Limitation of life sustaining therapy in disorders of consciousness: ethics and practice.

Clinical conversations surrounding the continuation or limitation of life-sustaining therapies (LLST) are both challenging and tragically necessary for patients with disorders of consciousness (DoC) following severe brain injury. Divergent cultural, philosophical and religious perspectives contribute to vast heterogeneity in clinical approaches to LLST-as reflected in regional differences and inter-clinician variability. Here we provide an ethical analysis of factors that inform LLST decisions among patients with DoC. We begin by introducing the clinical and ethical challenge and clarifying the distinction between withdrawing and withholding life-sustaining therapy. We then describe relevant factors that influence LLST decision-making including diagnostic and prognostic uncertainty, perception of pain, defining a 'good' outcome, and the role of clinicians. In concluding sections, we explore global variation in LLST practices as they pertain to patients with DoC and examine the impact of cultural and religious perspectives on approaches to LLST. Understanding and respecting the cultural and religious perspectives of patients and surrogates is essential to protecting patient autonomy and advancing goal-concordant care during critical moments of medical decision-making involving patients with DoC.

Neuroimmune activation is associated with neurological outcome in anoxic and traumatic coma.

The pathophysiological underpinnings of critically disrupted brain connectomes resulting in coma are poorly understood. Inflammation is potentially an important but still undervalued factor. Here, we present a first-in-human prospective study using the 18-kDa translocator protein (TSPO) radioligand 18F-DPA714 for PET imaging to allow in vivo neuroimmune activation quantification in patients with coma (n = 17) following either anoxia or traumatic brain injuries in comparison with age- and sex-matched controls. Our findings yielded novel evidence of an early inflammatory component predominantly located within key cortical and subcortical brain structures that are putatively implicated in consciousness emergence and maintenance after severe brain injury (i.e. mesocircuit and frontoparietal networks). We observed that traumatic and anoxic patients with coma have distinct neuroimmune activation profiles, both in terms of intensity and spatial distribution. Finally, we demonstrated that both the total amount and specific distribution of PET-measurable neuroinflammation within the brain mesocircuit were associated with the patient's recovery potential. We suggest that our results can be developed for use both as a new neuroprognostication tool and as a promising biometric to guide future clinical trials targeting glial activity very early after severe brain injury.

Exploring the clinical diagnostic value of linguistic learning ability in patients with disorders of consciousness using electrooculography.

For patients with disorders of consciousness (DoC), accurate assessment of residual consciousness levels and cognitive abilities is critical for developing appropriate rehabilitation interventions. In this study, we investigated the potential of electrooculography (EOG) in assessing language processing abilities and consciousness levels. Patients' EOG data and related electrophysiological data were analysed before and after explicit language learning. The results showed distinct differences in vocabulary learning patterns among patients with varying levels of consciousness. While minimally conscious patients showed significant neural tracking of artificial words and notable learning effects similar to those observed in healthy controls, whereas patients with unresponsive wakefulness syndrome did not show such effects. Correlation analysis further indicated that EOG detected vocabulary learning effects with comparable validity to electroencephalography, reinforcing the credibility of EOG indicator as a diagnostic tool. Critically, EOG also revealed significant correlations between individual patients' linguistic learning performance and their Oromotor/verbal function as assessed through behavioural scales. In conclusion, this study explored the differences in language processing abilities among patients with varying consciousness levels. By demonstrating the utility of EOG in evaluating consciousness and detecting vocabulary learning effects, as well as its potential to guide personalised rehabilitation, our findings indicate that EOG indicators show promise as a rapid, accurate and effective additional tool for diagnosing and managing patients with DoC.

Precise detection of awareness in disorders of consciousness using deep learning framework.

Diagnosis of disorders of consciousness (DOC) remains a formidable challenge. Deep learning methods have been widely applied in general neurological and psychiatry disorders, while limited in DOC domain. Considering the successful use of resting-state functional MRI (rs-fMRI) for evaluating patients with DOC, this study seeks to explore the conjunction of deep learning techniques and rs-fMRI in precisely detecting awareness in DOC. We initiated our research with a benchmark dataset comprising 140 participants, including 76 unresponsive wakefulness syndrome (UWS), 25 minimally conscious state (MCS), and 39 Controls, from three independent sites. We developed a cascade 3D EfficientNet-B3-based deep learning framework tailored for discriminating MCS from UWS patients, referred to as "DeepDOC", and compared its performance against five state-of-the-art machine learning models. We also included an independent dataset consists of 11 DOC patients to test whether our model could identify patients with cognitive motor dissociation (CMD), in which DOC patients were behaviorally diagnosed unconscious but could be detected conscious by brain computer interface (BCI) method. Our results demonstrate that DeepDOC outperforms the five machine learning models, achieving an area under curve (AUC) value of 0.927 and accuracy of 0.861 for distinguishing MCS from UWS patients. More importantly, DeepDOC excels in CMD identification, achieving an AUC of 1 and accuracy of 0.909. Using gradient-weighted class activation mapping algorithm, we found that the posterior cortex, encompassing the visual cortex, posterior middle temporal gyrus, posterior cingulate cortex, precuneus, and cerebellum, as making a more substantial contribution to classification compared to other brain regions. This research offers a convenient and accurate method for detecting covert awareness in patients with MCS and CMD using rs-fMRI data.

Multimodal approaches supporting the diagnosis, prognosis and investigation of neural correlates of disorders of consciousness: A systematic review.

The limits of the standard, behaviour-based clinical assessment of patients with disorders of consciousness (DoC) prompted the employment of functional neuroimaging, neurometabolic, neurophysiological and neurostimulation techniques, to detect brain-based covert markers of awareness. However, uni-modal approaches, consisting in employing just one of those techniques, are usually not sufficient to provide an exhaustive exploration of the neural underpinnings of residual awareness. This systematic review aimed at collecting the evidence from studies employing a multimodal approach, that is, combining more instruments to complement DoC diagnosis, prognosis and better investigating their neural correlates. Following the PRISMA guidelines, records from PubMed, EMBASE and Scopus were screened to select peer-review original articles in which a multi-modal approach was used for the assessment of adult patients with a diagnosis of DoC. Ninety-two observational studies and 32 case reports or case series met the inclusion criteria. Results highlighted a diagnostic and prognostic advantage of multi-modal approaches that involve electroencephalography-based (EEG-based) measurements together with neuroimaging or neurometabolic data or with neurostimulation. Multimodal assessment deepened the knowledge on the neural networks underlying consciousness, by showing correlations between the integrity of the default mode network and the different clinical diagnosis of DoC. However, except for studies using transcranial magnetic stimulation combined with electroencephalography, the integration of more than one technique in most of the cases occurs without an a priori-designed multi-modal diagnostic approach. Our review supports the feasibility and underlines the advantages of a multimodal approach for the diagnosis, prognosis and for the investigation of neural correlates of DoCs.

A neurophysiological profiling of the heartbeat-evoked potential in severe acquired brain injuries: A focus on unconsciousness.

Unconsciousness in severe acquired brain injury (sABI) patients occurs with different cognitive and neural profiles. Perturbational approaches, which enable the estimation of proxies for brain reorganization, have added a new avenue for investigating the non-behavioural diagnosis of consciousness. In this prospective observational study, we conducted a comparative analysis of the topological patterns of heartbeat-evoked potentials (HEP) between patients experiencing a prolonged disorder of consciousness (pDoC) and patients emerging from a minimally consciousness state (eMCS). A total of 219 sABI patients were enrolled, each undergoing a synchronous EEG-ECG resting-state recording, together with a standardized consciousness diagnosis. A number of graph metrics were computed before/after the HEP (Before/After) using the R-peak on the ECG signal. The peak value of the global field power of the HEP was found to be significantly higher in eMCS patients with no difference in latency. Power spectrum was not able to discriminate consciousness neither Before nor After. Node assortativity and global efficiency were found to vary with different trends at unconsciousness. Lastly, the Perturbational Complexity Index of the HEP was found to be significantly higher in eMCS patients compared with pDoC. Given that cortical elaboration of peripheral inputs may serve as a non-behavioural determinant of consciousness, we have devised a low-cost and translatable technique capable of estimating causal proxies of brain functionality with an endogenous, non-invasive stimulus. Thus, we present an effective means to enhance consciousness assessment by incorporating the interaction between the autonomic nervous system (ANS) and central nervous system (CNS) into the loop.

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.

EEG Microstate Analysis in Patients with Disorders of Consciousness and Its Clinical Significance.

Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness.

Distinct Spectral Profiles of Awake Resting EEG in Disorders of Consciousness: The Role of Frequency and Topography of Oscillations.

The prolonged disorders of consciousness (PDOC) pose a challenge for an accurate clinical diagnosis, mainly due to patients' scarce or ambiguous behavioral responsiveness. Measurement of brain activity can support better diagnosis, independent of motor restrictions. Methods based on spectral analysis of resting-state EEG appear as a promising path, revealing specific changes within the internal brain dynamics in PDOC patients. In this study we used a robust method of resting-state EEG power spectrum parameter extraction to identify distinct spectral properties for different types of PDOC. Sixty patients and 37 healthy volunteers participated in this study. Patient group consisted of 22 unresponsive wakefulness patients, 25 minimally conscious patients and 13 patients emerging from the minimally conscious state. Ten minutes of resting EEG was acquired during wakefulness and transformed into individual power spectra. For each patient, using the spectral decomposition algorithm, we extracted maximum peak frequency within 1-14 Hz range in the centro-parietal region, and the antero-posterior (AP) gradient of the maximal frequency peak. All patients were behaviorally diagnosed using coma recovery scale-revised (CRS-R). The maximal peak frequency in the 1-14 Hz range successfully predicted both neurobehavioral capacity of patients as indicated by CRS-R total score and PDOC diagnosis. Additionally, in patients in whom only one peak within the 1-14 Hz range was observed, the AP gradient significantly contributed to the accuracy of prediction. We have identified three distinct spectral profiles of patients, likely representing separate neurophysiological modes of thalamocortical functioning. Etiology did not have significant influence on the obtained results.

Statistical learning in patients in the minimally conscious state.

When listening to speech, cortical activity can track mentally constructed linguistic units such as words, phrases, and sentences. Recent studies have also shown that the neural responses to mentally constructed linguistic units can predict the outcome of patients with disorders of consciousness (DoC). In healthy individuals, cortical tracking of linguistic units can be driven by both long-term linguistic knowledge and online learning of the transitional probability between syllables. Here, we investigated whether statistical learning could occur in patients in the minimally conscious state (MCS) and patients emerged from the MCS (EMCS) using electroencephalography (EEG). In Experiment 1, we presented to participants an isochronous sequence of syllables, which were composed of either 4 real disyllabic words or 4 reversed disyllabic words. An inter-trial phase coherence analysis revealed that the patient groups showed similar word tracking responses to real and reversed words. In Experiment 2, we presented trisyllabic artificial words that were defined by the transitional probability between words, and a significant word-rate EEG response was observed for MCS patients. These results suggested that statistical learning can occur with a minimal conscious level. The residual statistical learning ability in MCS patients could potentially be harnessed to induce neural plasticity.

Dopaminergic brainstem disconnection is common to pharmacological and pathological consciousness perturbation.

Clinical research into consciousness has long focused on cortical macroscopic networks and their disruption in pathological or pharmacological consciousness perturbation. Despite demonstrating diagnostic utility in disorders of consciousness (DoC) and monitoring anesthetic depth, these cortico-centric approaches have been unable to characterize which neurochemical systems may underpin consciousness alterations. Instead, preclinical experiments have long implicated the dopaminergic ventral tegmental area (VTA) in the brainstem. Despite dopaminergic agonist efficacy in DoC patients equally pointing to dopamine, the VTA has not been studied in human perturbed consciousness. To bridge this translational gap between preclinical subcortical and clinical cortico-centric perspectives, we assessed functional connectivity changes of a histologically characterized VTA using functional MRI recordings of pharmacologically (propofol sedation) and pathologically perturbed consciousness (DoC patients). Both cohorts demonstrated VTA disconnection from the precuneus and posterior cingulate (PCu/PCC), a main default mode network node widely implicated in consciousness. Strikingly, the stronger VTA-PCu/PCC connectivity was, the more the PCu/PCC functional connectome resembled its awake configuration, suggesting a possible neuromodulatory relationship. VTA-PCu/PCC connectivity increased toward healthy control levels only in DoC patients who behaviorally improved at follow-up assessment. To test whether VTA-PCu/PCC connectivity can be affected by a dopaminergic agonist, we demonstrated in a separate set of traumatic brain injury patients without DoC that methylphenidate significantly increased this connectivity. Together, our results characterize an in vivo dopaminergic connectivity deficit common to reversible and chronic consciousness perturbation. This noninvasive assessment of the dopaminergic system bridges preclinical and clinical work, associating dopaminergic VTA function with macroscopic network alterations, thereby elucidating a critical aspect of brainstem-cortical interplay for consciousness.

Factors influencing recovery in a pediatric sample with disorders of consciousness: insights from an observational study.

OBJECTIVE: To estimate rates and time to reach emergence of consciousness from vegetative state/unresponsive wakefulness syndrome (VS/UWS), and explore factors associated with improved recovery in children and adolescents with disorders of consciousness (DoC) following severe traumatic and non-traumatic brain injury. METHODS: Analytical, retrospective, cohort study. Clinical records of consecutively referred patients admitted in VS/UWS to a neurological rehabilitation institute in Argentina, between 2005 and 2021 were reviewed. Seventy children and adolescents were included in the analysis. A specialized 12-week rehabilitation program was administered, and emergence was defined by scores ≥44 points on the Western Neuro Sensory Stimulation Profile (WNSSP), sustained for at least 3 weeks on consecutive weekly evaluations. RESULTS: Emergence from VS/UWS to consciousness occurred within 5.4 (SD 2.6) weeks in almost one-third of patients. Multivariate Cox regression analysis showed emergence was significantly lower in patients with hypoxic ischemic encephalopathy compared to patients with other non-traumatic etiologies [HRadj 0.23 (95% CI 0.06-0.89); p = 0.03)]. CONCLUSIONS: Our findings reinforce growing evidence on the impact of etiology on DoC recovery in pediatric populations, ultimately influencing treatment and family-related decisions in child neurorehabilitation.

Conscious care: a proposed model to improve interprofessional care of patients with disorders of consciousness in the acute hospital setting.

BACKGROUND: Forty percent of individuals within the Disorders of Consciousness (DoC) spectrum are misdiagnosed as in a vegetative state/unresponsive wakefulness syndrome (VS/UWS) when in fact they are minimally conscious or emerged, underscoring a need to optimize evaluation techniques and interprofessional care management. PRIMARY OBJECTIVE: Conscious Care is a proposed care model that aims to improve interprofessional care of patients with DoC in the hospital setting. The aim of this paper is to describe this model's key ingredients and various components. CONCLUSIONS: This care model will advance clinician and caregiver preparedness to manage the complexities of this population and advocate for equal access to post-hospital medical and rehabilitative services. Evaluation and treatment of survivors of DoC should incorporate current evidence which drives continuous quality improvement and education to clinicians across the continuum of care. Immediate action must be taken to decrease the vulnerability and neglect of this marginalized population. Conscious Care is an innovative, sustainable solution that will improve interprofessional awareness of best practices and available science, strengthen care, and advocate for the right to quality of life that this population is so often denied.

Speech recovery after single-dose zolpidem in two minimally conscious patients with severe traumatic brain injuries: a case report.

BACKGROUND: In rare cases, zolpidem administration has been found to paradoxically improve cognition in patients with brain injury in disorders of consciousness. CASE PRESENTATION: Two minimally conscious plus (MCS+) patients at baseline, a 24-year-old woman 8 weeks post-traumatic brain injury (TBI) and 23-year-old man 6 weeks post-TBI, demonstrated behavioral improvements after off-label, single-dose administration of 10 mg of zolpidem. DISCUSSION/CONCLUSION: The patients demonstrated improved cognition on Coma Recovery Scale-Revised assessment after ingesting zolpidem. In particular, speech was substantially restored as one patient recovered functional communication and both demonstrated intelligible verbalizations for the first-time post-injuries following zolpidem. Overall, evidence is limited regarding the underlying mechanisms of various cognitive improvements in zolpidem response although studies incorporating neuroimaging are promising. The outcomes and similarities between these cases contribute to the current literature and highlight the need for rigorous studies in the future to guide zolpidem trials in patient care for those with DOC.

Reliability and validation of the Japanese version of the coma recovery scale-revised (CRS-R).

PRIMARY OBJECTIVE: This study aimed to verify the reliability and validity of the Japanese version of the Coma Recovery Scale-Revised (CRS-R). METHODS: Subjects included 59 patients with disorders of consciousness (DOC) due to acquired brain injury. To validate test-retest reliability, Evaluator A assessed the CRS-R twice on the same day (A1, A2). To examine inter-rater reliability, Evaluators A (A2) and B (B) assessed the CRS-R without a time interval. To test concurrent validity, Evaluator A (A1) assessed the CRS-R, Japan Coma Scale (JCS), and the Glasgow Coma Scale (GCS) consecutively. To validate diagnostic accuracy, we evaluated the degree of agreement between A1 and A2 and between A2 and B in their diagnosis of DOC by CRS-R. RESULTS: The test-retest (ρ = 0.92) and inter- (ρ = 0.98) reliability of CRS-R were excellent" and Concurrent validity of CRS-R with JCS (ρ = -0.82) and GCS (ρ = 0.92) were high. Results of DOC diagnosis were consistent for 48/59 cases (κ = 0.82) for A1 and A2 and for 54/59 cases (κ = 0.92) for A2 and B. CONLCUSION: The Japanese version of the CRS-R may be as reliable and valid as the original English and other language versions.

Long-term repetitive transcranial direct current stimulation in patients with disorders of consciousness: a preliminary study.

OBJECTIVES: To investigate the effects of long-term repetitive transcranial direct current stimulation on patients with DOC in the subacute phase. METHODS: In a randomized, double-blind, controlled study, 33 patients were randomly assigned to the active or sham group, and 28 patients completed the study. Patients in the active group received anodal stimulation over the DLPFC, while patients in the sham group received placebo stimulation (20 min/day, 5 days/week, for 4 weeks). The level of consciousness among patients was assessed with the Coma Recovery Scale-Revised (CRS-R) at baseline and at the end of every week from the first to the fourth week. RESULTS: The CRS-R scores of both the active and sham groups showed a consistent increasing trend over time; however, the treatment effect of the active group was better than that of the sham group. In addition, there was a statistically significant difference in the total CRS-R score between the two groups at weeks 1, 2, 3 and 4. Moreover, 10 patients (71.4%) in the active group and 3 patients (21.4%) in the sham group were regarded as responders. CONCLUSION: Long-term tDCS could improve the level of consciousness of patients with DOC in the subacute stage.

A Novel Approach to Screen for Somatosensory Evoked Potentials in Critical Care.

BACKGROUND: Somatosensory evoked potentials (SSEPs) help prognostication, particularly in patients with diffuse brain injury. However, use of SSEP is limited in critical care. We propose a novel, low-cost approach allowing acquisition of screening SSEP using widely available intensive care unit (ICU) equipment, specifically a peripheral "train-of-four" stimulator and standard electroencephalograph. METHODS: The median nerve was stimulated using a train-of-four stimulator, and a standard 21-channel electroencephalograph was recorded to generate the screening SSEP. Generation of the SSEP was supported by visual inspection, univariate event-related potentials statistics, and a multivariate support vector machine (SVM) decoding algorithm. This approach was validated in 15 healthy volunteers and validated against standard SSEPs in 10 ICU patients. The ability of this approach to predict poor neurological outcome, defined as death, vegetative state, or severe disability at 6 months, was tested in an additional set of 39 ICU patients. RESULTS: In each of the healthy volunteers, both the univariate and the SVM methods reliably detected SSEP responses. In patients, when compared against the standard SSEP method, the univariate event-related potentials method matched in nine of ten patients (sensitivity = 94%, specificity = 100%), and the SVM had 100% sensitivity and specificity when compared with the standard method. For the 49 ICU patients, we performed both the univariate and the SVM methods: a bilateral absence of short latency responses (n = 8) predicted poor neurological outcome with 0% FPR (sensitivity = 21%, specificity = 100%). CONCLUSIONS: Somatosensory evoked potentials can reliably be recorded using the proposed approach. Given the very good but slightly lower sensitivity of absent SSEPs in the proposed screening approach, confirmation of absent SSEP responses using standard SSEP recordings is advised.

Equity in Clinical Care and Research Involving Persons with Disorders of Consciousness.

People with disorders of consciousness (DoC) are characteristically unable to synchronously participate in decision-making about clinical care or research. The inability to self-advocate exacerbates preexisting socioeconomic and geographic disparities, which include the wide variability observed across individuals, hospitals, and countries in access to acute care, expertise, and sophisticated diagnostic, prognostic, and therapeutic interventions. Concerns about equity for people with DoC are particularly notable when they lack a surrogate decision-maker (legally referred to as "unrepresented" or "unbefriended"). Decisions about both short-term and long-term life-sustaining treatment typically rely on neuroprognostication and individual patient preferences that carry additional ethical considerations for people with DoC, as even individuals with well thought out advance directives cannot anticipate every possible situation to guide such decisions. Further challenges exist with the inclusion of people with DoC in research because consent must be completed (in most circumstances) through a surrogate, which excludes those who are unrepresented and may discourage investigators from exploring questions related to this population. In this article, the Curing Coma Campaign Ethics Working Group reviews equity considerations in clinical care and research involving persons with DoC in the following domains: (1) access to acute care and expertise, (2) access to diagnostics and therapeutics, (3) neuroprognostication, (4) medical decision-making for unrepresented people, (5) end-of-life decision-making, (6) access to postacute rehabilitative care, (7) access to research, (8) inclusion of unrepresented people in research, and (9) remuneration and reciprocity for research participation. The goal of this discussion is to advance equitable, harmonized, guideline-directed, and goal-concordant care for people with DoC of all backgrounds worldwide, prioritizing the ethical standards of respect for autonomy, beneficence, and justice. Although the focus of this evaluation is on people with DoC, much of the discussion can be extrapolated to other critically ill persons worldwide.

Common Data Element for Disorders of Consciousness: Recommendations from the Working Group on Therapeutic Interventions.

BACKGROUND: Over the past 30 years, there have been significant advances in the understanding of the mechanisms associated with loss and recovery of consciousness following severe brain injury. This work has provided a strong grounding for the development of novel restorative therapeutic interventions. Although all interventions are aimed at modulating and thereby restoring brain function, the landscape of existing interventions encompasses a very wide scope of techniques and protocols. Despite vigorous research efforts, few approaches have been assessed with rigorous, high-quality randomized controlled trials. As a growing number of exploratory interventions emerge, it is paramount to develop standardized approaches to reporting results. The successful evaluation of novel interventions depends on implementation of shared nomenclature and infrastructure. To address this gap, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups and charged them with developing common data elements (CDEs). Here, we report the work of the Therapeutic Interventions Working Group. METHODS: The working group reviewed existing CDEs relevant to therapeutic interventions within the National Institutes of Health National Institute of Neurological Disorders and Stroke database and reviewed the literature for assessing key areas of research in the intervention space. CDEs were then proposed, iteratively discussed and reviewed, classified, and organized in a case report form (CRF). RESULTS: We developed a unified CRF, including CDEs and key design elements (i.e., methodological or protocol parameters), divided into five sections: (1) patient information, (2) general study information, (3) behavioral interventions, (4) pharmacological interventions, and (5) device interventions. CONCLUSIONS: The newly created CRF enhances systematization of future work by proposing a portfolio of measures that should be collected in the development and implementation of studies assessing novel interventions intended to increase the level of consciousness or rate of recovery of consciousness in patients with disorders of consciousness.

Optimal Design of Clinical Trials Involving Persons with Disorders of Consciousness.

BACKGROUND: Limited data exist regarding the optimal clinical trial design for studies involving persons with disorders of consciousness (DoC), and only a few therapies have been tested in high-quality clinical trials. To address this, the Curing Coma Campaign Clinical Trial Working Group performed a gap analysis on the current state of clinical trials in DoC to identify the optimal clinical design for studies involving persons with DoC. METHODS: The Curing Coma Campaign Clinical Trial Working Group was divided into three subgroups to (1) review clinical trials involving persons with DoC, (2) identify unique challenges in the design of clinical trials involving persons with DoC, and (3) recommend optimal clinical trial designs for DoC. RESULTS: There were 3055 studies screened, and 66 were included in this review. Several knowledge gaps and unique challenges were identified. There is a lack of high-quality clinical trials, and most data regarding patients with DoC are based on observational studies focusing on patients with traumatic brain injury and cardiac arrest. There is a lack of a structured long-term outcome assessment with significant heterogeneity in the methodology, definitions of outcomes, and conduct of studies, especially for long-term follow-up. Another major barrier to conducting clinical trials is the lack of resources, especially in low-income countries. Based on the available data, we recommend incorporating trial designs that use master protocols, sequential multiple assessment randomized trials, and comparative effectiveness research. Adaptive platform trials using a multiarm, multistage approach offer substantial advantages and should make use of biomarkers to assess treatment responses to increase trial efficiency. Finally, sound infrastructure and international collaboration are essential to facilitate the conduct of trials in patients with DoC. CONCLUSIONS: Conduct of trials in patients with DoC should make use of master protocols and adaptive design and establish international registries incorporating standardized assessment tools. This will allow the establishment of evidence-based practice recommendations and decrease variations in care.