But which are the engines behind such shifts in surface reflectance patterns, vegetation response to global climate changes, or anomalies in the environmental control mechanisms? This article compares long-term environmental variables (1948–2021) to recent vegetation index data , 2001–2021) and presents regional trends in climate variability and vegetation response across Europe. Results show that positive trends in vegetation response, temperature, rainfall, and soil moisture are accompanied by a strong increase in climate anomalies over large parts of Europe. Vegetation dynamics are strongly coupled to increased temperature and enhanced soil moisture during winter and the early growing season in the northern latitudes. Simultaneously, temperature, precipitation, and soil moisture anomalies are strongly increasing. Such a strong amplification in climate variability across Europe further enhances the vulnerability of vegetation cover during extreme events.Europe witnessed a strong increase in climate variability and enhanced climate-induced extreme events, such as hot drought periods, mega heat waves, and persistent flooding and flash floods. Intensified land degradation, land use, and landcover changes further amplified the pressure on the environmental system functionalities and fuelled climate change feedbacks. On the other hand, global satellite observations detected a positive spectral greening trend—most likely as a response to rising atmospheric CO Droughts are among the most severe environmental disasters, enhancing ecological and socio-economic conflicts  and monthly climate and environmental variables  . All codes supporting the analyses are stored in a repository  and environmental variables from GLDAS (1948–2021)   were downloaded from the Earthdata server of the United States Geological Survey (USGS) (2) Didan . The NDVhttps://disc.gsfc.nasa.gov; last accessed 3rd of July 2022) . To visualize the temporal development over Europe, monthly mean values were calculated and plotted as annual and seasonal time series. For this reason, two spatial masks were created that distinguish into regions below and above the mean annual average temperature of the study area over the period 1948–2021 (7.046578 °C). Basically, this is a differentiation into a northern and a southern part but includes higher elevated areas into the lower annual average temperate range.Trend analyses in surface reflection patterns and environmental explanatory covariates were performed using a linear model and annual and seasonal composite raster stacks  and the first standard deviation (SD) were calculated from aggregated raster stacks of each variable. SD was subtracted from and added to the mean value  to create the range of the standard deviation for the reference period. The (m + SD) was subtracted from each single year and growing period value and all values ≤ 0 were removed for the upper limits of the standard deviation range. According to the lower limits of the standard deviation range, (m − SD) was subtracted from each year and growing period value and all values ≥ 0 were removed. Both parts were merged to show negative and positive trends. Eventually, raster mean values of negative and positive anomalies were extracted and visualized with a smoothing estimator of the ggplot2 package that uses a linear relationship between x and y (LOESS) ) is not strongly correlated with spectral greening Fig. . HoweverAcross the eastern European countries and Russia, NDVI is positively correlated with snowfall and surface snow cover thickness, which in turn contributes to soil moisture content during the early growing season (MAM). In Central and Northeastern Europe, a temperature-controlled vegetation response signal is visible from the analyses. Particularly, Poland, Scandinavia, and large parts of Russia are affected by a strong increase in JJA and DJF temperature. The strongly positive NDVI signals in Central Europe can most likely be linked to reduced snowfall and snow cover in winter and particularly during early spring, which enhances the surface reflectance. A shift in the phenological phases, an advanced onset of the growing season, and intensive irrigation during JJA can further influence the NDVI signal, giving the impression of intensified spectral greening. Similarly to the Mediterranean region, Central Europe experiences a drop in soil moisture, which could probably be explained by enhanced irrigation, crop production (e.g. potatoes and maize), and foliage cover ) increase across Europe, affecting both the southern as well as the northern regions, and subsequent hot and dry year periods are estimated to occur more frequently by the mid of the twenty-first century ) are increasingly frequent in coastal areas of the Iberian Peninsula, the UK, and the southern Alpine region stretching south across the Balkans. However, dry spells and negative P(rain) anomalies occur in the same regions, which emphasizes the very strong climate variability in large parts of Central Europe. An increase in winter heavy precipitation has been predicted in Western Europe for future climate models, particularly affecting the UK and parts of southwestern Scandinavia ) are increasingly positive across Russia and Norway. The Alpine region, however, shows a significantly negative tendency to snowfall and snow cover anomalies, according to the trend analysis.Long-term time series analysis of the selected GLDAS variables over the period 1948–2021 shows a strong increase in positive rainfall and snowfall flux (P(rain), P(snow)), followed by an increase in positive snow cover thickness Fig. . Mean neRemote sensing tools have gained momentum in large-scale observations of vegetation response to global warming, greening trend analyses, and landcover change monitoring. The recent trends in spectral greening and browning have been linked for example to surface water body fraction, increased temperature, atmospheric carbon input, and soil moisture content  are prone to beetle outbreaks, due to their high vulnerability to drought periods, rising temperature, and increased storm occurrences under a globally changing climate of the boreal zones (Čada et al., High temperatures paired with increasing soil moisture prolong the growing season in the high latitudes, which in turn amplifies the risk for windfall during storm season, bark beetle infections, and forest decline (Müller et al., Extreme heatwaves as in 2003 in Central Europe and particularly in 2010 across Russia have been traced back to atmospheric patterns that caused a massive increase in surface temperature (Di Capua et al., 2 atmospheric concentrations enhance ecosystem productivity in the high latitudes, increase the decomposition of organic matter in the permafrost region, and shift the climatic limitations of arable land towards the north (Liu et al., 2 and methane release from thawing permafrost (Knoblauch et al., 2 and other greenhouse gases from bare soil surfaces and reduces the carbon sink during vegetation cover decline (Lal et al., Global warming and coupled rising CO2 concentration, precipitation totals, the spread of agricultural exploitation, and increased warming of the permafrost in the Northern Hemisphere (Peng et al., 2 increase is particularly sensitive to soil moisture availability, soil type, and texture (Fay et al., European forests are highly vulnerable to rapid changes in ecosystem parameters caused by climate change (Forzieri et al., Parallel to this, the number of extreme years with heat waves is growing, which will raise questions regarding a calculable risk of future agricultural strategies. Central Europe is particularly affected, showing a strong increase in negative vegetation anomalies. These trends will intensify in the future and a reversal of the greening trend in the wake of prolonged droughts could lead to massive surface atmosphere interactions and regional climate amplifications. Further trend analyses of climate variables are needed to enhance the knowledge of regional environmental feedbacks. Monitoring surface transformations over long temporal periods is mostly limited by the scale and detailed ground-based measurements can be carried out only locally, which produces high spatial resolution datasets but lacks the comparison of global environmental response to global feedbacks (Cortés et al., Spectral greening shows increasing trends across most parts of Central and Northern Europe. In general, these have been linked to increasing atmospheric carbon content and rising temperatures—particularly in the northern latitudes. Simultaneously, climate variability is increasing rapidly, with higher frequencies of prolonged drought spells and severe flooding events caused by extreme weather events. Under climate change predictions, the temperature will further rise in most parts of Europe, which in turn accelerates moisture transport, soil moisture content, and eventually a longer growing season in the northern parts of Europe. On the other hand, the Mediterranean and large parts of Eastern and Southeastern Europe experience severe dry-up processes and strongly negative soil moisture trends, which impact natural vegetation and require massive irrigation measures to cope with rising surface temperatures, particularly in summer. These trends, however, do not remain restricted to the southern parts of Europe but affect Central and Eastern Europe and particularly Germany, Poland, and the central-eastern countries towards Ukraine. Landcover change caused by vegetation decline is already present in large parts of Russia and Ukraine and will further strengthen during persistent hot drought events in summer.


This proceedings article presents actionable research targets on the basis of the presentations and discussions at the 2nd Curing Coma National Institutes of Health (NIH) symposium held from May 3 to May 5, 2021. Here, we summarize the background, research priorities, panel discussions, and deliverables discussed during the symposium across six major domains related to disorders of consciousness. The six domains include (1) Biology of Coma, (2) Coma Database, (3) Neuroprognostication, (4) Care of Comatose Patients, (5) Early Clinical Trials, and (6) Long-term Recovery. Following the 1st Curing Coma NIH virtual symposium held on September 9 to September 10, 2020, six workgroups, each consisting of field experts in respective domains, were formed and tasked with identifying gaps and developing key priorities and deliverables to advance the mission of the Curing Coma Campaign. The highly interactive and inspiring presentations and panel discussions during the 3-day virtual NIH symposium identified several action items for the Curing Coma Campaign mission, which we summarize in this article.The online version contains supplementary material available at 10.1007/s12028-022-01505-3. The word “coma” is derived from the Greek word “Koma,” meaning deep sleep. The term was initially used in Hippocratic medicine and then in the second century by Galen before reappearing in the seventeenth century to describe the state of “lack of consciousness” . As provIn 1972, the term “persistent vegetative state” was used to describe the state of apparent wakefulness without awareness where responsiveness is limited to primitive postural and reflex movements of the limbs . Other fFrom the primitive understanding of DoC in the seventeenth century CE with the practice of “bloodletting” therapy for stroke, to the modern medicine involving multimodal and multidisciplinary care approach, our understanding of the biology of coma has improved significantly with improved diagnostic and monitoring tools. In 2006, Owen et al.  publishePatient and family perspectives are integral to curing coma . The symDespite the advances in mechanistic understandings, improved definitions, new tools, and revised clinical scales over the past five decades, management strategies and patient outcomes of comatose patients have not significantly improved. With the availability of diagnostic tools such as MRI, fluorodeoxyglucose positron emission tomography, and the EEG—along with some promising pharmacologic interventions to aid in coma recovery—the scientific community is more prepared than ever to undertake this mission to advance and improve the care of coma patients. As specialists with rigorous clinical training and dedicated careers in managing critically ill patients with coma and DoC, the neurocritical care community is optimally positioned to lead this mission. In 2016, the leaders of the Neurocritical Care Research Central (NCRC) and the Neurocritical Care Research Network of Neurocritical Care Society (NCS) identified important gaps in the organizational research portfolio of coma and DOC and envisioned an approach to bridge this gap constructively. This effort led to the Blue Ocean Strategy Meeting in 2018 , where a panel of multidisciplinary experts collectively agreed on the need for a collaborative approach to “cure coma.” Recognizing the need for a centralized platform to advance coma science, the Curing Coma Campaign (CCC) started with idea generation, expert consensus, and strategic planning. The CCC executive committee and the Scientific Advisory Council have worked diligently to build the infrastructure, identify, and recruit field experts and define important knowledge gaps to embark upon this ardent journey of improving care standards for patients with DoC [The National Institute of Neurological Disorders and Stroke (NINDS) initially collaborated with the CCC to organize a part I, 2-day virtual symposium in September 2020 to facilitate a broad discussion between various stakeholders, including CCC leadership, National Institutes of Health (NIH) representative, experts in coma science, industry partners, and patient advocates. The summary of the proceedings was published in the special CCC issue . FollowiThe CCC launched the biology of coma WG tasked with determining the state of the science in DoC. The WG was divided into four subgroups whose remits were to (1) account for DoC heterogeneity to refine endotypes, (2) characterize DoC mechanisms by multiple spatial–temporal scales, (3) move Curing Coma science toward individualized prognostic tools, and (4) develop systemic frameworks to optimize therapeutic trials. Details related to recommendations from each of the subgroups were published separately –25.There are specific sites critical for consciousness, but the absence of activation of these sites on functional imaging of patients with DoC  does noThere are systems and connections that subserve consciousness. However, consciousness is likely a function of individual traits  and disease states , which There are important characteristics of information transmitted by the systems and connections that subserve consciousness. There is a complex assignment of neural resources for task performance. Studies of neural correlates of consciousness demonstrate anticorrelations (negative correlations) between DMN and task-positive network in DoC. These anticorrelations serve as biomarkers of efficient resource allocation and indicate that the content of information processed is relevant for transmission . ConscioBrainstem arousal systems are important, with diverse roles and neurochemical signatures matched to function .Cortical interneurons are targets of neurochemical modulation , and theWhat are the neurochemical substrates that modulate this process?What do we know about biology that drives human consciousness? We know that there are genetic accompaniments to brain structures and systems associated with human evolution .Understanding DoC involves discerning its critical components that include key anatomical sites, systems and connections, characteristics of transmitted information, the neurochemical substrates and the biology that drives human consciousness. The current understanding of DoC along these five categories were discussed:. Identification of mechanisms involved in each phase of DoC across the C-EC-R spectrum would facilitate the development of targeted therapies specific to that phase.A framework for differentiating clinical subtypes of DoC is currently lacking. The WG proposed clinical differentiation of DoC based on the presence or absence of consciousness, environmental connectedness , and responsiveness (C-EC-R) . IdentifAs different regions of the brain are intricately connected in a complex fashion, focal structural changes can lead to distant or even global functional impact (diaschisis). There is a need to identify links between structural brain damage and related functional implications. The development of a comprehensive brain map using multimodal tools such as structural and functional neuroimaging, neurophysiological techniques, and whole-brain computational models is required to understand mechanisms of DoC on a macroscale. Various approaches such as the information theory, graph theory, and the dynamical systems theory also need to be leveraged for improved understanding of brain connectivity.A comprehensive understanding of the structural–functional relationship requires understanding the brain on a macroscale and a deep dive into the microenvironment consisting of genetic, cellular, molecular, microcircuits, and neurotransmitter substrates. Links between micro and macroscale need to be established using computational models and in-vivo animal models. To accomplish this, we need to (1) develop clinically relevant translational animal models of DoC, (2) identify the role of subcortical structures and their interplay with the cortex in heterogeneous models of DoC, and (3) establish the association of cellular  and subcellular (molecular and genetic) mediators with various DoC phenotypes. Effective collaboration between bench and clinical researchers is crucial to allow bidirectional hypothesis testing Combining both traditional hypothesis-driven and data-driven approaches is necessary to improve our understanding of DoC. In this regard, there is a need to (1) develop precise theoretical predictions and advance biomarker research to address each dimension of the C-EC-R framework, (2) build a comprehensive set of data and theory-driven biomarkers addressing multilevel analyses, and (3) compare and develop existing theories by promoting adversarial collaboration among thought leaders –46 in DoThere is a need to integrate levels of description, imaging modalities, and theoretical approaches. To develop endotypes, large-scale data sets are necessary to study the heterogeneity of DoC at different levels of analyses . Such data sets will also facilitate the construction of realistic computational models of DoC and the development of personalized medicine modelsThe biology of coma WG specifically identified five research priorities to accurately understand, diagnose, classify, prognosticate, and develop targeted therapies for patients with DoC.The panel discussed that the insights into the biology of consciousness are informed by multifaceted research in DoC and agreed that a parallel approach is needed to address these five goals to ensure significant and timely progress. In addition to leveraging existing data sets, there is a need for development of large data sets to help track the current drug therapies used in DoC and to evaluate their efficacy in DoC as means of identifying the underlying mechanisms.Further, the panel discussed that certain gene activation in cell models may inform the repair, synaptogenesis, and plasticity of genes to help researchers identify therapies for DoC related to those genes. For example, recent studies have revealed that certain genes, such as the human accelerated region genes, are differentially expressed in humans compared with those of chimpanzees and macaques and tend to have a role in expanding cognitive networks (particularly the DMN) . StudiesIn terms of the pediatric population, the panel discussed that recovery from brain injury in pediatric patients is unique regarding the fact that pediatric recovery not only means return to premorbid baseline but also involves demonstration of growth along the expected developmental trajectory. Hence, the panel emphasized the need to understand pediatric recovery trajectories as a separate entity from adult cohorts.Lastly, the panel discussed the need for a central database housing a full list of clinical trials related to DoC and reiterated that database designs that support both hypotheses-driven driven and data-driven approaches in parallel and in a complementary manner is necessary.Develop a program project or center of excellence model as the main push to foster open communication with integration of data from animals, humans, and in silico models to effectively move the field forward.Standardize clinical and behavioral assessment in patients with DoC to facilitate effective data collation across centers.Audit prevalence, management, and monitoring strategies and outcomes of patients with DoC in various centers across the world.Undertake health economic analysis for DoC research.Develop standards for clinical and behavioral assessments in DoC.Develop preclinical behavioral, neurophysiological, and neuroimaging models that could subsequently translate into clinical trials.Secure governmental research support for carefully selected individual (RO1 and training grants) as well as research projects  that integrate across disciplines  and across lifespan (birth to elderly) is essential. Apart from DoC research, funding should also focus on consciousness research as the foundation to understanding DoC.The deliverables for the biology of coma WG include the following:A large international data set that captures data from patients with DoC is crucial to gain insights into mechanisms, predictors, and trajectory of recovery and to lay the foundation for future interventional trials. The coma science database WG conducted a needs assessment in 2020 to understand the acute data needs of the coma science community. The majority of survey participants were primarily involved with clinical research affecting patients with DoC. According to the survey, the mission-critical data needed to accomplish goals toward curing coma included patient-specific data, encounter-specific data, and psychometric data. Additionally, survey participants recognized that long-term follow-up data and high-fidelity and time-synchronous data are needed but not currently accessible. The survey results, main research gaps, and challenges have been outlined in the proceedings article from the 1st symposium . A panelCDE development aims to streamline neuroscience clinical research using content standards that enable clinical investigators to systematically collect, analyze, and share data across the research community. The CDE project has been developed in collaboration with the NINDS to create CDEs specific to coma and DoC. A total of ten different WGs have been created to approach a variety of topics, including (1) clinical/behavioral phenotype, (2) hospital course/confounders/medications, (3) imaging (4), electrophysiology, (5) biospecimens, (6) pediatric and other patient groups, (7) therapeutic interventions, (8) physiologic data, (9) outcomes and end points, and (10) goals of care/family data. The WG members were intentionally selected to ensure diversity in scientific expertise, career stage and demographics while ensuring the inclusion of other stakeholders such as patient advocates and industry representatives. Final CDEs are expected to be published in 2022. The intended impact of this foundational work is to (1) reduce time/cost to develop data collection tools, (2) reduce study start-up time, (3) promote data collection in a consistent format, (4) improve data quality, and (5) facilitate collaborations and comparisons between studies and meta-analyses.Accommodate a variety of high-resolution data ensuring data flexibility, data validity and data harmonization.Effectively collect usable data with role-based access into a secure flexible app interface and federated or distributed data structure.Ensure proper data distribution, which includes distribution of primary studies’ data to study teams, exploratory post hoc analyses, performance data for best practices efforts, and patient/caregiver engagement.Ensure data governance and analysis structure to be transparent while maintaining data security, quality, integrity, storage, curation, and portability of a wide variety of data, including biomarker repository.Apart from CDE development, there is a need for a central database that would allow us to gain insights into mechanisms, predictors, and trajectory of recovery of coma and to lay the foundation for interventional trials. Currently, there are only a few limited data sets related to DoC with significant gaps, including variability in data collection and fragmentation of data between acute and long-term care. Existing consortia –49 offerThe coma science database WG has envisioned a complex network of tiered data collection approaches to include small community centers with clinical data to the large academic centers with the ability to obtain advanced imaging and high-resolution physiological data. Additionally, the development of a longitudinal model system to collect data from acute to chronic phases of DoC and beyond would facilitate the conduct of robust outcome studies of DoC. Data from various sources are envisioned to be housed in designated core CCC database centers across the globe, where the data are federated, curated, and distributed to promote DoC research. The WG has identified 50 commercial, academic, and registry-based database enterprises and is actively engaged in conversations with eligible vendors to select the right database for this colossal project.Develop a hybrid database architecture leveraging DoC-specific CDEs focused on linking high-resolution imaging and physiologic data with minimum necessary clinical data, including the long-term outcome data.Design a tier-based network organization to maximize the scalability of high-impact science and clinical trial design.Facilitate implementation of the broader research priorities of the CCC community, spanning scientific discovery and clinical evidence to clinical practice by focusing on concrete, short-term objectives.Facilitate translational scientific discoveries through an infrastructure that enable novel hypothesis discovery and preclinical validation of potential therapies.Create an infrastructure that facilitates longitudinal studies on outcomes assessment and research across the continuum of care.Enable a community of resource for novel statistical, analytical, and methodological approach on big data that emerge from studies on coma science.Design community, patient, and public engagement that provides timely information on best practices, expected outcomes, and available resources.To support the development of a coma science database, the WG proposed the following seven priorities:The panel agreed on the need to create a centralized prospective database structure to advance coma science and develop the foundation to support research priorities of other WGs. A comprehensive database accommodating acute through chronic phases of DoC is needed to cater to a variety of researchers across disease trajectory. Big data would be valuable regardless of whether it is collected at centers of excellence in a preplanned standardized format or heterogeneous clinical data acquired in a nonresearch setting, as it allows comparisons across cohorts and can help combine data-driven models of structure and function with theory-driven models. Additionally, big data are needed to test hypotheses, discover therapies and to develop personalized treatment of this complex disorder.The panel discussed that challenges regarding data collation of existing databases involving DoC include the use of heterogeneous data definitions , clinical practice variability, nonstandardized prognostication, and patient/family communication and the variability of management in different facilities across the trajectory of care. In terms of high-fidelity data, specific challenge includes the difference in data sampling frequency across institutions due to the lack of existing standards, thereby limiting data harmonization to the lowest sampling frequency across cohorts. The creation of CDEs and development of standardized protocols are therefore crucial to address these inconsistencies. Patient privacy regulation is another barrier when trying to collate data along disease trajectory from acute, subacute to chronic phases. The panel agreed that innovative ways to address privacy issues are needed to overcome barriers across care settings. Further, apart from serving as the structural unit for centralized data collection, CCC will also serve as the center of excellence for DoC to promote education regarding standardized data definitions, standardized data collection approaches, standardized communication around DoC with patients and families, and the development of guidelines related to DoC.A comprehensive database approach initiative of the CCC is envisioned to bridge the silos across various stakeholders including preclinical researchers, clinical researchers, nonclinicians, patients, and families and also across the disease trajectory in any individual patient. The panel expressed that a spoke and hub model is likely appropriate for such a massive undertaking with designated cores or centers of excellence for various types of data such as clinical data, biomarkers, physiologic and the imaging data. Finally, in the era of big data, the panel agreed that the integration of artificial intelligence (AI) and machine learning (ML) is important to move the field forward.Finalization of a vendor to establish comprehensive centralized database and secure adequate funding for initiation and maintenance of such a database.Identification of major hubs or centers of excellence for each data domain Standardization of data collection methodology including standard clinical, diagnostic, and prognostic measures.Development of a process for execution of data use agreements across collaborating centers.Development of education material for dissemination to collaborating centers.Creation of a central database using standardized CDEs that can provide the infrastructure for global collaboration and assist in breaking research bubbles.Seek strategic funding mechanisms with ability to combine databases across modalities  and scientific groups to help foster synergistic collaborations.The deliverables for the coma science database WG include the following:History and modern science have taught us that patients who appear unconscious may, in fact, not be unaware. One such example from recent history is that of Saul Bellow, a noble laureate who was assumed to be comatose during hospitalization, yet he was able to provide a stream of conscious narrative from his recollection during the period of presumed comatose state , 51. In Neuroprognostication refers to an understanding of the most likely prognostic trajectory in patients with neurologic injury by means of biomarkers, neuroimaging, clinical examination and other variables. Accurate neuroprognostication is important for effective communication with the surrogate decision-makers in terms of communicating the potential for recovery, likelihood of disability and the possibility of awakening from coma. During the 1st NIH symposium, five gaps in prognostication were identified: (1) end points for prognostic assessment have not been defined, (2) we do not have standard methods to reliably ascertain and statistically address withdrawal of life supporting therapy (WOLST), (3) we need to standardize and improve diagnostic evaluations and establish the right time window for neuroprognostication, (4) we need prediction tools that use comprehensive clinical information to create statistically appropriate models, and (5) prognostic communication and its impact on families’ decision-making in DOC is understudied.Prognostic markers should not just be available but also applicable and feasible across various clinical settings and disease mechanisms. We need accurate, precise, and clinically applicable tests that can serve most patients after onset of coma.Timing of prognostication is extremely important. Current clinical practice recommendations suggest delaying prognosis for cardiac CA until 72 h and at least 2–3 days for other patients with ABI. However, data suggest that delayed awakening beyond 72 h  can occuAs coma recovery is a dynamic process, prognostic markers, specific to disease phenotypes should either have the flexibility to be applied across the DoC trajectory or we need to develop multiple tests specific to the stage of coma.Communication strategies congruent with the values and preferences of patients and surrogates should be developed.The existing neuroprognostication research structure of DoC is fragmented, lacks the infrastructure to support collaboration, and lacks prognostic accuracy given categorization of disease based on overt presentation rather than mechanistic understandings. Existing limitations are related to the use of convenience samples with small sample size, lack of blinding and lack of external validation. The biggest limitation, however, is related to early WOLST. There is a need to develop consensus on how to study coma, either by DoC phenotype , primary injury type  or neuroanatomic injury subtypes . Neuroprognostication parameters need to be approached as index tests based on relevant neurologic function that are directly related to the functional outcomes and affect the quality of life . There iThe World Health Organization international classification of functioning, disability, and health includes three components: (1) impairments, (2) functional ability, and (3) engagement in activity and participation. A variety of functional and other outcome measures should be included with granularity in prognostic research. Further, to address the numerous confounders of death reporting , reporting should also include the mode of death, timing from injury, extent of support at the time of death, reason for WOLST and reason for primary injury at the time of presentation (if applicable).Despite the widespread nihilism, particularly in DoC related to CA, available evidence suggests that patients with coma continue to improve post discharge and outcomes continue to evolve over 1–6 months after injury , 57. PatIn-depth understanding of limitations regarding available evidence for neuroprognostication will guide the design of future studies. Efforts should be focused on developing models with accurate calibration using large amount of clinical data. There are several existing candidate tests and data which need to be evaluated simultaneously with an aim toward development of multivariable models to allow incremental accuracy of neuroprognostication. To develop such models, we need a large multicenter prospective observational coma registry that includes key prognostic data including diverse etiologies of DoC with serial testing over time. Important variables to consider include the following: (1) clinical examination including phenotypes of DoC (2) somatosensory evoked potential (SSEP) to assess thalamocortical connectivity, (3) serological/cerebrospinal fluid/chemical/genetic biomarkers, (4) Functional neuroimaging pertaining to stages of coma, (5) EEG with quantified parameters, and (6) brain-computer interface and other novel technologies. Additionally, inclusion of baseline variables , intensity of management (acute and rehab phase) and inclusion of pediatric population is important. Also, there is a need for innovative methods of analysis to assess predictors from early to late phases of DoC. Accurate modeling of prognosis and disease trajectory for personalized prognostication could benefit from advanced statistical methods and novel tools such as ML technology for data assimilation. In such models, external validation of the outcome metrics in a large independent cohort is crucial.Develop prognostic indicators for patients with various mechanisms of DoC meeting consensus criteria that is accurate, reliable, conducted at specific time points, flexible across the disease trajectory, and congruent with patient and surrogate’s preexisting values and preferences.Develop consensus on how to study neuroanatomic injury subtypes and assessment with targeted modalities linked to meaningful outcomes .Design a multicenter prospective observational coma registry including pediatric population with data captured across the outcome trajectory .Identify ways to facilitate communication of prognosis and prognostic uncertainty between clinicians and patients/families.Based on the identified gaps, the WG formulated four main research priorities for neuroprognostication:The panel discussed that there is a general sense of nihilism among clinical practitioners and one of the goals of CCC should be to help communicate the complexity of DoC prognosis and help develop an understanding of the confidence interval for neuroprognostication at various stages of DoC. A parcellated prognostication approach with stepwise milestones throughout the course of recovery would be more appropriate than a dichotomized prognostication of favorable versus unfavorable outcome. Panel reiterated the complexity of neuroprognostication in the pediatric population due to the continued neurodevelopment through the course of recovery and highlighted the need for robust longitudinal studies on recovery trajectory and prognostic approaches on all age groups.The panel also discussed that one of the issues with clinical trials on neuroprognostication is the ethical aspect of continuation of life supporting therapy especially if it does not concur with the values of the patient and surrogates. Such patients and families should be excluded from clinical trials on prognostication. Widespread education endeavors are needed to change the culture of nihilism among providers and families. However, a trial that requires prolongation of DNR or WOLST wait times would require an in-depth discussion with the families in addition to detailed informed consent. Data from countries with cultures that support prolongation of life supporting measures would be helpful in determining the natural history of DoC. Within the United States, one of the limiting factors might also be related to the DNR orders in which some clinicians and families may perceive this to mean “do not provide aggressive medical therapy,” even though the intended use of this order is only for the clinical management of one specific clinical scenario . The panel highlighted the need to develop protocols surrounding WOLST decisions and address confounders  that impact outcomes. Further, the panel discussed the need to identify key elements and strategies for communicating uncertainty in a tactful, emotionally supportive and culturally competent manner followed by verification of surrogates’ understanding of outcome communication.To define consensus standards for prognostication research: The goal is to define the highest value prognostic tests with an appropriate timeline for testing that is needed to determine patient/family centric high value outcomes.To develop mechanisms for natural history and comparative effectiveness studies for neuroprognostication.Develop mechanisms to study modifiable barriers to family/team communication that impedes practice of appropriately delayed prognostication and decision-making.Acquire funding for both network infrastructure and individual investigator-initiated studies to advance neuroprognostication in patients with DoC.The deliverables for the neuroprognostication WG include the following:To cure coma, we need to provide effective care for our patients with DoC. Care involves two aspects: (1) caring about a patient, which is the emotional aspect, and (2) caring for a patient, which involves a set of actions or interventions performed to meet the patient’s needs. Caring for the patient is integral to CCC for three main reasons (1) if the comatose patient dies before curative intervention , the possibility of recovery is irrevocably eliminated; (2) identification of variables of care that confound the benefit of clinical intervention (e.g. WOLST within the first few days) can help reduce sample size needed for future studies measuring the effectiveness of the curative interventions; and (3) it is essential to identify interventions that will move the patient toward (benefit) or away (harm) from recovery.The care of coma patients is highly variable. Routine clinical assessment and monitoring are tailored according to the availability of the tools and technology, the culture of the health care setting, clinical expertise, and experience of the health care providers. To date, there are no global standards, even for basic tasks such as examining patients with DoC. Although there are new DoC care guidelines promoting use of advanced DoC biomarkers, these guidelines point more toward timing in the subacute to chronic phase, and have no clear recommendations for the acute phase. In terms of therapeutic intervention, the use of neurostimulants in patients with DoC is also highly inconsistent. We have not yet established the optimum timing for clinical interventions such as tracheostomy, nor have we gained an adequate understanding of optimum frequency and duration of physical, occupational, and cognitive therapy to achieve the best possible recovery. This variability in care leads to heterogeneity in patient outcomes and introduces bias in DoC research.Apart from inconsistency in care, variability is also present in the type of care providers. In day-to-day clinical practice, care of the patients with DoC is provided by multiple caretakers, including physicians, nurses, therapists, pharmacists, social and spiritual services, and family members. For every intervention, it is important to assess behavioral or physiologic cues from the patient to ensure the appropriateness of any given intervention. As an example, although bathing and cleaning is a routine part of clinical care, if the intracranial pressure appears to be on an uptrend in a patient with ABI, it would be reasonable to treat the elevated intracranial pressure before lowering the head of the bed for cleaning. Such judgments regarding optimum timing of intervention based on patient cues have been described as the cue-response theory  and shouAssessment and monitoring: (1) Available assessment tools have substantial variation and often have poor psychometric properties; (2) feasibility, necessity, and ethical considerations of advanced monitoring  have not been well studied; (3) there is a need to differentiate and delineate routine vs. advanced monitoring and understand the impact of these tools on patients outcomes; (4) objective assessments should replace subjective assessments to decrease variations; and (5) Patients and family experience should be integrated into assessment tools across care settings and through transitions of care.Timing of intervention: (1) We need to identify optimal timepoints for routine care interventions ; (2) we need to assess the effectiveness of time points for interventions across various DoC etiologies ; and (3) we need to establish the optimum duration of routine care interventions.Expertise and experience: We need to identify expertise and interdisciplinary team needed across care settings for specific bedside assessments and interventions to avoid variability in care. This may be achieved by determining desired training/certification of designated experts for specific assessments and interventions throughout the care continuum.Technology: (1) we need to determine the clinical utility of modern technology and their impact on patient outcomes; (2) we need to identify optimal mechanisms to implement useful and helpful innovations across care settings feasibly and effectively; (3) we need to determine the cost–benefit ratio of care technologies and determine the impact on patient and health system outcomes; and (4) we need to determine the limitations and benefits of technological advances including AI-based tools, data visualization tools, automated emergency alerts, adapted gaming for therapeutic and educational purposes and the feasibility of nontraditional data types.Religion and culture: (1) We need to understand and incorporate family views regarding faith and spirituality in the healing process; (2) we need to be cognizant of religious and cultural norms surrounding WOLST; (3) we need to establish and evaluate models of care delivery that integrate family into all decisions throughout the continuum of care; (4) we need to consider legal aspects of WOLST including cultural/ethical/religious preferences, family and patient values and beliefs, use of surrogate decision-makers; and (5) we need to consider treatment bias related to spirituality or religion of clinicians as well as access to religious advisors in the care setting .External and regulatory factors: (1) We need to consider the impact of regulatory requirements and guidelines on local resource allocation and outcomes throughout the continuum of care; (2) we need to minimize variability in care, (3) we need to move toward a centers of excellence that provides expertise and recommendations throughout the continuum of care; (4) we need to determine the positive vs. negative impact of program certification on outcomes as well as the resource strains and burden on participating organizations; and (5) we need to determine potential benchmarks and quality indicators specific to the care of patients with DoC across treatment settings.The WG has identified six main domains impacting care based on the observed gaps. Broadly, these domains include the patient level, provider level, and system-level factors that interface with each other and influence the patient’s care. Existing gaps along these six domains include the following:To establish validated and objective measures for the diagnosis of DoC that is consistent across patient populations, disciplines, treatment, and resource settings and measured at a predefined interval from index event.To establish global incidence, prevalence, and etiology of coma, the natural history of disease progression, and impact of current practices on acute post/acute outcomes and resource allocationTo standardize coma assessment battery throughout the continuum of care to provide consistent approach to clinical examination, indicators for advanced imaging, and better accuracy and consistency of prognostic models across settings and populations.Identify the current degree of variations in practice and impact on patient acute and postacute outcomes.Establish new best practices, reinforce existing practices, and eliminate ineffective practices and timing for assessment, monitoring, treatment, and care transitions.Minimize practice variations to ensure consistent and effective evidence-based coma care across resource settings.Routine integration and examination of consciousness-promoting therapies in acute care using pragmatic trial designs.Implementation science to identify optimal strategies for integrating identified best practices into routine clinical care globally.Availability of resources and costs associated with long-term coma and DoC management for patients and families.These six domains are interconnected within the clinical implementation, public health, and clinical research aspects. Addressing the domains through scientific innovation and discovery will inform the appropriate clinical intervention to improve the care of patients with DoC. The WG proposed nine overarching research priorities based on the identified gaps:The WG emphasized the need for a pragmatic approach to advance care of the patients with DoC with the appropriate understanding of global disparities in care and regional cultures and practice preferences. The group highlighted the need for close communication and collaboration between preclinical and clinical research teams to create a highly functional and cohesive research group. Data repositories should include current clinical practices across DoC etiology and across the spectrum of care so future research can appropriately account for these variations while actively standardizing practice where possible.The care of the coma patients is the center of the CCC mission as, without proper care, there is no cure. The panel members discussed that many existing interventions and treatments for DoC are currently based on common or best practice standards that lack strong evidence for generalized application, especially in the pediatric population. This has led to heterogeneity in care, which needs to be recognized and promptly addressed using education, research, and implementation of evidence-based practices. Variability in practice makes it difficult to test the efficacy of any intervention that might be helpful in curing coma, therefore, standardized approaches increase our chances of finding a cure. The panel also highlighted the need for widening the search for funding sources to support the interdisciplinary research teams that focus on the various needs of the multidisciplinary care teams working with patients with DoC.The panel expressed that while working toward reducing variability and optimizing care of the patients with DoC, several factors at the patient, clinician, and system level should be considered. For example, while advocating for standardized practices regarding WOLST decisions, we need to consider patient and families’ culture and values, prognostic humility, ethical considerations for clinicians, and resource needs at the system level, including facility cost of long-term care for patients with DoC. Extracting natural history data from countries and regions that are culturally supportive of prolongation of life-sustaining therapies may be one approach for obtaining such data. In terms of standardization and protocolization, the cost/benefit ratio of new and additional regulatory oversight implementation should be considered. Additionally, the CCC should seek ways to work within cultures that support the individual clinician’s ability to critically evaluate decisions of care, as strict regulations and protocols that demand compliance over clinical judgment can often be obstructive. It is also important to heed the needs of the clinical team that cares for patients with DoC. One such need is to develop ways for streamlined communication between multidisciplinary care teams with the ability to freely discuss and integrate care decisions.In terms of integration of novel tools and innovation, the panel expressed the need to understand the limitations of such tools. For AI-based tools, it is very important to understand the models on which the tool was tested and validated as the dictum “garbage-in-garbage-out” holds true, especially in in silico models that cannot capture the variables and confounders in a real clinical setting. A model complex enough to identify which changes are significant and how they affect the patients does not yet exist. Large volume of prospective data with models including overt and covert clinical variables pertaining to routine clinical care are needed to improve the reliability of AI in critical care settings. Although care of the coma patients includes optimization and standardization of sophisticated measures such as electrophysiological, biophysical, and other biomarkers as well as innovation such as AI, approaching the low hanging fruits such as standardization of basic approach for evaluation of comatose patients can be impactful. In the current clinical setting, simple care aspects such as the variability in the basic assessment of the comatose patient  can be significantly limiting in measuring impact of our clinical interventions. Furthermore, the panel highlighted that care of the coma patients is complex, and one-size-fits-all model is inadequate given the multiple factors specific to each clinical scenario, including variation in care teams based on pathology. However, despite this heterogeneity, identifying common grounds is possible on some of the key factors, and efforts should be focused on improving and standardizing common aspects of assessment, monitoring, and therapy.Identify variations in care and related impact on outcomes across resource settings and populations.Identify existing and establish new evidence-based best practices to minimize variations in assessment, timing, monitoring, technologies, and treatments for coma care.Identify optimal strategies using an implementations science approach to integrate established best practices in clinical settings.Create models of care that integrate family engagement and decisions making throughout the lifespan.The deliverables for the care of the coma patients WG include the following:Preceding the discussion related to early clinical trials, cortical effects of anesthetics were reviewed. General anesthesia (GA) leads to a drug-induced, reversible state that consists of antinociception , unconsciousness, amnesia, akinesia , and maintenance of physiological stability . NumerouThe mechanisms through which anesthetics produce their neurophysiological responses in cortical, thalamic, and brainstem circuits differ by drug class, patient’s age, and physiological state. Slow delta oscillations are also noted to be predominant in very young (0–3 months old)  and veryTo cure coma, we need a multifaceted approach. Ideally, we need (1) the ability to map human brain networks that are essential for consciousness and allow for repeated bedside assessments in the acute phase; (2) new tools to identify preserved brain network connections that allow personalized connectome mapping; (3) to develop point-of-care fluid biomarkers to identify patients who may benefit from therapy and have valid metrics for assessment of treatment response; (4) to develop targeted treatments personalized to patients; and (5) to ensure long-term follow-up.One of the main goals of the CCC is to determine how early interventions may offer novel opportunities for consciousness recovery through clinical trials of consciousness-promoting therapies. Patients with DoC are often overlooked in clinical trials, especially in the acute phase of the disease. Early interventions could offer immense opportunities for consciousness recovery. Development of such early consciousness-promoting therapies in the ICU could (1) prevent premature WOLST; (2) facilitate recovery of consciousness; (3) decrease ICU-related complications; (4) improve opportunities for rehabilitation; and (5) minimize long-term disability.Develop trials based on defined patient phenotypes and endotypes.Develop adaptive, exploratory interventional trials to identify interventions that support the recovery of consciousness.Develop simple master protocols to achieve these deliverables andImplement findings into routine clinical care.As part of the CCC mission, the early clinical trials WG is charged with developing proof-of-concept clinical trials that improve the accuracy of prognostication as well as treatment strategies that promote recovery of consciousness throughout the continuum of DoC care. The overarching goal of the WG is to:To navigate these aspects, there is a need to develop innovative ways to categorize various types of DoC to accurately monitor treatment response . AdoptioThe CCC Coma Epidemiology, Evaluation, and Therapy  survey rWhich patients are likely to respond to treatment?Which trial designs are most efficient?Which outcome measures have the best sensitivity and specificity?Which is the best approach to control for variability of care?Efforts across the CCC have created opportunities to bridge siloed efforts and leverage the expertise of diverse groups spanning the continuum of care to provide a big picture of consciousness research. Regardless, the charge is complex with no precedent to follow and has numerous roadblocks to overcome. To start, we need to address some basic questions related to early clinical trial in DoC such as:Set expectations for future trials (define what good research looks like).Assess current variabilities in care and trial resources across collaborating sites.Develop proxy biomarkers that allow for trials with small patient numbers to inform larger trials on timing of treatment and promising strategies. Additionally, develop a consensus on the specific clinical measures (GCS vs. CRS-R), imaging tools, blood/CSF biomarkers, electrophysiology and the pharmacodynamics.Define end points, ways to assess them, and identify the best performing measures. For example, should the trials use traditional Glasgow Outcome Scale-Extended (GOSE) versus functional measures? What is the appropriate timing of measurement? Should the outcomes be measured short term or long term? Regardless of the outcome measure selected, it should be feasible and patient/family-centric.Determining best infrastructure and designs for trials.Enrich samples based on similarities among patients.Based on the gaps, the WG proposed six research priorities:The panel discussed that sample enrichment with proper sample selection is important to ensure success of the clinical trials . EnricheTo begin, we first need to identify key site investigators across the CCC research network, and work on the logistics of interventional fidelity as we move forward with adaptive trials. However, the panel reemphasized that given the need for long-term follow-up to assess DoC outcomes, identification and validation of early biomarkers to evaluate treatment response and early prognostic markers would help determine go/no go decisions, especially for high-fidelity adaptive trial designs. Rather than a sequential approach, parallel but noncompeting studies with slightly different inclusion criteria for DoC should also be considered to lessen the screening burden on the local sites. One of the biggest gaps impeding design of supervised ML models or adaptive trial designs is our limited understanding , 83 of tUnderstanding the breadth of heterogeneity in care.Developing intermediate endpoints using surrogate measures such as biomarkers.Identifying optimal patient and family centered outcomes.Tiered approach or program of research using various study designs.The deliverables for the early clinical trial WG include the following:Level 1: Global point-prevalence/prospective cohort study  and identify biomarkers and surrogate endpoints.Years 3–5: Implementation Phase: Initiation of clinical trials.The WG also outlined a 5-year roadmap for early clinical trials:According to Confucius, “study the past if you would divine the future.” In order to understand the LTR potential, we must study those who have demonstrated what is possible. Taking this long-view provides a perspective from which to study LTR and (1) define prognostic endpoints; (2) understand personal or environmental factors that influence good long-term recovery; (3) understand and implement interventions that support and optimize long-term recovery; and (4) understand health care disparities.Substantial recovery over long periods of time is possible for a sizable group of individuals with prolonged DoC.Individuals with TBI tend to fare better than non-TBI (nTBI) with respect to DoC. Improvements over a 10-year period have been reported in TBI, with > 25% living without in-home support and are able to work in a competitive work environment. In addition, there are known improvements documented over 2-year period in patients with nontraumatic causes of DoC .Comorbidities and secondary conditions make recovery course nonlinear and heterogeneous from a statistical perspective.There are very limited studies in children, but studies have documented recovery up to 2 years post-injury.Most DoC studies are derived from inpatient rehabilitation cohorts, that represent minority of DoC population who could benefit from this type of rehabilitation care, yet they do not receive this specialized care .The current state of LTR research can be summarized in the following points:Some recent work within the TBI Model Systems network can serve as an exemplar for LTR studies. The TBI Model System has the infrastructure to follow thousands of survivors over the lifetime to observe the natural history of the disease. In one such study, the investigators looked at 2058 patients with TBI and DoC at the time of rehabilitation admission and found that 82% recovered consciousness during acute inpatient rehabilitation and 40% became partially or fully independent . AbsenceAn increase in knowledge base about recovery trajectories in the absence of limitations to care . Such knowledge is important to:Generate scientific evidence that supports guidelines for WOLST.Identify and communicate key elements and processes around uncertainty with DoC recovery.Development of more accurate and flexible modeling of recovery trajectory using advanced statistical methods, widely adopted and implemented CDEs, and patient-centered outcomes.Utilization of data sets that track patient data across the continuum of care using patient-centered outcomes that can be integrated into clinical practice and workflow.Enhanced understanding of biomarkers and mechanisms affecting LTR course.Integrated research/health care delivery systems that translate novel research treatments and technologies into practice and facilitate access to DoC care programs across the recovery continuum.The WG identified several key steps to address the many existing gaps on DoC LTR research :An increRehabilitation is a foundational component of studying and optimizing LTR trajectory. The NIH 5-year research plan on rehabilitation developed in 2016 outlines priorities in multiple areas of rehabilitation medicine and research that can benefit individuals with temporary or chronic limitations in function . This prRehabilitation across the lifespan: Strategies to promote rehabilitation across the lifespan include: (1) identification of preexisting LTR cohorts and using them to understand the impact of early withdrawal of life supporting therapy (WOLST) as well as to develop communication strategies for conveying prognostic uncertainly regarding natural course of DoC; (2) utilization of CCC LTR experts and existing CCC sites for biomarkers studies using CDEs specifically designed to capture the LTR perspective; (3) application of DoC-specific CDEs across the disease continuum at all consortium sites and promoting pragmatic follow-up batteries utilizing novel technology such as telemedicine and wearable devices; (4) identification of appropriate LTR assessment tools with consideration for metrics sensitive to technologies and treatments; (5) identification of appropriate timing across the course of recovery for operationalizing and implementing specific rehabilitation strategies. For example, integrating physiatry in post-acute phase to manage specific issues such as delirium, spasticity, dysautonomia, etc. and early neurostimulation as standard of care in the acute post-injury period; and (6) integration of variables related to social determinants of health  to evaluate their impact on LTR.Longitudinal studies to assess recovery trajectories: We need to evaluate prognostic accuracy for LTR as premature WOLST is quite prevalent. Development of prediction models would be helpful to guide clinical decisions. Inclusion of physiatry colleagues in LTR research is critical. Several existing databases and networks for adult recovery-based research on various DoC etiologies such as TBI –92, CA –95, and Utilization of existing databases and networks for pediatric/Neonatal recovery-based research: Similar to the adult registries, leveraging existing pediatric and neonatal databases , 97 and Technology development and use: Important considerations for technology development include age and stage of development; brain health, secondary conditions, and comorbidities, environmental milieu including barriers to use, health disparities, infrastructure and access, utility, cultural acceptability, average caregiver’s ability to utilize the product as well as family/caregiver education and the availability of economic resources for repair and maintenance. As for prioritization of technology, since portability is extremely important to patients and caregivers, innovation related to motor assistance with focus on ergonomics is crucial. Similarly, regaining fine motor movements that facilitate integration into the community and work environment equates to economic independence for adults and meeting educational expectations for pediatric patients. Hence technology focused on improving mechanical precisions using technology such as the virtual reality should be considered. Cognitive training is equally important with the development of age and stage-appropriate content for adequate cognitive rehab. Additionally, augmented communication tools using brain-computer interface can significantly enhance quality of life of patients and caregivers and should also be prioritized. As new innovative tools continue to develop, equality in access to care should be a key consideration to ensure that these initiatives do not expand the existing gap in health care disparity . The WG Translational Science: The panel noted that the next area of research prioritization is biomarkers of LTR for determination of prognostic trajectories. Investigators should strive to characterize longitudinal profiles as the initial step toward population stratification in assessing treatment response and prognosis across age groups and recovery continuum, with the understanding that recovery is not a linear process. Biomarkers that capture systemic response to neurological insult  should be considered. Markers that capture both adaptive and maladaptive responses associated with repair and recovery are important, such as the structural plasticity , functional plasticity  and maladaptive plasticity . Further, it is important to account for personal biology, etiology of DoC and complications as that can have major impact on LTR. Biomarkers focusing on secondary conditions after brain injury  should also be considered. Finally, there should be appropriate stratification and power calculation to capture racial differences in biomarker functionality, profile, and utility.These rehabilitation research priorities of NIH  align wi6.Models of DoC care. Models of DoC should follow a continuous care pathway supported by best evidence with embedded data collection that informs current care while also contributing to research and future care. As a guidance for creation of such a model, the CCC can study the chronic care model that leverages the interplay of health systems  and the community in which one lives  to achieve the best outcome possible by incorporating various components of these two integral systems  to proviThe three main components for LTR biomarker research include: (1) neuroimaging for detection of covert cognition (event related-fMRI), functional integrity of consciousness (resting state-fMRI), metabolic evaluation (Positron emission tomography/PET) and monitoring of secondary brain damage (Diffusion Tensor-MRI); (2) neurophysiology for monitoring of paroxysmal activity (EEG), restructuring of sleep stages (polysomnography), integrity of the sensory paths and late potentials ; and (3) wet biomarkers for chronic inflammation, cell migration, hormones and neurotrophin markers, CNS exosomal markers as well as genetics and epigenetics. Biomarker discovery requires a phased approach with (1) designing data-driven models to learn from the existing databases of patients with DoC using big data and ML technology; (2) identification of potential new biomarkers and strategies to harness data-driven evidence to guide rehabilitation; and (3) developing a consensus for the routine use of the most informative long-term biomarkers.In summary, we need to develop valid and effective value-based care paradigms to, improve quality of care, increase access to care, prevent costly complications, detect changes in trajectories that require modifications of care, develop mechanisms to collect data, share data and have communication mechanisms in place to deliver collaborative care. Such a model would then allow us to provide the care that could help improve outcomes in patients with DoC.The panel discussed that we currently lack meaningful data on patients with DoC from vulnerable populations with regards to age, gender, and ethnicity. There is a need to focus on a large-scale population study that includes vulnerable populations to adequately represent these groups into the data sets with derivation of relevant outcome measures.The panel agreed that various LTR priorities align with NIH priorities along the domains of longitudinal studies, translational biomarkers, integration of technology and models of multidisciplinary integrative care. Although DoC affects millions of patients worldwide and is a major source of morbidity and mortality with high economic impact, adequate funding is lacking in this field of research. Panel agreed that with appropriate funding, CCC is well-suited to spearhead this mission to not only leverage existing infrastructure such as the NCRC, global collaborative networks and Neurocritical Care Foundation, but also to develop a central platform for a wide group of clinicians, scientists and other stakeholders to synergistically work toward a cure for coma.Development of multidisciplinary integrative care modelModeling long-term trajectories across the life spanIncorporating technology to optimize LTRIncorporating biomarkers to assess LTRThe deliverables of the LTR WG include the following:To achieve this, the WG proposed a phased approach starting with measures to first, (1) help Define DoC cohort; (2) define data requirement for LTR research; and (3) establish and implement care standards. The second phase would focus on (1) strategies to establish methods to access data in real-time from multiple sources and (2) determine the key data points that can best inform care. In the third phase, the WG suggested implementing clinical cohort studies involving multisite DoC network.Care of the comatose patient:Accurate diagnosis and differentiation between states of consciousness which has implications for prognostication including discharge decisions.Age-based considerations.Allocation of resources with respect to management of patients with DoC with consideration of patients without DoC.Continuity along the spectrum of care from hospital admission to rehabilitation and finally home/community.Decision-making about withdrawing or withholding life-sustaining therapies.Ethics of diagnostic modalities in terms of availability and allocation.Experimental/translational interventions.Practice variation.Prognostication.Avoid self-fulfilling prophecy or nihilism versus medical futility.Family of the comatose patients:Family support through the continuum of care.Appropriate communication in the ICU.Decision-making about goals of care including issues related to advanced care planning  and identification of surrogate decision maker.Smooth process of care transitions.Burden of care for family.Clinical research about comaBalance the risks and benefits for patients and family members.Informed consent practices.Equitable recruitment.Standardizing protocols for detection of consciousness.Management of data from comatose patientsSafety, efficacy, and subject selection for investigational drugs and devices.Disclosure of results to family and medical team.Sharing research results.Protection, privacy, and confidentiality of neural data from data mining and discrimination of patients.Transparency to families and medical team.Data sharing.Implementation/innovation for comatose patientsDistinction between clinical care and research.Distinction between clinical and research data.Determination of when data can and should be used for actionable diagnosis or prognosis.Feasibility of various clinical research technologies.Translating research into practice.Equity for comatose patientsAllocation of detection of consciousness, hospital, rehabilitation, and homecare resources.Additional considerations such as cultural, international, religious, and social.Public engagement and perceptionsEncourage public education.Overcome historical biases and nihilism in the broad medical community and public.Share results with the broad medical community, media, and the public.In response to the large number of ethical considerations raised at the first CCC symposium in September 2020, the Campaign convened the Ethics Module Group. The pillars of biomedical ethics consist of representation of patients who are unable to represent themselves by (1) respecting the patient’s autonomy, (2) using beneficence in all aspects of care, (3) providing nonmaleficent care, and (4) considering justice in all decisions. Relatedly, the Belmont Report recommends all research to include respect for persons, beneficence, and justice. The primary ethical concern for patients in coma is their loss of capacity related to decision-making including matters of clinical care and research. As a community involved in the care of the vulnerable population, we all need to work toward identifying and addressing existing ethical conflicts related to patients with DoC as well as proactively anticipate and mitigate potential future ethical conflicts central to the provision of care and the advancement of research . To achiAs a global research platform, the CCC community should adopt above ethical considerations as guiding principles for DoC research.The CCC has achieved great progress since its announcement in October 2019 at the 17th NCS annual meeting. Many field leaders and NCS members across various workgroups and models are actively involved in propelling this colossal mission while remaining inclusive (moon shot culture), adaptable (learn as we go) and available . The highly engaging discussions over the 3-day NINDS-funded symposium have elucidated the high degree of overlap across the research spectrum that can only be accomplished with collaborative and synergistic workflow.(I)Major barriers that have prevented a cure for coma•Absence of clearly defined problems.•Inability to accurately identify the type and locations of the defects.•Unavailability of reliable diagnostic tools.•Division into separate disease categories .•Pervasiveness of silo mentality some of which is dependent on how the work force is incentivized.•Exclusive rather than all-inclusive teams.•Shortage/Lack of appropriate funding.(II)Existing needs to find a cure for comaThe main discussions that took place during the 3-day symposium can be synthesized into three main points: (1) major barriers that have prevented a cure for coma; (2) existing needs to find a cure for coma; and (3) main priorities of the CCC to move its mission forward.Infrastructure: Includes database, clinical trial standards, CDEs and strategic collaboration.Basic research for cure: Includes understanding of the biology of coma, development of biomarkers for diagnosis and prognostication, preclinical model/animal studies and prospective studies.Care of the coma patient: This includes understanding of effectiveness and timing of current routine tests, treatments and interventions, evidence-based approach to reduce practice variability, research related to prognostication and LTR.The main research needs for curing coma can be broadly categorized into three main components:An insight into what has prevented a cure for coma.Determination of the scope of research needed.Understanding of the currently available tools and capabilities.Identification of new tools and technologies needed to cure coma.Estimation of resources  required to cure coma.Elimination of major barriers that hinder our ability to cure coma.Risk assessment as well as the development of mitigation strategies.Development of action plan with milestones.(III)Main priorities of the CCCA.Capitalize on existing data sets.Prospective multicenter interdisciplinary studies to define the science of caring for patients with DoC that creates the optimal context in which recovery can occur.Develop CDEs/common language.Analysis and communication of best practices.Improve patient care based on what we know and can do today to raise the standard of care and improve outcomes. This involves:B.Leverage existing biomarkers and combine them in novel ways.Develop new biomarkers.Progress from clinical phenotypes to endotypes for evaluation of dynamic pathobiological changes over time.Validate with large-scale, multicenter studies.Understand coma at the neuronal level and defining endotypes to understand the nature and location of the defect and its potential outcome trajectory. For this we need to:C.ElectromagneticMechanicalSensoryChemicalRegenerativeDevelop individualized targeted treatments based on endotypes to repair or retrain brain circuits. This can be achieved by means of various approaches, including:D.New tools and models for prognostication to better define the factors that predict outcomes.Ability to detect cognitive motor dissociation.Decision support for WOLST.Establishment of programs of excellence .Establish prognostication tools with ethical considerations to eliminate nihilism, reduce errors in WOLST and develop objective and empathetic communication strategies with families and surrogates. For this we need:E.Patients enrollment based on physiologic and anatomic response to targeted therapiesExecution of novel early-phase clinical trials to refine outcome endpoints, and surrogate neuroimaging and biomarkers to improve classification of patients with coma and DoC for future design of larger clinical trialsDevelopment of large-scale, randomized, controlled trialsUtilization of existing tools while focusing on development of new tools, CDEs and biomarkers for standardization.Establishment of standards for DoC trials and implementation of these standards to conduct trials aimed at closing current gaps in DoC knowledge. This approach will help foster consistency in data collection and optimize data analysis. Some strategies to reduce research heterogeneity include,F.Develop and implement a database that includes clinical, imaging, electrophysiological, chemical, epigenetic and other data. This will create a central repository of relevant DoC data for research collaborations and eventually the development of algorithms for real-time development of decision support tools at the bedside,G.Insist and ensure that every trial, technical thrust and research effort is transparent, is complementary and builds upon all the other efforts. This approach will help eliminate silos and reduce redundancy and waste.H.Establish an effective new approach for DoC. This involves the development of new model for central data and management center. One approach could be “research focus specific” where 3–5 centers would collaborate to achieve goals specific to each working group with defined milestones within a 5-year funding cycle. In this model, about 30 centers would participate to propel the CCC mission in parallel while remaining highly engaged and communicative where results of one group would inform the study design of the other group within the CCC collaborative. In this model, the CCC collaborative would undergo quarterly reviews of performance and outcomes and an annual review by an advisory board while ensuring collaboration and lack of redundancy. The collaboration would remain adaptive with the addition of new centers as needed and elimination of underperforming centers. Such a model could allow lifetime follow-up of all enrolled participants across the research domains.Other needs to ensure the success of this mission include:Database development: 2 millionBiology and new biomarker development: 15 millionProspective studies: 10 millionClinical trials for treatment evaluations: 13 millionPatient care protocol development: 10 millionPrognostication and ethics: 10 millionThe CCC executive committee has estimated a total budget of US $60 million (about 12 million per year) to accomplish these goals. Estimates related to various priority areas include:Over the past 10 years, about 24.3 million (average of 2.4 million/year) NIH dollars have already been invested in DoC research with a total of 68 awardees, only 6 of which are active awards . MeanwhiThe Curing Coma community has made significant progress since its inception. Now is the time to collate efforts not only to improve the understanding of mechanistic underpinnings of coma, but also to find ways to translate scientific discovery into clinical practice. It is crucial to bridge siloed independent efforts globally with a communicative, collaborative and synergistic strategy from multidisciplinary clinical and research teams across the continuum of coma care. To facilitate this collaborative approach, a centralized platform is urgently needed to bring together clinicians, scientists, patients, and families for a common mission of improving care of the comatose patients. Establishment of such a platform with clear vision and defined milestones is the natural next step. This platform would be critical not only in educating and galvanizing the stakeholders and creating the global standards of coma care but also in improving the outcomes of patients with disordered consciousness.Supplementary file1 (DOCX 44 kb)Below is the link to the electronic supplementary material.


Traumatic brain injury (TBI) is a highly complex phenomenon involving a cascade of disruptions across biomechanical, neurochemical, neurological, cognitive, emotional, and social systems. Researchers and clinicians urgently need a rigorous conceptualization of brain injury that encompasses nonlinear and mutually causal relations among the factors involved, as well as sources of individual variation in recovery trajectories. System dynamics, an approach from systems science, has been used for decades in fields such as management and ecology to model nonlinear feedback dynamics in complex systems. In this mini-review, we summarize some recent uses of this approach to better understand acute injury mechanisms, recovery dynamics, and care delivery for TBI. We conclude that diagram-based approaches like causal-loop diagramming have the potential to support the development of a shared paradigm of TBI that incorporates social support aspects of recovery. When developed using adequate data from large-scale studies, simulation modeling presents opportunities for improving individualized treatment and care delivery. Worldwide, sixty-nine million people sustain traumatic brain injury (TBI) annually . ExperieTBI has been identified as the “most complex disease in the most complex organ” of the body, , spanninResearchers and clinicians urgently need a rigorous conceptualization of brain injury that encompasses nonlinear and mutually causal relations among the factors involved, as well as sources of individual variation in recovery trajectories. The fundamental necessity of this type of systems approach has been advocated by medical and scientific research experts for nearly 30 years. The National Center for Medical Rehabilitation Research (NCMRR) published a research plan that rejected the traditional linear view of rehabilitation and encouraged the adoption of a systems approach as “an essential feature of medical rehabilitation research and, ultimately, all health care delivery” (1993). Unfortunately, this mandate has not been accomplished, and recent TBI research continues the call for a systems perspective .System dynamics, an approach from complex systems science , involveTo locate studies using system dynamics modeling for TBI research, we searched Google Scholar and PubMed using relevant terms. We focused on articles published in the past 15 years that used system dynamics modeling  in some aspect of TBI pathophysiology, diagnosis, prognosis, treatment, recovery, or care delivery. Because much of this research is emerging, we included conference publications. Articles were not vetted for quality due to the small number of studies identified and the descriptive nature of this brief review.Ten publications were identified that fit the search criteria. Included studies span a variety of fields, approaches, and research questions. Some studies used system dynamics to model specific pathophysiological mechanisms, such as intracranial pressure (ICP) and inflammation. Because system dynamics modeling involves accumulations and flows, it is especially well suited for modeling ICP. Although the properties of brain regions can differ significantly, treating volumes and pressures in an aggregate fashion is appropriate due to the rigid volume constraint of the intracranial cavity.Early researchers used electrical circuit analogs and their associated ODEs to study elevated ICP resulting from hematoma and brain swelling during the acute post-injury phase of TBI (Marmarou 1973 and Ursino 1988). The mathematics of system dynamics is identical to these electrical analogs and has the advantage of a diagrammatic visualization that is more comprehensible for most clinicians than electrical circuit diagrams. To describe the complex dynamics of recovery across multiple levels, members of the current author team previously developed a conceptual systems framework for studying concussion , followeA computational model based upon the basic causal structure of the causal-loop diagram discussed above was able to generate estimated recovery trajectories for all severities of TBI given different inputs . Due to Even when evidence-based guidelines for TBI exist, implementation of guidelines in clinical practice remains limited and challenging . Yet sysDynamic systems models of patient and clinical workflows over time thus provide strategies that may be singularly suited for implementing care guidelines consistently in multiple complex medical environments. Systems modeling techniques have also demonstrated utility for predicting what resources for clinical care may be needed in the future. For example, To address the need for complexity-informed approaches for understanding TBI injury and recovery, system dynamics has been used in recent years to model isolated mechanisms, complex relationships between factors in recovery, and aspects of care delivery. Approaches range from highly speculative mathematical models to diagram-based and group modeling methods. The scope of these models also varies widely, from specific mechanisms to a comprehensive understanding of the broad spectrum of processes involved in recovery. These differences reflect the range of capabilities of system dynamics modeling more broadly .a priori determination of hypothesized causal relationships between variables in a system. This determination can be closely tied to prior scientific literature or other sources (in silico experimentation to preliminarily test hypotheses when direct experimentation is impractical or unethical (A defining characteristic of system dynamics modeling is that it is mechanistic, meaning that it involves  sources  co-creat sources , or made sources , dependi sources . System nethical . These aSystem dynamics, as with any operational modeling, is time consuming and requires specialized training . SimulatOf the range of applications detailed in this mini-review, the use of causal-loop diagramming to integrate findings from different knowledge and information sources is perhaps the most unique contribution. Causal-loop diagrams can be particularly relevant to understanding the counterintuitive outcomes often observed among survivors of TBI, after controlling for objective variables such as severity of injury . For exaFuture TBI research could benefit from group model building to engage survivors, family and caregivers, and other stakeholders in the process of visualizing the recovery process from the “as-lived” perspective . From th