 130 DSAs in 100 eligible patients. Patients with ≥2 DSAs (n = 20) donated fewer organs (1.7 +/- 1.6 SD) than patients undergoing a single DSA (n = 80, 2.6 +/- 1.7 organs, p = 0.03), and they became less often donors (n = 12, 60%) than patients with just 1 DSA (n = 65, 81.3%; p = 0.04). Interrater agreement of radiological DSA interpretation was 88.5% (Cohen's kappa = 0.76). Patients with self-maintained blood pressure had more often residual intracranial circulation (n = 13/26, 50%) than patients requiring inotropic support (n = 14/74, 18.9%; OR = 0.23, 95% CI [0.09-0.61]; p = 0.002). Discussion: In potential donors who fulfill clinical BD/DNC criteria, delays caused by repetition of confirmatory DSA result in lost donors and organ transplants. Self-maintained blood pressure at the time of clinical BD/DNC increases the odds for residual intracranial circulation, creating diagnostic uncertainty because radiological DSA interpretation is not uniform. We suggest that avoiding unnecessary repetition of confirmatory investigations like DSA may result in more organs donated.

Quantitative pupillometry for neuroprognostication in comatose post-cardiac arrest patients: A protocol for a predefined sub-study of the Blood pressure and Oxygenations Targets after Out-of-Hospital Cardiac Arrest (BOX)-trial.

Background: Resuscitation guidelines propose a multimodal prognostication strategy algorithm at ≥72 hours after the return of spontaneous circulation to evaluate neurological outcome for unconscious cardiac arrest survivors. Even though guidelines suggest quantitative pupillometry for assessing pupillary light reflex, threshold values are not yet validated.This study aims to validate pre-specified thresholds of quantitative pupillometry by quantitatively assessing the percentage reduction of pupillary size (qPLR) <4% and Neurological Pupil index (NPi) ≤2 and in predicting unfavorable neurological outcome. Both as an isolated predictor and combined with guideline-suggested neuron-specific enolase (NSE) threshold >60 µg L-1 in the current prognostication strategy algorithm. Methods: We conduct this pre-planned diagnostic sub-study in the randomized, controlled, multicenter clinical trial "Blood Pressure and Oxygenation Targets after Out-of-Hospital Cardiac Arrest-trial". Blinded to treating physicians and outcome assessors, measurements of qPLR and NPi are obtained from cardiac arrest survivors at time points (±6 hours) of admission, after 24, 48, and 72 hours, or until the time of awakening or death. Discussion: This study will be the largest prospective study investigating the predictive performance of automated quantitative pupillometry in unconscious patients resuscitated from cardiac arrest. We will test specific threshold values of NPi ≤2 and qPLR <4% to predict unfavorable outcome following cardiac arrest. The validation of pupillometry alone and combined with NSE with the criteria of the current prognostication strategy algorithm will hopefully increase the level of evidence and support clinical neuroprognostication with automated quantitative pupillometry in unconscious post-cardiac arrest patients. Trial registration: Registered March 30, 2017, at ClinicalTrials.gov (Identifier: NCT03141099).

Specific thresholds of quantitative pupillometry parameters predict unfavorable outcome in comatose survivors early after cardiac arrest.

Aim: Quantitative pupillometry is the guideline-recommended method for assessing pupillary light reflex for multimodal prognostication in comatose patients resuscitated from out-of-hospital cardiac arrest (OHCA). However, threshold values predicting an unfavorable outcome have been inconsistent across studies; therefore, we aimed to identify specific thresholds for all quantitative pupillometry parameters. Methods: Comatose post-OHCA patients were consecutively admitted to the cardiac arrest center at Copenhagen University Hospital Rigshospitalet from April 2015 to June 2017. The parameters of quantitatively assessed pupillary light reflex (qPLR), Neurological Pupil index (NPi), average/max constriction velocity (CV/MCV), dilation velocity (DV), and latency of constriction (Lat) were recorded on the first three days after admission. We evaluated the prognostic performance and identified thresholds achieving zero percent false positive rate (0% PFR) for an unfavorable outcome of 90-day Cerebral Performance Category (CPC) 3-5. Treating physicians were blinded for pupillometry results. Results: Of the 135 post-OHCA patients, the primary outcome occurred for 53 (39%) patients.On any day during hospitalization, a qPLR < 4%, NPi < 2.45, CV < 0.1 mm/s, and an MCV < 0.335 mm/s predicted 90-day unfavorable neurological outcome with 0% FPR (95%CI: 0-0%), with sensitivities of 28% (17-40%), 9% (2-19%), 13% (6-23%), and 17% (8-26%), respectively on day 1. Conclusion: We found that specific thresholds of all quantitative pupillometry parameters, measured at any time following hospital admission until day 3, predicted a 90-day unfavorable outcome with 0% FPR in comatose patients resuscitated from OHCA. However, at 0% FPR, thresholds resulted in low sensitivity. These findings should be further validated in larger multicenter clinical trials.

Incidence and prevalence of coma in the UK and the USA.

The epidemiology of coma is unknown because case ascertainment with traditional methods is difficult. Here, we used crowdsourcing methodology to estimate the incidence and prevalence of coma in the UK and the USA. We recruited UK and US laypeople (aged ≥18 years) who were nationally representative (i.e. matched for age, gender and ethnicity according to census data) of the UK and the USA, respectively, utilizing a crowdsourcing platform. We provided a description of coma and asked survey participants if they-'right now' or 'within the last year'-had a family member in coma. These participants (UK n = 994, USA n = 977) provided data on 30 387 family members (UK n = 14 124, USA n = 16 263). We found more coma cases in the USA (n = 47) than in the UK (n = 20; P = 0.009). We identified one coma case in the UK (0.007%, 95% confidence interval 0.00-0.04%) on the day of the survey and 19 new coma cases (0.13%, 95% confidence interval 0.08-0.21%) within the preceding year, resulting in an annual incidence of 135/100 000 (95% confidence interval 81-210) and a point prevalence of 7 cases per 100 000 population (95% confidence interval 0.18-39.44) in the UK. We identified five cases in the USA (0.031%, 95% confidence interval 0.01-0.07%) on the day of the survey and 42 new cases (0.26%, 95% confidence interval 0.19-0.35%) within the preceding year, resulting in an annual incidence of 258/100 000 (95% confidence interval 186-349) and a point prevalence of 31 cases per 100 000 population (95% confidence interval 9.98-71.73) in the USA. The five most common causes were stroke, medically induced coma, COVID-19, traumatic brain injury and cardiac arrest. To summarize, for the first time, we report incidence and prevalence estimates for coma across diagnosis types and settings in the UK and the USA using crowdsourcing methods. Coma may be more prevalent in the USA than in the UK, which requires further investigation. These data are urgently needed to expand the public health perspective on coma and disorders of consciousness.

Global warming and neurological practice: systematic review.

BACKGROUND: Climate change, including global warming, will cause poorer global health and rising numbers of environmental refugees. As neurological disorders account for a major share of morbidity and mortality worldwide, global warming is also destined to alter neurological practice; however, to what extent and by which mechanisms is unknown. We aimed to collect information about the effects of ambient temperatures and human migration on the epidemiology and clinical manifestations of neurological disorders. METHODS: We searched PubMed and Scopus from 01/2000 to 12/2020 for human studies addressing the influence of ambient temperatures and human migration on Alzheimer's and non-Alzheimer's dementia, epilepsy, headache/migraine, multiple sclerosis, Parkinson's disease, stroke, and tick-borne encephalitis (a model disease for neuroinfections). The protocol was pre-registered with PROSPERO (2020 CRD42020147543). RESULTS: Ninety-three studies met inclusion criteria, 84 of which reported on ambient temperatures and nine on migration. Overall, most temperature studies suggested a relationship between increasing temperatures and higher mortality and/or morbidity, whereas results were more ambiguous for migration studies. However, we were unable to identify a single adequately designed study addressing how global warming and human migration will change neurological practice. Still, extracted data indicated multiple ways by which these aspects might alter neurological morbidity and mortality soon. CONCLUSION: Significant heterogeneity exists across studies with respect to methodology, outcome measures, confounders and study design, including lack of data from low-income countries, but the evidence so far suggests that climate change will affect the practice of all major neurological disorders in the near future. Adequately designed studies to address this issue are urgently needed, requiring concerted efforts from the entire neurological community.

Public opinion and legislations related to brain death, circulatory death and organ donation.

BACKGROUND: It is poorly understood how public perception of the difference between brain death and circulatory death may influence attitudes towards organ donation. We investigated the public opinion on brain death versus circulatory death and documented inconsistencies in the legislations of countries with different cultural and socioeconomic backgrounds. METHODS: Using a crowdsourcing approach, we randomized 1072 participants from 30 countries to a case report of organ donation after brain death or to one following circulatory death. Further, we sampled guidelines from 24 countries and 5 continents. RESULTS: Of all participants, 73% stated they would be willing to donate all organs, while 16% would want to donate some of their organs. To increase the rate of donations, 47% would agree with organ donation without family consent as the default. Exposure to "brain death" was not associated with a lesser likelihood of participants agreeing with organ donation (82.1%) compared to "circulatory death" (81.9%; relative risk 1.02, 95% CI 0.99 to 1.03; p = .11). However, participants exposed to "circulatory death" were more certain that the patient was truly dead (87.9% ±â€¯19.7%) than participants exposed to "brain death" (84.1% ±â€¯22.7%; Cohen's d 0.18; p = 0:004). Sampling of guidelines revealed large differences between countries regarding procedures required to confirm brain death and circulatory death, respectively. CONCLUSIONS: Implementation of organ donation after circulatory death is unlikely to negatively influence the willingness to donate organs, but legislation is still brain death-based in most countries. The time seems ripe to increase the rate of circulatory death-based organ donation.