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See detailNeural responses to heartbeats detect residual signs of consciousness during resting state in post-comatose patients
Candia-Rivera, D; Annen, Jitka ULiege; Gosseries, Olivia ULiege et al

in Journal of Neuroscience (in press)

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See detailConsciousness and communication BCIs in severe brain-injured patients
Annen, Jitka ULiege; Laureys, Steven ULiege; Gosseries, Olivia ULiege

in Handbook Brain-Computer Interfacing: Neural Devices for paralysis in neurological practise and beyond (in press)

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See detailPreservation of brain activity in unresponsive patients identifies MCS star
Thibaut, Aurore ULiege; Panda, Rajanikant ULiege; Annen, Jitka ULiege et al

in Annals of Neurology (2021)

Objectives: Brain-injured patients who are unresponsive at the bedside (i.e., vegetative state/unresponsive wakefulness syndrome – VS/UWS) may present brain activity similar to patients in minimally ... [more ▼]

Objectives: Brain-injured patients who are unresponsive at the bedside (i.e., vegetative state/unresponsive wakefulness syndrome – VS/UWS) may present brain activity similar to patients in minimally conscious state (MCS). This peculiar condition has been termed “nonbehavioural MCS” or “MCS*”. In the present study we aimed to investigate the proportion and underlying brain characteristics of patients in MCS*. Methods: Brain 18F-fluorodeoxyglucose Positron Emission Tomography (FDG-PET) was acquired on 135 brain-injured patients diagnosed in prolonged VS/UWS (n=48) or MCS (n=87). From an existing database, relative metabolic preservation in the fronto-parietal network (measured with standardized uptake value) was visually inspected by 3 experts. Patients with hypometabolism of the fronto-parietal network were labelled “VS/UWS”, while its (partial) preservation either confirmed the behavioural diagnosis of “MCS” or, in absence of behavioural signs of consciousness, suggested a diagnosis of “MCS*”. Clinical outcome at 1-year follow-up, functional connectivity, grey matter atrophy, and regional brain metabolic patterns were investigated in the three groups (VS/UWS, MCS* and MCS). Results: 67% of behavioural VS/UWS presented a partial preservation of brain metabolism (i.e., MCS*). Compared to VS/UWS patients, MCS* patients demonstrated a better outcome, global functional connectivity and grey matter preservation more compatible with the diagnosis of MCS. MCS* patients presented lower brain metabolism mostly in the posterior regions compared to MCS patients. Interpretation: MCS* is a frequent phenomenon that is associated with better outcome and better brain preservation than the diagnosis of VS/UWS. Complementary exams should be provided to all unresponsive patients before taking medical decisions. [less ▲]

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See detailDecreased evoked slow-activity after tDCS in disorders of consciousness
Mensen, Armand; BODART, Olivier ULiege; Thibaut, Aurore ULiege et al

in Frontiers in Systems Neuroscience (2020), 14(62),

Due to life-saving medical advances, the diagnosis and treatment of disorders of consciousness (DOC) has become a more commonly occurring clinical issue. One recently developed intervention option has ... [more ▼]

Due to life-saving medical advances, the diagnosis and treatment of disorders of consciousness (DOC) has become a more commonly occurring clinical issue. One recently developed intervention option has been non-invasive transcranial direct current stimulation. This dichotomy of patient responders may be better understood by investigating the mechanism behind the transcranial direct current stimulation (tDCS) intervention. The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) has been an important diagnostic tool in DOC patients. We therefore examined the neural response using TMS-EEG both before and after tDCS in seven DOC patients (four diagnosed as in a minimally conscious state and three with unresponsive wakefulness syndrome). tDCS was applied over the dorsolateral prefrontal cortex, while TMS pulses were applied to the premotor cortex. None of the seven patients showed relevant behavioral change after tDCS. We did, however, find that the overall evoked slow activity was reduced following tDCS intervention. We also found a positive correlation between the strength of the slow activity and the amount of high-frequency suppression. However, there was no significant pre-post tDCS difference in high frequencies. In the resting-state EEG, we observed that both the incidence of slow waves and the positive slope of the wave were affected by tDCS. Taken together, these results suggest that the tDCS intervention can reduce the slow-wave activity component of bistability, but this may not directly affect high-frequency activity. We hypothesize that while reduced slow activity may be necessary for the recovery of neural function, especially consciousness, this alone is insufficient. [less ▲]

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See detailIslands of awareness or islands of cortical complexity?
Cecconi, Benedetta; Laureys, Steven ULiege; Annen, Jitka ULiege

in Trends in Neurosciences (2020)

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See detailAuditory and somatosensory p3 are complementary for the assessment of patients with disorders of consciousness
Annen, Jitka ULiege; Mertel, I.; Xu, R. et al

in Brain Sciences (2020), 10(10), 1-14

The evaluation of the level of consciousness in patients with disorders of consciousness (DOC) is primarily based on behavioural assessments. Patients with unresponsive wakefulness syndrome (UWS) do not ... [more ▼]

The evaluation of the level of consciousness in patients with disorders of consciousness (DOC) is primarily based on behavioural assessments. Patients with unresponsive wakefulness syndrome (UWS) do not show any sign of awareness of their environment, while minimally conscious state (MCS) patients show reproducible but fluctuating signs of awareness. Some patients, although with remaining cognitive abilities, are not able to exhibit overt voluntary responses at the bedside and may be misdiagnosed as UWS. Several studies investigated functional neuroimaging and neurophysiology as an additional tool to evaluate the level of consciousness and to detect covert command following in DOC. Most of these studies are based on auditory stimulation, neglecting patients suffering from decreased or absent hearing abilities. In the present study, we aim to assess the response to a P3-based paradigm in 40 patients with DOC and 12 healthy participants using auditory (AEP) and vibrotactile (VTP) stimulation. To this end, an EEG-based brain-computer interface was used at DOC patient’s bedside. We compared the significance of the P3 performance (i.e., the interpretation of significance of the evoked P3 response) as obtained by ‘direct processing’ (i.e., theoretical-based significance threshold) and ‘offline processing’ (i.e., permutation-based single subject level threshold). We evaluated whether the P3 performances were dependent on clinical variables such as diagnosis (UWS and MCS), aetiology and time since injury. Last we tested the dependency of AEP and VTP performances at the single subject level. Direct processing tends to overestimate P3 performance. We did not find any difference in the presence of a P3 performance according to the level of consciousness (UWS vs. MCS) or the aetiology (traumatic vs. non-traumatic brain injury). The performance achieved at the AEP paradigm was independent from what was achieved at the VTP paradigm, indicating that some patients performed better on the AEP task while others performed better on the VTP task. Our results support the importance of using multimodal approaches in the assessment of DOC patients in order to optimise the evaluation of patient’s abilities. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. [less ▲]

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See detailBrain-computer interfaces for consciousness assessment and communication in severely brain-injured patients
Annen, Jitka ULiege; Laureys, Steven ULiege; Gosseries, Olivia ULiege

in Millán, José del R.; Ramsey, Nick F. (Eds.) Handbook of Clinical Neurology. Volume 168: Brain-Computer Interfaces (2020)

Patients with disorders of consciousness (DOC) suffer from awareness deficits. Comorbidities such as motor disabilities or visual problems hamper clinical assessments, which can lead to misdiagnosis of ... [more ▼]

Patients with disorders of consciousness (DOC) suffer from awareness deficits. Comorbidities such as motor disabilities or visual problems hamper clinical assessments, which can lead to misdiagnosis of the level of consciousness and render the patient unable to communicate. Objective measures of consciousness can reduce the risk of misdiagnosis and could enable patients to communicate by voluntarily modulating their brain activity. This chapter gives an overview of the literature regarding brain-computer interface (BCI) research in DOC patients. Different auditory, visual, and motor imagery paradigms are discussed, alongside their corresponding advantages and disadvantages. At this point, the use of BCIs for DOC patients in clinical applications is still preliminary. However, perspectives on the improvements in BCIs for DOC patients seem positive, and implementation during rehabilitation shows promise. © 2020 Elsevier B.V. [less ▲]

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See detailIslands of Awareness or Cortical Complexity?
Cecconi, Benedetta ULiege; LAUREYS, Steven ULiege; Annen, Jitka ULiege

in Trends in Neurosciences (2020)

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See detailPerturbations in dynamical models of whole-brain activity dissociate between the level and stability of consciousness
Sanz Perl; Pallavicini, Carla; Pérez Ipiña, Ignacio et al

E-print/Working paper (2020)

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See detailAutomated Machine Learning-based diagnosis of impaired consciousness: cross-center and protocol generalization of EEG biomarkers.
Raimondo, Federico ULiege; Engemann, Denis; King, Jean-Remi et al

Conference (2019, September 24)

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See detailDiagnostic accuracy of the CRS-R index in patients with disorders of consciousness
Annen, Jitka ULiege; Filippini, Maria Maddalena; Bonin, Estelle ULiege et al

in Brain Injury (2019), 33(11), 1409-1412

Objective: To obtain a CRS-R index suitable for diagnosis of patients with disorders of consciousness (DOC) and compare it to other CRS-R based scores to evaluate its potential for clinics and research ... [more ▼]

Objective: To obtain a CRS-R index suitable for diagnosis of patients with disorders of consciousness (DOC) and compare it to other CRS-R based scores to evaluate its potential for clinics and research. Design: We evaluated the diagnostic accuracy of several CRS-R-based scores in 124 patients with DOC. ROC analysis of the CRS-R total score, the Rasch-based CRS-R score, CRS-R-MS and the CRS-R index evaluated the diagnostic accuracy for patients with the Unresponsive Wakefulness Syndrome (UWS) and Minimally Conscious State (MCS). Correlations were computed between the CRS-R-MS, CRS-R index, the Rasch-based score and the CRS-R total score. Results: Both the CRS-R-MS and CRS-R index ranged from 0 to 100, with a cut-off of 8.315 that perfectly distinguishes between patients with UWS and MCS. The CRS-R total score and Rasch-based score did not provide a cut-off score for patients with UWS and MCS. The proposed CRS-R index correlated with the CRS-R total score, Rasch-based score and the CRS-R-MS. Conclusion: The CRS-R index is reliable to diagnose patients with UWS and MCS and can be used in compliance with the CRS-R scoring guidelines. The obtained index offers the opportunity to improve the interpretation of clinical assessment and can be used in (longitudinal) research protocols. [less ▲]

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See detailBrain functional network segregation and integration in patients with disorders of consciousness
Panda, Rajanikant ULiege; Annen, Jitka ULiege; Gosseries, Olivia ULiege et al

Conference (2019, June 10)

Introduction: The brain regulates information flow by balancing integration and segregation of networks to facilitate flexible cognition and behavior. However, it is unclear how this mechanism manifests ... [more ▼]

Introduction: The brain regulates information flow by balancing integration and segregation of networks to facilitate flexible cognition and behavior. However, it is unclear how this mechanism manifests during loss of consciousness [1-3]. In this study, we studied brain network segregation and integration using resting state functional magnetic resonance imaging (fMRI) data to assess brain networks in patients with disorders of consciousness. Methods: Fifty-four patients with disorders of consciousness (24 unresponsive wakefulness syndrome (UWS) (M:F=16:8; mean age= 45±13), 30 minimally conscious state (MCS) (M:F=23:7; mean age= 36±14) and 30 age- and gender-matched healthy controls underwent fMRI. The resting-state MRI data were acquired during wakefulness with eyes closed using a 3 Tesla MRI scanner. Additionally a T1-weighted, structural imaging was performed for anatomical coregistration. First, the fMRI data were pre-processed for realignment, co-registration, segmentation, normalization, head motion regressed out and 0.01-0.1Hz band pass filtered. Data were then parcellated in 256 brain regions (ROIs) using Shen functional atlas from [4]. The connectivity matrix was computed using Pearson correlation. Graph theory connectivity was carried out to measure brain network topological properties in terms of network segregation and integration by computing binarized undirected connectivity matrix. Normalized clustering coefficients were computed as measures of network segregation while normalized participation coefficients were computed as measures of network integration [3]. Through integrated nodal graph measures, individual networks (such as default mode, frontoparietal, auditory, salience, subcortical and cerebellum networks) were also computed to study which networks were predominantly affected [3]. To enable comparison of network properties across groups, we used sparsity-based threshold (S) to avoid spurious results. To prevent biases associated with a single threshold, we determined a range of sparsity (0.06 ≤ S ≤ 0.5, with an increment of 0.025), which avoids excess network fragmentation at sparser thresholds. The between group differences for global (i.e., whole brain) and individual networks were computed with unpaired t-test with FDR correction for multiple comparison [5-6]. Finally the network segregation and integration mean values were correlated with Coma Recovery Scale-Revised (CRS-R) modified score [7]. Results: Patients in UWS had decreased participation coefficients (network integration) compared to those in MCS (effect size= -0.44, p<0.0001) and controls (effect size= -0.63, p<0.0001). Patients in MCS had significant decreased participation coefficients compared to controls (effect size= -0.37, p<0.001). On the other hand, patients in UWS had significant increased clustering coefficient (network segregation) compared to those in MCS (effect size= 0.39, p= <0.001) and controls (effect size= 0.63, p<0.0001). Patients in MCS had significant increased clustering coefficients compared to controls (effect size= 0.03, p<0.01). This decreased participation coefficient and increased clustering coefficient were noted predominantly observed in the frontoparietal and subcortical networks. Conclusions: Patients with disorders of consciousness present decreased in network integration and increased in network segregation. Notably, fragmentation of network integration is observed in patients in unaware patients (UWS), which indicates impaired information flow in the brain modules, especially in the frontoparietal and subcortical networks. This introduces a potential measure to classify patients with disorders of consciousness, which could ultimately be used for clinical diagnosis. Reference: 1. Fukushima, M., (2018). Structure–function relationships during segregated and integrated network states of human brain functional connectivity. Brain Structure and Function, 223(3), 1091-1106. 2. Deco, G., (2015). Rethinking segregation and integration: contributions of whole-brain modelling. Nature Reviews Neuroscience, 16(7), 430. 3. Keerativittayayut, R., (2018). Large-scale network integration in the human brain tracks temporal uctuations in memory encoding performance. eLife, 7, e32696. 4. Finn, E. S., (2015). Functional connectome ngerprinting: identifying individuals using patterns of brain connectivity. Nature neuroscience, 18(11), 1664. 5. Holla, B., (2017). Disrupted resting brain graph measures in individuals at high risk for alcoholism. Psychiatry Research: Neuroimaging, 265, 54-64. 6. Chennu, S., (2017). Brain networks predict metabolism, diagnosis and prognosis at the bedside in disorders of consciousness. Brain, 140(8), 2120-2132. 7. Demertzi, A., (2015). Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients. Brain, 138(9), 2619-2631. [less ▲]

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See detail2 EEG-based methods for the diagnosis of disorders of consciousness
Sanz, Leandro ULiege; Wolff, Audrey ULiege; Fecchio, Matteo et al

Poster (2019, May 17)

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See detailDiagnostic accuracy of a CRS-R modified score in patients with disorders of consciousness.
Annen, Jitka ULiege; Filippini, Maria Maddalena ULiege; Bonin, Estelle ULiege et al

Conference (2019, March 16)

Introduction The Coma Recovery Scale-Revised (CRS-R) is the gold standard diagnostic tool for assessing patients with disorders of consciousness (DOC) after severe acquired brain injury (Giacino, Kalmar ... [more ▼]

Introduction The Coma Recovery Scale-Revised (CRS-R) is the gold standard diagnostic tool for assessing patients with disorders of consciousness (DOC) after severe acquired brain injury (Giacino, Kalmar and Whyte, 2004; Seel et al., 2010). Differential diagnosis of DOC includes the unresponsive wakefulness syndrome (UWS;(Laureys et al., 2010)), characterized by the recovery of eye-opening but no behavioral evidence of self or environmental awareness, and the minimally conscious state (MCS; (Giacino et al., 2002)) defined by clearly discernible but inconsistent behavioral signs of conscious awareness. The CRS-R assesses reflexes and cognitively mediated behavior in six domains, namely auditory (4 items), visual (5 items), motor (6 items), oromotor (3 items), communication (2 items) and arousal (3 items). Items in every subscale are hierarchically ordered (i.e. reflexive to cognitively-mediated behaviors; higher level behaviors correspond to higher level of neurologic functioning and ability to demonstrate lower-level behaviors or disappearance of pathological behaviors as sign of recovery) and can be used to infer the patient’s level of consciousness (La Porta et al., 2013; Gerrard, Zafonte and Giacino, 2014). Several studies on DOC investigating markers of consciousness, recovery and treatment used the CRS-R total score (i.e. addition of the highest scores reached for each subscale) as regressor in neuroimaging analyses (Bruno et al., 2012; Thibaut et al., 2012; Margetis et al., 2014; Bagnato et al., 2015). However, ignoring the hierarchy of the subscales in the CRS-R total score reduces the sensitivity for the diagnosis of MCS patients (i.e., 100% specificity for UWS but false negative diagnostic error of 22%, with a cut-off CRS-R total score of 10 (Bodien et al., 2016)). In addition, the ordinal nature of the CRS-R total score make it limited to use with parametric statistical tests (e.g., requiring normal distribution). A solution to this problem has been proposed by Sattin and colleagues (2015) who computed a CRS-R modified score (CRS-R MS1), by considering reflexes and cognitively mediated behaviors separately, reliably distinguishing between UWS and MCS patients. These authors also argue that the interpretation of the total CRS-R scores is limited due to “the underlying assumption that if a patient is able to show higher-level behaviors, he/she is also able to show lower-level responses”. Sattin et al. (2015) propose to account for the number of presented responses in every subscale (i.e., every items in a subscale should be assessed and scored). One major drawback to this approach is that according to the CRS-R guidelines, the assessor should start assessing the highest item and move to the next subscale once an item is scored, in line with the hierarchical organization of the scale. This means that, if the CRS-R is performed according to the guidelines (for which the CRS-R has been validated), the CRS-R modified score cannot be calculated. Even if assessing all items might be valid, it is unlikely to be done in many clinical and research settings as it would increase assessment time and fatigue the patient. We here propose to adapt the CRS-R MS1 by considering only the highest score reached on every subscale, respecting the CRS-R guidelines. Methods One-hundred twenty-four patients admitted to the University Hospital of Liège were assessed multiple times with the CRS-R, at least once including the assessment of all items. Patients for whom the CRS-R assessment including all items provided the same diagnosis as the patient’s final diagnosis were selected. The study was approved by the ethics committee of the University Hospital of Liège and the legal guardians of patients gave written informed consent for participation in the study, in accordance with the Declaration of Helsinki. The CRS-R total score and two CRS-R MS were calculated for every patient. The CRS-R MS combines scores for reflexes and cognitive behaviors of every CRS-R subscale which can be used to obtain the CSR-R MS from a transposition matrix. The CRS-R MS1 was calculated as previously described (Sattin et al., 2015), and the CRS-R MS2 only used the highest score in every subscale (i.e., assuming that lower items were successful). Statistics were performed in R (R Core team, 2012). We assessed group differences in age (two sample t-test), time since injury (two sample t-test) and etiology (χ2 test). Receiver Operating Characteristic were calculated to obtain the sensitivity and specificity at several classification thresholds (package pROC (Robin et al., 2011)). We calculated the correlation between the CRSR MS1 and CRSR MS2 using Pearson correlation, and both scores with the CRS-R total score using Spearman correlation. Finally, we used a Kolmogorov-Smirnoff test to evaluate whether CRSR MS1 and CRSR MS2 come from different distributions (i.e., if one approach provides additional information over the other). Results Eighty-five MCS patients (26 females; mean age 40.4 (SD±17.4) years old; 43 traumatic; mean time since injury 2.7 (SD±4.0) years) and 39 UWS patients (14 females; mean age 50.6 (SD±16.5) years old; 29 traumatic; mean time since injury 1.2 (SD±1.8) years) were included in the study. MCS patients were older (t(77.6)-3.15, p<0.002 95%CI[-16.7, -3.7]), were in a more chronic stage (t(121.9)=2.9, p = 0.005, 95%CI[974,427]), and suffered more often from a traumatic brain injury (χ2=6.8, p = 0.01) than UWS patients. The ROC analysis for both MS showed an AUC of 1 (cut-off:8.315, 100% specificity and sensitivity). The ROC analysis for the CRS-R total score showed an AUC of 0.94 (cut-off:9, sensitivity = 100%, specificity = 67%). A correlation was found between the CRSR total score and both the CRSR MS1 (r = 0.94, p < 0.0001, figure 1A) and CRSR MS2 (r = 0.96, p < 0.0001, figure 1B). The two CRS-R MS correlated (r = 0.96, p = 0.0001, figure 1C). CRSR MS1 and CRSR MS2 were drawn from the same distribution (D(124)= 0.13, p = 0.25). Discussion CRSR MS2 correlated strongly with the CRSR MS1, and perfectly discriminated UWS from MCS patients. As for accurate diagnosis the CRS-R should be repeated (preferably five times (Wannez et al., 2018)) short assessments are preferred, and possibly also reduce effects of fatigue. Second, the CRSR MS2 can be calculated with CRS-R assessments performed according to the CRS-R guidelines, facilitating its use in clinical environments, and in research settings where CRSR MS2 can be used pro- and retrospectively for research protocols. Furthermore, the results indicate that the two modified scores share the same distribution. This suggests that assessing all CRS-R items as proposed previously does not significantly contribute to the stratification of patients. The CRSR MS2 code is available via: Github A remaining limitation of the proposed score is that it does not allow to distinguish MCS minus (i.e. showing language independent signs of awareness, like visual pursuit) from MCS plus (i.e. showing language dependent signs of awareness) patients, or emergence from MCS. However, a clear consensus about the diagnostic criteria is needed before an updated modified score can be provided. In conclusion, the current analyses show that the calculation of the CRS-R modified score using the highest item in every subscale is valid for clinical diagnosis, and provides perspective for its use for research. Figure Figure 1. Correlation between the CRS-R total score and the CRS-R MS1 (1A), CRSR MS2 (1B), and between the two modified CRS-R scores (1C). MCS plus patients are here characterized by command following, intelligible verbalization and/or intentional communication. Acknowledgements This project has received funding from the University and University Hospital of Liege, the Belgian National Funds for Scientific Research (FRS-FNRS), the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2) the Luminous project (EU-H2020-fetopenga686764), the Center-TBI project (FP7-HEALTH- 602150), the Public Utility Foundation ‘Université Européenne du Travail’, “Fondazione Europea di Ricerca Biomedica”, the Bial Foundation, the Mind Science Foundation and the European Commission, the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 778234, European Space Agency (ESA) and the Belgian Federal Science Policy Office (BELSPO) for their support in the framework of the PRODEX Programme. CC is a post-doctoral Marie Sklodowska-Curie fellow (H2020-MSCA-IF-2016-ADOC-752686), and SL is research director at FRS-FNRS. We are highly grateful to the members of the Liège Coma Science Group for their assistance in clinical evaluations, and we thank all the patients and their families and the Neurology department of the University hospital of Liège. [less ▲]

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See detailInternational validation of the Phone Outcome Questionnaire for patients with Disorders Of Consciousness
Wolff, Audrey ULiege; Estraneo, Anna; Noé, Quique et al

Poster (2019, March 15)

Assessing the evolution of severely brain-injured patients with disorders of consciousness (DOC) with current tools like the Glasgow Outcome Scale-Extended (GOS-E) remains a challenge. At the bedside, the ... [more ▼]

Assessing the evolution of severely brain-injured patients with disorders of consciousness (DOC) with current tools like the Glasgow Outcome Scale-Extended (GOS-E) remains a challenge. At the bedside, the most reliable diagnostic tool is currently the Coma Recovery Scale-Revised. The CRS-R distinguishes patients with unresponsive wakefulness syndrome (UWS) from patients in minimally conscious state (MCS) and patients who have emerged from MCS (EMCS). This international multi-centric study aims to validate a phone outcome questionnaire (POQ) based on the CRS-R and compare it to the CRS-R performed at the bedside and to the GOS-E which evaluates the level of disability and assigns patient’s in outcomes categories. The POQ will allow clinicians to probe the evolution of patient’s state of consciousness based on caregivers feedback. This research project is part of the International Brain Injury Association, Disorders of Consciousness-Special Interest Group (DOCSIG) and DOCMA consortium. [less ▲]

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