Disorders Of Consciousness Patients Research Articles

Breakdown of effective information flow in disorders of consciousness: Insights from TMS-EEG

BackgroundThe complexity of the neurophysiological mechanisms underlying human consciousness is widely acknowledged, with information processing and flow originating in cortex conceived as a core mechanism of consciousness emergence. Combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is considered as a promising technique to understand the effective information flow associated with consciousness. ObjectivesTo investigate information flow with TMS-EEG and its relationship to different consciousness states. MethodsWe applied an effective information flow analysis by combining time-varying multivariate adaptive autoregressive model and adaptive directed transfer function on TMS-EEG data of frontal, motor and parietal cortex in patients with disorder of consciousness (DOC), including 14 vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients, 21 minimally conscious state (MCS) patients, and 22 healthy subjects. ResultsTMS in DOC patients, particularly VS/UWS, induced a significantly weaker effective information flow compared to healthy subjects. The bidirectional directed information flow was lost in DOC patients with TMS of frontal, motor and parietal cortex. The interactive ROI rate of the information flow network induced by TMS of frontal and parietal cortex was significantly lower in VS/UWS than in MCS. The interactive ROI rate correlated with DOC clinical scales. ConclusionsTMS-EEG revealed a physiologically relevant correlation between TMS-induced information flow and levels of consciousness. This suggests that breakdown of effective cortical information flow serves as a viable marker of human consciousness. SignificanceFindings offer a unique perspective on the relevance of information flow in DOC, thus providing a novel way of understanding the physiological basis of human consciousness.

Correlation between Thalamocortical Tract and Default Mode Network with Consciousness Levels in Hypoxic-Ischemic Brain Injury Patients: A Comparative Study Using the Coma Recovery Scale-Revised.

BACKGROUND The thalamocortical tract (TCT) links nerve fibers between the thalamus and cerebral cortex, relaying motor/sensory information. The default mode network (DMN) comprises bilateral, symmetrical, isolated cortical regions of the lateral and medial parietal and temporal brain cortex. The Coma Recovery Scale-Revised (CRS-R) is a standardized neurobehavioral assessment of disorders of consciousness (DOC). In the present study, 31 patients with hypoxic-ischemic brain injury (HI-BI) were compared for changes in the TCT and DMN with consciousness levels assessed using the CRS-R. MATERIAL AND METHODS In this retrospective study, 31 consecutive patients with HI-BI (17 DOC,14 non-DOC) and 17 age- and sex-matched normal control subjects were recruited. Magnetic resonance imaging was used to diagnose HI-BI, and the CRS-R was used to evaluate consciousness levels at the time of diffusion tensor imaging (DTI). The fractional anisotropy (FA) values and tract volumes (TV) of the TCT and DMN were compared. RESULTS In patients with DOC, the FA values and TV of both the TCT and DMN were significantly lower compared to those of patients without DOC and the control subjects (p<0.05). When comparing the non-DOC and control groups, the TV of the TCT and DMN were significantly lower in the non-DOC group (p<0.05). Moreover, the CRS-R score had strong positive correlations with the TV of the TCT (r=0.501, p<0.05), FA of the DMN (r=0.532, p<0.05), and TV of the DMN (r=0.501, p<0.05) in the DOC group. CONCLUSIONS This study suggests that both the TCT and DMN exhibit strong correlations with consciousness levels in DOC patients with HI-BI.

Uncovering sympathetic nervous system dysfunction in disorders of consciousness via heart rate variability during head-up tilt test.

Few standardized tools are available for evaluation of disorders of consciousness (DOC). The potential of heart rate variability (HRV) during head-up tilt (HUT) test was investigated as a complementary evaluation tool. Twenty-one DOC patients and 21 healthy participants were enrolled in this study comparing clinical characteristics and HRV time- and frequency-domain outcomes and temporal changes during HUT test. During the 1st-5th min of the HUT, DOC group showed a significant increase and decrease in log low frequency (LF) (p = 0.045) and log normalized high frequency (nHF) (p = 0.02), respectively, compared to the supine position and had lower log normalized LF (nLF) (p = 0.004) and log ratio of low-to-high frequency (LF/HF) (p = 0.001) compared to healthy controls. As the HUT continued from the 6th to the 20th min, DOC group exhibited a significant increase in log LF/HF (16th-20th min) (p < 0.05), along with a decrease in log nHF (6th-10th and 16th-20th min) (p < 0.05) and maintained lower log LF, log nLF, and log LF/HF than controls (p < 0.05). 1st-10th min after returning to the supine position, DOC group demonstrated a significant decrease in log nHF (p < 0.01) and increases in log LF/HF (p < 0.01) and had lower log LF (p < 0.01) and log nLF (p < 0.05) compared to controls. In contrast, the control group exhibited a significant decrease in log nHF (p < 0.05) and increase in log LF/HF (p < 0.05) throughout the entire HUT test. Notably, no significant differences were observed when comparing time-domain outcomes reflecting parasympathetic nervous system between the two groups. HRV during HUT test indicated a delayed and attenuated autonomic response, particularly in the sympathetic nervous system, in DOC patients compared with healthy individuals.

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

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

Neck muscle spasticity in patients with disorder of consciousness: a pilot study.

Disorder of consciousness (DOC) is a state of prolonged altered consciousness due to severe acquired brain injury (ABI). DOC can be differentiated into coma, unresponsive wakefulness syndrome (UWS), or minimally conscious state (MCS) depending on the behavioral features observed and their relationship to the level of consciousness. Spasticity is one of the most frequently reported medical comorbidities in DOC patients. Since there is a critical lack of spasticity-focused studies and, in turn, of target treatment, we designed this pilot prospective study to evaluate cervical spine muscle spasticity and its effect on rehabilitation outcome in a large cohort of patients followed from the post-acute phase to 6 months after severe ABI. To evaluate neck muscle spasticity and investigate its impact on neurological and functional outcome in a large cohort of adult patients with DOC followed from post-acute to 6 months after severe ABI. Single-center prospective pilot study. Highly specialized inpatient neurorehabilitation clinic. Patients with severe ABI admitted within 3 months after the acute event to our Neurorehabilitation Unit between May 21st, 2019 and April 23rd, 2020 for treatment of DOC as a part of their rehabilitation program. In this single-center prospective pilot study demographic data, etiology of ABI (traumatic versus non-traumatic), DOC evaluated with the revised Coma Recovery Scale (CRS-R), and neurological and functional outcome assessed respectively with the Glasgow Coma Scale (GCS) and Functional Independence Measure (FIM) were considered. During cervical examination, we assessed spasticity with the Modified Ashworth Scale (MAS), deviation of head alignment with a goniometer, and pain with the Nociception Coma Scale-Revised (NCS-R). Of the 48 patients, 41.7% were diagnosed with UWS and 58.3% were in a minimally conscious state (MCS). We found spasticity of neck muscles in 91.7% of patients, with no difference in severity (assessed with MAS) between UWV and MCS. The NCS-R score at cervical spine examination was lower in UWS than MCS. Spasticity was severer in patients with traumatic brain injury (TBI) compared to non-traumatic. At multiple linear regression analysis, younger age, hemisyndrome, and tetraparesis were independent predictors of severity of neck muscle spasticity in MCS. More severe spasticity was a predictor of worse neurological and functional outcome at discharge in UWS patients, independently of the other confounding variables at admission (e.g., age, severity of brain injury, functional assessment, and pain). Spasticity of neck muscles frequently develops in patients with DOC and is more severe in those after TBI. UWV and MCS have different spasticity profiles as regards risk factors and neurological and functional outcome. Severity of neck muscle spasticity in UWV patients may represent an early indicator of worse neurological and functional outcome after inpatient rehabilitation. Our findings could prompt clinicians to redefine the rehabilitation aims regarding spasticity and to estimate the functional outcome in patients undergoing intensive rehabilitation after severe ABI.

Temporal and spatial variability of dynamic microstate brain network in disorders of consciousness.

Accurately diagnosing patients with the vegetative state (VS) and the minimally conscious state (MCS) reached a misdiagnosis of approximately 40%. A method combined microstate and dynamic functional connectivity (dFC) to study the spatiotemporal variability of the brain in disorders of consciousness (DOC) patients was proposed. Resting-state EEG data were obtained from 16 patients with MCS and 16 patients with VS. Mutual information (MI) was used to assess the EEG connectivity in each microstate. MI-based features with statistical differences were selected as the total feature subset (TFS), then the TFS was utilized to feature selection and fed into the classifier, obtaining the optimal feature subsets (OFS) in each microstate. Subsequently, an OFS-based MI functional connectivity network (MIFCN) was constructed in the cortex. The group-average MI connectivity matrix focused on all channels revealed that all five microstates exhibited stronger information interaction in the MCS when comparing with the VS. While OFS-based MIFCN, which only focused on a few channels, revealed greater MI flow in VS patients than in MCS patients under microstates A, B, C, and E, except for microstate D. Additionally, the average classification accuracy of OFS in the five microstates was 96.2%. Constructing features based on microstates to distinguish between two categories of DOC patients had effectiveness.

ST-SCGNN: A Spatio-Temporal Self-Constructing Graph Neural Network for Cross-Subject EEG-Based Emotion Recognition and Consciousness Detection.

In this paper, a novel spatio-temporal self-constructing graph neural network (ST-SCGNN) is proposed for cross-subject emotion recognition and consciousness detection. For spatio-temporal feature generation, activation and connection pattern features are first extracted and then combined to leverage their complementary emotion-related information. Next, a self-constructing graph neural network with a spatio-temporal model is presented. Specifically, the graph structure of the neural network is dynamically updated by the self-constructing module of the input signal. Experiments based on the SEED and SEED-IV datasets showed that the model achieved average accuracies of 85.90% and 76.37%, respectively. Both values exceed the state-of-the-art metrics with the same protocol. In clinical besides, patients with disorders of consciousness (DOC) suffer severe brain injuries, and sufficient training data for EEG-based emotion recognition cannot be collected. Our proposed ST-SCGNN method for cross-subject emotion recognition was first attempted in training in ten healthy subjects and testing in eight patients with DOC. We found that two patients obtained accuracies significantly higher than chance level and showed similar neural patterns with healthy subjects. Covert consciousness and emotion-related abilities were thus demonstrated in these two patients. Our proposed ST-SCGNN for cross-subject emotion recognition could be a promising tool for consciousness detection in DOC patients.

Music, occupational, physical, and speech therapy interventions for patients in disorders of consciousness: An umbrella review.

Current clinical guidelines recommend that a multidisciplinary team inclusive of allied healthcare practitioners deliver assessment and intervention for disorders of consciousness. Allied health professionals include music, occupational, physical, and speech therapists. These allied health clinicians are challenged to select interventions due to a lack of evidence-based recommendations regarding rehabilitation interventions that support recovery of consciousness. This umbrella review synthesizes available systematic reviews (SRs) that describe occupational, speech and language, physical and/or musical therapeutic interventions for people with disorders of consciousness. Identify and summarize evidence from systematic reviews (SRs) that examine allied healthcare interventions for patients with disorders of consciousness. Additionally, this umbrella review aims to evaluate the impact of allied health interventions on recovery of consciousness, methodological quality and risk of bias for the included systematic reviews. An umbrella review was completed. The review was reported according to the Preferred Reporting Items for Overview of Reviews (PRIOR) guidance. Five academic databases (PubMed, CINAHL, PsycInfo, Web of Science, and the Cochrane Library) were searched for SRs and/or meta-analyses of allied health (i.e., music, occupational, physical, and speech therapy) interventions for disorders of consciousness. For included studies, data were extracted and quality of the SRs appraised using the A Measurement Tool to Assess Systematic Reviews (AMSTAR) 2 checklist. Data extracted from each SR identified the authors and years of primary studies, interventions, comparators, and outcomes related to recovery of consciousness (i.e., neurobehavioral/cognitive), functional status, physiological response pain, and adverse events. Rehabilitation interventions were categorized and described. Fifteen SRs were included and three of these reviews conducted meta-analyses. Identified rehabilitation interventions included: 1) sensory stimulation, 2) median nerve stimulation, 3) communication/environmental control through assistive technology, 4) mobilization, and 5) music-based therapy. SRs were published between 2002 and 2022 and included 2286 participants. Using the AMSTAR 2, the quality of reviews was critically low (k = 6), low (k = 3), moderate (k = 4), and high (k = 2). SRs within this umbrella review demonstrated significant heterogeneity in research methods and use of outcome measures to evaluate the recovery of consciousness within the primary studies. These factors influenced the ability to conduct meta-analyses. Sensory stimulation, median nerve stimulation, music therapy and mobilization are all interventions that demonstrate some level of benefit, but current SRs fail to prove benefit through high-level quality evidence. There is an indisputable need for continued rehabilitation research to expand options for treatment modalities and to ensure that the interventions being applied to DoC rehabilitation are evidence-based to improve consciousness and recovery.

Central autonomic network and early prognosis in patients with disorders of consciousness

The central autonomic network (CAN) plays a crucial role in modulating the autonomic nervous system. Heart rate variability (HRV) is a valuable marker for assessing CAN function in disorders of consciousness (DOC) patients. We used HRV analysis for early prognosis in 58 DOC patients enrolled within ten days of hospitalization. They underwent a five-minute electrocardiogram during baseline and acoustic/visual stimulation. The coma recovery scale-revised (CRS-R) was used to define the patient’s consciousness level and categorize the good/bad outcome at three months. The high-frequency Power Spectrum Density and the standard deviation of normal-to-normal peaks in baseline, the sample entropy during the stimulation, and the time from injury features were used in the support vector machine analysis (SVM) for outcome prediction. The SVM predicted the patients’ outcome with an accuracy of 96% in the training test and 100% in the validation test, underscoring its potential to provide crucial clinical information about prognosis.

Research hotspots and frontiers of neuromodulation techniques in disorders of consciousness: a bibliometric analysis.

The characteristics of disorders of consciousness (DOC) are changes in arousal and/or awareness caused by severe brain injuries. To date, the management of DOC patients remains a complex and challenging task, and neuromodulation techniques offer a promising solution. However, a bibliometric analysis focusing on neuromodulation techniques in DOC is currently absent. The aim of this study is to provide a bibliometric visualization analysis to investigate the research hotspots and frontiers in the field of neuromodulation techniques in DOC from 2012 to 2022. The publications were collected and retrieved from the Web of Science (WoS) from 2012 to 2022. CiteSpace and Microsoft Excel were utilized perform the first global bibliographic analysis of the literature related to neuromodulation techniques for DOC. The analysis included a total of 338 publications. From 2012 to 2022, a consistent yet irregular increase in the number of articles published on neuromodulation techniques in DOC was observed. Frontiers in Neurology published the highest number of papers (n = 16). Neurosciences represented the main research hotspot category (n = 170). The most prolific country, institution, and author were the USA (n = 105), the University of Liege (n = 41), and Laureys Steven (n = 38), respectively. An analysis of keywords revealed that UWS/VS, MCS, and TMS constituted the primary research trends and focal points within this domain. This bibliometric study sheds light on the current progress and emerging trends of neuromodulation techniques in DOC from 2012 to 2022. The focal topics in this domain encompass the precise diagnosis of consciousness levels in patients suffering from DOC and the pursuit of efficacious neuromodulation-based evaluation and treatment protocols for such patients.

Brain Temporal-Spectral Functional Variability Reveals Neural Improvements of DBS Treatment for Disorders of Consciousness.

Deep brain stimulation (DBS) is establishing itself as a promising treatment for disorders of consciousness (DOC). Measuring consciousness changes is crucial in the optimization of DBS therapy for DOC patients. However, conventional measures use subjective metrics that limit the investigations of treatment-induced neural improvements. The focus of this study is to analyze the regulatory effects of DBS and explain the regulatory mechanism at the brain functional level for DOC patients. Specifically, this paper proposed a dynamic brain temporal-spectral analysis method to quantify DBS-induced brain functional variations in DOC patients. Functional near-infrared spectroscopy (fNIRS) that promised to evaluate consciousness levels was used to monitor brain variations of DOC patients. Specifically, a fNIRS-based experimental procedure with auditory stimuli was developed, and the brain activities during the procedure from thirteen DOC patients before and after the DBS treatment were recorded. Then, dynamic brain functional networks were formulated with a sliding-window correlation analysis of phase lag index. Afterwards, with respect to the temporal variations of global and regional networks, the variability of global efficiency, local efficiency, and clustering coefficient were extracted. Further, dynamic networks were converted into spectral representations by graph Fourier transform, and graph energy and diversity were formulated to assess the spectral global and regional variability. The results showed that DOC patients under DBS treatment exhibited increased global and regional functional variability that was significantly associated with consciousness improvements. Moreover, the functional variability in the right brain regions had a stronger correlation with consciousness enhancements than that in the left brain regions. Therefore, the proposed method well signifies DBS-induced brain functional variations in DOC patients, and the functional variability may serve as promising biomarkers for consciousness evaluations in DOC patients.

Global Field Time-Frequency Representation-Based Discriminative Similarity Analysis of Passive Auditory ERPs for Diagnosis of Disorders of Consciousness.

Behavioural diagnosis of patients with disorders of consciousness (DOC) is challenging and prone to inaccuracies. Consequently, there have been increased efforts to develop bedside assessment based on EEG and event-related potentials (ERPs) that are more sensitive to the neural factors supporting conscious awareness. However, individual detection of residual consciousness using these techniques is less established. Here, we hypothesize that the cross-state similarity (defined as the similarity between healthy and impaired conscious states) of passive brain responses to auditory stimuli can index the level of awareness in individual DOC patients. To this end, we introduce the global field time-frequency representation-based discriminative similarity analysis (GFTFR-DSA). This method quantifies the average cross-state similarity index between an individual patient and our constructed healthy templates using the GFTFR as an EEG feature. We demonstrate that the proposed GFTFR feature exhibits superior within-group consistency in 34 healthy controls over traditional EEG features such as temporal waveforms. Second, we observed the GFTFR-based similarity index was significantly higher in patients with a minimally conscious state (MCS, 40 patients) than those with unresponsive wakefulness syndrome (UWS, 54 patients), supporting our hypothesis. Finally, applying a linear support vector machine classifier for individual MCS/UWS classification, the model achieved a balanced accuracy and F1 score of 0.77. Overall, our findings indicate that combining discriminative and interpretable markers, along with automatic machine learning algorithms, is effective for the differential diagnosis in patients with DOC. Importantly, this approach can, in principle, be transferred into any ERP of interest to better inform DOC diagnoses.

Wessex Head Injury Matrix in Patients with Prolonged Disorders of Consciousness: A Reliability Study.

Introduction: The Wessex Head Injury Matrix (WHIM) was developed to assess patients with disorders of consciousness (DOC) and was tested in terms of inter-rater reliability (IRR) and test-retest reliability (TRR) in the year 2000. The American Congress of Rehabilitation and Medicine reported that IRR and TRR were unproven. We aim to assess the reliability of the WHIM in prolonged DOC patients (PDOC). Methods: A total of 51 PDOC patients (32 unresponsive wakefulness syndrome (UWS/VS) and 19 minimally conscious state (MCS)) who were hosted in a dedicated unit for long-term brain injury care were enrolled. The time from injury ranged from 182 to 3325 days. Two raters administered the Coma Recovery Scale-Revised (CRS-R) and the WHIM to test the IRR and TRR. The TRR was administered two weeks after the first assessment. Results: For the CRS-R, the agreement in IRR and TRR was perfect between the two raters. The agreement for the WHIM ranged from substantial to almost perfect for IRR and from fair to substantial for the TRR. Conclusions: The WHIM showed a strong IRR when administered by expert raters and strongly correlated with the CRS-R. This study provides further evidence of the psychometric qualities of the WHIM and the importance of its use in PDOC patients.

THE ROLE OF NURSES IN DISORDERS OF CONSCIOUSNESS: ​IMPLEMENTATION OF SENSORY STIMULATION IN THE NEURO-ICU

Abstract In the Neuro Intensive Care Unit (Neuro-ICU), patients with Disorders of Consciousness (DoC) often experience sensory deprivation. DoC, resulting from brain damage, encompasses varying degrees of wakefulness and awareness, ranging from coma to vegetative state and minimally conscious state. Research highlights a concerning trend in the Neuro-ICU, where older adults with DoC are more susceptible to mortality compared to their younger counterparts. This study emphasizes the indispensable role of nurses in effectively managing DoC within the Neuro-ICU, particularly through the thoughtful application of sensory stimulation interventions. Sensory stimulation is a promising approach that engages patients’ various senses—touch, sight, sound, and smell, aiming to awaken awareness and cognitive responses in DoC patients. By fostering neural activity, sensory stimulation holds the potential to contribute to their recovery. Importantly, these techniques can be customized to each patient’s specific condition and responses, and nurses, due to their continuous patient interactions, are uniquely positioned to administer these interventions at the bedside. Recognizing this vital role, evidence-based strategies are proposed, encompassing thorough literature analysis, assessment of nurses’ attitudes, and exploration of potential interventions within the Neuro-ICU setting. This research highlights the significant impact nursing can have on elevating patient outcomes. It demonstrates how evidence-based interventions like sensory stimulation can be seamlessly woven into patient care, providing a valuable and holistic approach for individuals grappling with the intricate challenges presented by DoC.

Clinical neuromodulatory effects of deep brain stimulation in disorder of consciousness: A literature review.

The management of patients with disorders of consciousness (DOC) presents substantial challenges in clinical practice. Deep brain stimulation (DBS) has emerged as a potential therapeutic approach, but the lack of standardized regulatory parameters for DBS in DOC hinders definitive conclusions. This comprehensive review aims to provide a detailed summary of the current issues concerning patient selection, target setting, and modulation parameters in clinical studies investigating the application of DBS for DOC patients. A meticulous systematic analysis of the literatures was conducted, encompassing articles published from 1968 to April 2023, retrieved from reputable databases (PubMed, Embase, Medline, and Web of Science). The systematic analysis of 21 eligible articles, involving 146 patients with DOC resulting from acquired brain injury or other disorders, revealed significant insights. The most frequently targeted regions were the Centromedian-parafascicular complex (CM-pf) nuclei and central thalamus (CT), both recognized for their role in regulating consciousness. However, other targets have also been explored in different studies. The stimulation frequency was predominantly set at 25 or 100 Hz, with pulse width of 120 μs, and voltages ranged from 0 to 4 V. These parameters were customized based on individual patient responses and evaluations. The overall clinical efficacy rate in all included studies was 39.7%, indicating a positive effect of DBS in a subset of DOC patients. Nonetheless, the assessment methods, follow-up durations, and outcome measures varied across studies, potentially contributing to the variability in reported efficacy rates. Despite the challenges arising from the lack of standardized parameters, DBS shows promising potential as a therapeutic option for patients with DOC. However, there still remains the need for standardized protocols and assessment methods, which are crucial to deepen the understanding and optimizing the therapeutic potential of DBS in this specific patient population.

Pupil dilation response elicited by violations of auditory regularities is a promising but challenging approach to probe consciousness at the bedside

Pupil dilation response (PDR) has been proposed as a physiological marker of conscious access to a stimulus or its attributes, such as novelty. In a previous study on healthy volunteers, we adapted the auditory “local global” paradigm and showed that violations of global regularity elicited a PDR. Notably without instructions, this global effect was present only in participants who could consciously report violations of global regularities. In the present study, we used a similar approach in 24 non-communicating patients affected with a Disorder of Consciousness (DoC) and compared PDR to ERPs regarding diagnostic and prognostic performance. At the group level, global effect could not be detected in DoC patients. At the individual level, the only patient with a PDR global effect was in a MCS and recovered consciousness at 6 months. Contrasting the most regular trials to the most irregular ones improved PDR’s diagnostic and prognostic power in DoC patients. Pupillometry is a promising tool but requires several methodological improvements to enhance the signal-to-noise ratio and make it more robust for probing consciousness and cognition in DoC patients.

Untargeted Metabolomic Analyses of Body Fluids to Differentiate TBI DOC and NTBI DOC.

To investigate the metabolomic differences between Traumatic brain injury (TBI) disorder of consciousness (DOC) patients and non-traumatic brain injury (NTBI) DOC patients by using cerebrospinal fluid (CSF), serum and urine samples beneficial to understand the pathological mechanism differences between the two etiologies, provide potential clues for the subsequent treatment and prognosis, and investigate the metabolome differences and similarities between TBI and NTBI among three different body fluids. In total, 24 TBI DOC subjects and 29 NTBI DOC subjects were enrolled. CSF, serum and urine samples from TBI DOC and NTBI DOC patients were collected and analyzed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarkers and altered metabolic functions. When comparing TBI DOC and NTBI DOC, 36, 31 and 52 differential metabolites were obtained in CSF, serum and urine, respectively. The functional analysis of differential metabolites obtained in CSF, serum and urine were all related to amino acid metabolism. Except for amino acid metabolism, metabolic biomarkers in CSF, serum and urine mainly focus on central function, cognitive function, necrosis and apoptosis and neurological function, respectively. In CSF, the highest AUC was 0.864 (Isoproturon) and 0.816 (Proline betaine). Then, the AUC of NFurfurylformamide in serum was 0.941, while the AUC of Dihydronepetalactone and Doxepin N-oxide glucuronide were 1.0 in urine. CSF, serum and urine metabolomic analyses could differentiate TBI DOC from NTBI DOC and functional analyses showed a metabolic change difference between TBI DOC and NTBI DOC.

Predictors of long-term decannulation in patients with disorders of consciousness.

The predictors of tracheostomy decannulation in patients with disorders of consciousness (DOC) are not comprehensively understood, making prognosis difficult. The primary objective of this study was to identify predictors of tracheostomy decannulation in patients with disorders of consciousness (DOC). The secondary aim was to evaluate the feasibility and safety of the modified Evans blue dye test (MEBDT) in tracheostomized DOC patients. This retrospective study included all patients with disorders of consciousness (DOC) who underwent tracheostomy and were admitted between January 2016 and September 2022. Age, sex, etiology, initial Glasgow coma scale (GCS), initial Coma Recovery Scale-Revised (CRS-R), diagnosis of unresponsive wakefulness syndrome (UWS) or minimal consciousness state (MCS), MEBDT, initial modified Rankin scale (mRS), and initial Functional Oral Intake Scale (FOIS) were collected upon study enrollment. The relationship between clinical characteristics and cannulation status was investigated through a Cox regression model. A total of 141 patients were included in the study. The average age of these patients was 52.5 ± 16.7 years, with 42 (29.8%) being women. During the study period, 86 subjects (61%) underwent successful decannulation. Univariate analysis revealed that decannulated patients exhibited a significantly better conscious state compared to those without decannulation (CRS-R: p < 0.001; GCS: p = 0.023; MCS vs. UWS: p < 0.001). Additionally, a negative modified Evans blue dye test (MEBDT) result was significantly associated with tracheostomy decannulation (p < 0.001). In the multivariate analysis, successful decannulation was associated with a higher level of consciousness (MCS vs. UWS, p < 0.001, HR = 6.694) and a negative MEBDT result (negative vs. positive, p = 0.006, HR = 1.873). The Kaplan-Meier analysis further demonstrated that MEBDT-negative patients and those in the MCS category had a higher probability of decannulation at 12 months (p < 0.001). The findings of this study indicate that a negative MEBDT result and a higher level of consciousness can serve as predictive factors for successful tracheostomy decannulation in DOC patients.

Resting-state EEG microstates as electrophysiological biomarkers in post-stroke disorder of consciousness.

Ischemic stroke patients commonly experience disorder of consciousness (DOC), leading to poorer discharge outcomes and higher mortality risks. Therefore, the identification of applicable electrophysiological biomarkers is crucial for the rapid diagnosis and evaluation of post-stroke disorder of consciousness (PS-DOC), while providing supportive evidence for cerebral neurology. In our study, we conduct microstate analysis on resting-state electroencephalography (EEG) of 28 post-stroke patients with awake consciousness and 28 patients with PS-DOC, calculating the temporal features of microstates. Furthermore, we extract the Lempel-Ziv complexity of microstate sequences and the delta/alpha power ratio of EEG on spectral. Statistical analysis is performed to examine the distinctions in features between the two groups, followed by inputting the distinctive features into a support vector machine for the classification of PS-DOC. Both groups obtain four optimal topographies of EEG microstates, but notable distinctions are observed in microstate C. Within the PS-DOC group, there is a significant increase in the mean duration and coverage of microstates B and C, whereas microstate D displays a contrasting trend. Additionally, noteworthy variations are found in the delta/alpha ratio and Lempel-Ziv complexity between the two groups. The integration of the delta/alpha ratio with microstates' temporal and Lempel-Ziv complexity features demonstrates the highest performance in the classifier (Accuracy = 91.07%). Our results suggest that EEG microstates can provide insights into the abnormal brain network dynamics in DOC patients post-stroke. Integrating the temporal and Lempel-Ziv complexity microstate features with spectral features offers a deeper understanding of the neuro mechanisms underlying brain damage in patients with DOC, holding promise as effective electrophysiological biomarkers for diagnosing PS-DOC.

Evaluating the effect of spinal cord stimulation on patient with disorders of consciousness: A TMS-EEG study

ObjectiveThe application of spinal cord stimulation (SCS) in the treatment of disorders of consciousness (DOC) has attracted attention, but its effect on brain activity is still unknown. Transcranial magnetic stimulation combined with EEG (TMS-EEG) can measure cortical activity, which can evaluate the effect of SCS on DOC. MethodsWe record 20 DOC patients' CRS-R values and TMS-EEG data before and after one-session SCS (Pre-SCS and Post-SCS). 20 DOC patients including 10 patients with unresponsive wakefulness syndrome (UWS) and 10 patients with minimally conscious states (MCS). TMS evoked potential (TEP) was used to measure the changes of cortical activity in DOC patients between Pre-SCS and Post-SCS. Firstly, we used the global mean field potential (GMFP) and fast perturbational complexity index (PCIst) to compare the temporal changes of patients' cortical activity. Then, we obtained the frequency feature (natural frequency, NF) based on the TEP time-frequency analysis, and compared the changes of natural frequency between Pre-SCS and Post-SCS. Finally, the study explored the relationship between the patient's baseline CRS-R values and changes of TMS evoked cortical activity in time and frequency domains. ResultsAfter SCS, MCS and UWS groups almost have no changes of CRS-R values (MCS: 9.9 ± 1.52 at Pre-SCS, 10.2 ± 1.48 at Post-SCS; UWS: 5.6 ± 1.26 at Pre-SCS, 5.7 ± 1.34 at Post-SCS). MCS group showed significant increases of GMFP amplitude (around 100 ms and 300 ms) and PCIst values at Post-SCS (p < 0.05). UWS group had no significant changes (p > 0.05). Besides, SCS induced the significant increases of natural frequency for MCS group(p < 0.05), but not for UWS group. At last, the study found that all patient's baseline CRS-R values were significantly correlated with ΔPCIst (r = 0.67, p < 0.005), and ΔNF (r = 0.72, p < 0.001). ConclusionsSCS can modulate cortical activity of DOC patient, including temporal complexity and natural frequency. The changes of cortical activity caused by SCS are related to patients’ consciousness level. TMS-EEG can evaluate the effect of SCS on DOC patients.