Clinical Decision on Disorders of Consciousness After Acquired Brain Injury: Stepping Forward

Best Evidence Summary for the Improvement and Management of Disorders of Consciousness in Patients With Severe Brain Injury

BACKGROUND AND PURPOSE

The treatment effect of consciousness after brain injury is currently uncertain. Thus, this study aimed to retrieve the evidence from neurologists around the world on the management of consciousness disorders in patients with severe brain injury and evaluate and summarize the evidence, providing the guidance on the related management for clinicians.

METHODS

Following the evidence summary report standard of Fudan University Center for Evidence-Based Nursing, clinical guidelines, expert consensuses, systematic reviews, and evidence summaries were systematically retrieved from UpToDate; BMJ Best Practice; Guidelines International Network; the Cochrane Library; Embase; PubMed; Sinomed; Web of Science; CNKI; WanFang database; American Academy of Neurology (AAN); American Congress of Rehabilitation Medicine (ACRM); European Academy of Neurology; and National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR). The publishing timeline for articles was limited from January 2017 to January 2024.

RESULTS

Fourteen articles were finally identified. The 26 best pieces of evidence were recommended by inducting and integrating the evidence from these articles, covering the following seven aspects: consciousness assessment, multidisciplinary team, intervention in facilitating arousal, sensory stimulation programs, drug administration, rehabilitation program, and prevention of complications.

CONCLUSION

This study summarized the evidence of consciousness management in patients with brain injury, providing guidance for clinicians to develop and apply those interventions to improve the patient's clinical outcomes and quality of life. In addition, relevant factors such as the clinical environment and cooperation with the patient's family members should be evaluated and adjusted before applying such evidence. Future studies should focus on more targeted randomized clinical trials.

Revolutionizing treatment for disorders of consciousness: a multidisciplinary review of advancements in deep brain stimulation

Among the existing research on the treatment of disorders of consciousness (DOC), deep brain stimulation (DBS) offers a highly promising therapeutic approach. This comprehensive review documents the historical development of DBS and its role in the treatment of DOC, tracing its progression from an experimental therapy to a detailed modulation approach based on the mesocircuit model hypothesis. The mesocircuit model hypothesis suggests that DOC arises from disruptions in a critical network of brain regions, providing a framework for refining DBS targets. We also discuss the multimodal approaches for assessing patients with DOC, encompassing clinical behavioral scales, electrophysiological assessment, and neuroimaging techniques methods. During the evolution of DOC therapy, the segmentation of central nuclei, the recording of single-neurons, and the analysis of local field potentials have emerged as favorable technical factors that enhance the efficacy of DBS treatment. Advances in computational models have also facilitated a deeper exploration of the neural dynamics associated with DOC, linking neuron-level dynamics with macroscopic behavioral changes. Despite showing promising outcomes, challenges remain in patient selection, precise target localization, and the determination of optimal stimulation parameters. Future research should focus on conducting large-scale controlled studies to delve into the pathophysiological mechanisms of DOC. It is imperative to further elucidate the precise modulatory effects of DBS on thalamo-cortical and cortico-cortical functional connectivity networks. Ultimately, by optimizing neuromodulation strategies, we aim to substantially enhance therapeutic outcomes and greatly expedite the process of consciousness recovery in patients.

Efficacy of melatonin for prolonged disorders of consciousness: a double-blind, randomized clinical trial

BACKGROUND

Sleep is essential for the recovery of patients with disorders of consciousness (DoC). However, few approaches targeting sleep were applied. Melatonin has been shown to enhance sleep efficiency with virtually no side effects. This study explored melatonin's benefits for patients with prolonged DoC, as well as the underlying mechanisms involved.

METHODS

A cohort of 46 patients with prolonged DoC were randomly assigned to either the melatonin treatment group or the placebo group. Assessments were conducted using the Coma Recovery Scale-Revised (CRS-R), electroencephalography (EEG), and polysomnography (PSG) before and after the intervention, with follow-up CRS-R evaluations performed 6 months post-treatment.

RESULTS

Compared to the placebo, melatonin demonstrated a significant improvement in CRS-R scores after a 2-week period in patients with unresponsive wakefulness syndrome (UWS) (Fgroup*time = 6.86, P = 0.032; Fgroup = 4.03, P = 0.045) and this improvement was particularly pronounced in visual scores (Fgroup*time = 7.03, P = 0.030; Fgroup = 4.90, P = 0.027). Moreover, patients with UWS who received melatonin exhibited a higher relative spectral density of the alpha band in the frontal lobe compared to those who received placebo (Ftime-mel = 4.55, P = 0.033) and benefited for their prognosis after 6 months (Pseudo R2 = 0.370, F = 12.03, P = 0.034).

CONCLUSIONS

Overall, melatonin intervention seems to have a better response in UWS patients with preserved sleep cycles. These positive effects may not be solely attributed to improvements in the patients' sleep quality.

TRAIL REGISTRATION

ClinicalTrials.gov: NCT05285124.

Assessing consciousness in acute coma using name-evoked responses

Detecting consciousness in clinically unresponsive patients remains a significant challenge. Existing studies demonstrate that electroencephalography (EEG) can detect brain responses in behaviorally unresponsive patients, indicating potential for consciousness detection. However, most of this evidence is based on chronic patients, and there is a lack of studies focusing on acute coma cases. This study aims to detect signs of residual consciousness in patients with acute coma by using bedside EEG and electromyography (EMG) during an auditory oddball paradigm. We recruited patients with acute brain injury (either traumatic brain injury or cardiac arrest) who were admitted to the intensive care unit within two weeks after injury, with a Glasgow Coma Scale (GCS) score of 8 or below. Auditory stimuli included the patients' own names and other common names (referred to as standard names), spoken by the patients' relatives, delivered under two conditions: passive listening (where patients were instructed that sounds would be played) and active listening (where patients were asked to move hands when heard their own names). Brain and muscle activity were recorded using EEG and EMG during the auditory paradigm. Event-related potentials (ERP) and EMG spectra were analyzed and compared between responses to the subject's own name and other standard names in both passive and active listening conditions. A total of 22 patients were included in the final analysis. Subjects exhibited enhanced ERP responses when exposed to their own names, particularly during the active listening task. Compared to standard names or passive listening, distinct differences in brain network connectivity and increased EMG responses were detected during active listening to their own names. These findings suggest the presence of residual consciousness, offering the potential for assessing consciousness in behaviorally unresponsive patients.

Task-based EEG and fMRI paradigms in a multimodal clinical diagnostic framework for disorders of consciousness

Disorders of consciousness (DoC) are generally diagnosed by clinical assessment, which is a predominantly motor-driven process and accounts for up to 40 % of non-communication being misdiagnosed as unresponsive wakefulness syndrome (UWS) (previously known as prolonged/persistent vegetative state). Given the consequences of misdiagnosis, a more reliable and objective multimodal protocol to diagnosing DoC is needed, but has not been produced due to concerns regarding their interpretation and reliability. Of the techniques commonly used to detect consciousness in DoC, task-based paradigms (active paradigms) produce the most unequivocal result when findings are positive. It is well-established that command following (CF) reliably reflects preserved consciousness. Task-based electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can detect motor-independent CF and reveal preserved covert consciousness in up to 14 % of UWS patients. Accordingly, to improve the diagnostic accuracy of DoC, we propose a practical multimodal clinical decision framework centered on task-based EEG and fMRI, and complemented by measures like transcranial magnetic stimulation (TMS-EEG).

State-specific Regulation of Electrical Stimulation in the Intralaminar Thalamus of Macaque Monkeys: Network and Transcriptional Insights into Arousal

Long-range thalamocortical communication is central to anesthesia-induced loss of consciousness and its reversal. However, isolating the specific neural networks connecting thalamic nuclei with various cortical regions for state-specific anesthesia regulation is challenging, with the biological underpinnings still largely unknown. Here, simultaneous electroencephalogram-fuctional magnetic resonance imaging (EEG-fMRI) and deep brain stimulation are applied to the intralaminar thalamus in macaques under finely-tuned propofol anesthesia. This approach led to the identification of an intralaminar-driven network responsible for rapid arousal during slow-wave oscillations. A network-based RNA-sequencing analysis is conducted of region-, layer-, and cell-specific gene expression data from independent transcriptomic atlases and identifies 2489 genes preferentially expressed within this arousal network, notably enriched in potassium channels and excitatory, parvalbumin-expressing neurons, and oligodendrocytes. Comparison with human RNA-sequencing data highlights conserved molecular and cellular architectures that enable the matching of homologous genes, protein interactions, and cell types across primates, providing novel insight into network-focused transcriptional signatures of arousal.

The assessment of consciousness status in primary brainstem hemorrhage (PBH) patients can be achieved by monitoring changes in basic vital signs

The objective of the study was to explore the association between basic vital signs and consciousness status in patients with primary brainstem hemorrhage (PBH). Patients with PBH were categorized into two groups based on Glasgow Coma Scale (GCS) scores: disturbance of consciousness (DOC) group (GCS=3-8) and non-DOC group (GCS=15). Within DOC group, patients were further divided into behavioral (GCS=4-8) and non-behavioral (GCS=3) subgroups. Basic vital signs, such as body temperature, heart rate, and respiratory rate, were monitored every 3 hours during the acute bleeding phase (1st day) and the bleeding stable phase (7th day) of hospitalization. The findings revealed a negative correlation between body temperature and heart rate with GCS scores in DOC group at both time points. Moreover, basic vital signs were notably higher in the DOC group compared to non-DOC group. Specifically, the non-behavioral subgroup within DOC group exhibited significantly elevated heart rates on the 1st day of hospitalization and moderately increased respiratory rates on the 7th day compared to the control group. Scatter plots illustrated a significant relationship between body temperature and heart rate with consciousness status, while no significant correlation was observed with respiratory rate. In conclusion, the study suggests that monitoring basic vital signs, particularly body temperature and heart rate, can serve as valuable indicators for evaluating consciousness status in PBH patients. These basic vital signs demonstrated variations corresponding to lower GCS scores. Furthermore, integrating basic vital sign monitoring with behavioral assessment could enhance the assessment of consciousness status in PBH patients.

Exploration of resting-state brain functional connectivity as preclinical markers for arousal prediction in prolonged disorders of consciousness: A pilot study based on functional near-infrared spectroscopy

BACKGROUND

There is no diagnostic assessment procedure with moderate or strong evidence of use, and evidence for current means of treating prolonged disorders of consciousness (pDOC) is sparse. This may be related to the fact that the mechanisms of pDOC have not been studied deeply enough and are not clear enough. Therefore, the aim of this study was to explore the mechanism of pDOC using functional near-infrared spectroscopy (fNIRS) to provide a basis for the treatment of pDOC, as well as to explore preclinical markers for determining the arousal of pDOC patients.

METHODS

Five minutes resting-state data were collected from 10 pDOC patients and 13healthy adults using fNIRS. Based on the concentrations of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the time series, the resting-state cortical brain functional connectivity strengths of the two groups were calculated, and the functional connectivity strengths of homologous and heterologous brain networks were compared at the sensorimotor network (SEN), dorsal attention network (DAN), ventral attention network (VAN), default mode network (DMN), frontoparietal network (FPN), and visual network (VIS) levels. Univariate binary logistic regression analyses were performed on brain networks with statistically significant differences to identify brain networks associated with arousal in pDOC patients. The receiver operating characteristic (ROC) curves were further analyzed to determine the cut-off value of the relevant brain networks to provide clinical biomarkers for the prediction of arousal in pDOC patients.

RESULTS

The results showed that the functional connectivity strengths of oxyhemoglobin (HbO)-based SEN∼SEN, VIS∼VIS, DAN∼DAN, DMN∼DMN, SEN∼VIS, SEN∼FPN, SEN∼DAN, SEN∼DMN, VIS∼FPN, VIS∼DAN, VIS∼DMN, HbR-based SEN∼SEN, and SEN∼DAN were significantly reduced in the pDOC group and were factors that could reflect the participants' state of consciousness. The cut-off value of resting-state functional connectivity strength calculated by ROC curve analysis can be used as a potential preclinical marker for predicting the arousal state of subjects.

CONCLUSION

Resting-state functional connectivity strength of cortical networks is significantly reduced in pDOC patients. The cut-off values of resting-state functional connectivity strength are potential preclinical markers for predicting arousal in pDOC patients.

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

Background

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.

Methods

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.

Results

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.

Conclusion

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.

The signs of computer tomography combined with artificial intelligence can indicate the correlation between status of consciousness and primary brainstem hemorrhage of patients

Background

For patients of primary brainstem hemorrhage (PBH), it is crucial to find a method that can quickly and accurately predict the correlation between status of consciousness and PBH.

Objective

To analyze the value of computer tomography (CT) signs in combination with artificial intelligence (AI) technique in predicting the correlation between status of consciousness and PBH.

Methods

A total of 120 patients with PBH were enrolled from August 2011 to March 2021 according to the criteria. Patients were divided into three groups [consciousness, minimally conscious state (MCS) and coma] based on the status of consciousness. Then, first, Mann–Whitney U test and Spearman rank correlation test were used on the factors: gender, age, stages of intracerebral hemorrhage, CT signs with AI or radiology physicians, hemorrhage involving the midbrain or ventricular system. We collected hemorrhage volumes and mean CT values with AI. Second, those significant factors were screened out by the Mann–Whitney U test and those highly or moderately correlated by Spearman’s rank correlation test, and a further ordinal multinomial logistic regression analysis was performed to find independent predictors of the status of consciousness. At last, receiver operating characteristic (ROC) curves were drawn to calculate the hemorrhage volume for predictively assessing the status of consciousness.

Results

Preliminary meaningful variables include hemorrhage involving the midbrain or ventricular system, hemorrhage volume, grade of hematoma shape and density, and CT value from Mann–Whitney U test and Spearman rank correlation test. It is further shown by ordinal multinomial logistic regression analysis that hemorrhage volume and hemorrhage involving the ventricular system are two major predictors of the status of consciousness. It showed from ROC that the hemorrhage volumes of <3.040 mL, 3.040 ~ 6.225 mL and >6.225 mL correspond to consciousness, MCS or coma, respectively. If the hemorrhage volume is the same, hemorrhage involving the ventricular system should be correlated with more severe disorders of consciousness (DOC).

Conclusion

CT signs combined with AI can predict the correlation between status of consciousness and PBH. Hemorrhage volume and hemorrhage involving the ventricular system are two independent factors, with hemorrhage volume in particular reaching quantitative predictions.

Machine learning and network analysis for diagnosis and prediction in disorders of consciousness

BACKGROUND

Prolonged Disorders of Consciousness (PDOC) resulting from severe acquired brain injury can lead to complex disabilities that make diagnosis challenging. The role of machine learning (ML) in diagnosing PDOC states and identifying intervention strategies is relatively under-explored, having focused on predicting mortality and poor outcome. This study aims to: (a) apply ML techniques to predict PDOC diagnostic states from variables obtained from two non-invasive neurobehavior assessment tools; and (b) apply network analysis for guiding possible intervention strategies.

METHODS

The Coma Recovery Scale-Revised (CRS-R) is a well-established tool for assessing patients with PDOC. More recently, music has been found to be a useful medium for assessment of coma patients, leading to the standardization of a music-based assessment of awareness: Music Therapy Assessment Tool for Awareness in Disorders of Consciousness (MATADOC). CRS-R and MATADOC data were collected from 74 PDOC patients aged 16-70 years at three specialist centers in the USA, UK and Ireland. The data were analyzed by three ML techniques (neural networks, decision trees and cluster analysis) as well as modelled through system-level network analysis.

RESULTS

PDOC diagnostic state can be predicted to a relatively high level of accuracy that sets a benchmark for future ML analysis using neurobehavioral data only. The outcomes of this study may also have implications for understanding the role of music therapy in interdisciplinary rehabilitation to help patients move from one coma state to another.

CONCLUSIONS

This study has shown how ML can derive rules for diagnosis of PDOC with data from two neurobehavioral tools without the need to harvest large clinical and imaging datasets. Network analysis using the measures obtained from these two non-invasive tools provides novel, system-level ways of interpreting possible transitions between PDOC states, leading to possible use in novel, next-generation decision-support systems for PDOC.

Functional networks in prolonged disorders of consciousness

Prolonged disorders of consciousness (DoC) are characterized by extended disruptions of brain activities that sustain wakefulness and awareness and are caused by various etiologies. During the past decades, neuroimaging has been a practical method of investigation in basic and clinical research to identify how brain properties interact in different levels of consciousness. Resting-state functional connectivity within and between canonical cortical networks correlates with consciousness by a calculation of the associated temporal blood oxygen level-dependent (BOLD) signal process during functional MRI (fMRI) and reveals the brain function of patients with prolonged DoC. There are certain brain networks including the default mode, dorsal attention, executive control, salience, auditory, visual, and sensorimotor networks that have been reported to be altered in low-level states of consciousness under either pathological or physiological states. Analysis of brain network connections based on functional imaging contributes to more accurate judgments of consciousness level and prognosis at the brain level. In this review, neurobehavioral evaluation of prolonged DoC and the functional connectivity within brain networks based on resting-state fMRI were reviewed to provide reference values for clinical diagnosis and prognostic evaluation.

Influence of High-Frequency Repetitive Transcranial Magnetic Stimulation on Neurobehavioral and Electrophysiology in Patients with Disorders of Consciousness

Objective

High-frequency repetitive transcranial magnetic stimulation (HF-rTMS) has been proposed as a promising therapeutic intervention for patients with disorders of consciousness (DOC). However, its therapeutic effects in the literature are inconsistently documented. The primary aim of this study was to explore the alterations in neural connectivity and neurobehavioral reactivity during rTMS modulation in patients with DOC. In addition, safety was investigated as a secondary aim.

Methods

The presence of bilateral N20 components in DOC patients was determined by somatosensory-evoked potential (SEP) before enrollment in the study. A total of 64 patients were enrolled and randomly placed into the active and sham groups. Ultimately, 50 patients completed the study. Twenty-five patients in the active group underwent real HF-rTMS, and 25 patients in the sham group underwent sham HF-rTMS, which was delivered over the left dorsolateral prefrontal cortex (DLPFC). The outcome measures of performed pre- and postintervention included the latencies of the N20 and N20-P25 amplitudes of SEP, brainstem auditory-evoked potential (BAEP) grade, JFK Coma Recovery Scale-Revised (CRS-R) score, and Glasgow Coma Scale (GCS) score; any adverse events were recorded at any time during the intervention.

Result

Following six weeks of treatment, a significant increase was observed in the total CRS-R and GCS scores, and the N20-P25 amplitudes of patients in the two groups were compared with that obtained from preintervention (all p values < 0.05). The waves of BAEP in the two groups also showed a trend toward normalized activity compared with preintervention grades (p values < 0.05). A significant decrease in the latencies of N20 (p values < 0.001) was observed in the active group compared with measurements obtained from preintervention, whereas no significant decrease was observed in the sham group (p values = 0.013). The improvement in total CRS-R scores (p values = 0.002), total GCS scores (p values = 0.023), and N20-P25 amplitudes (p values = 0.011) as well as the decrease in latencies of N20 (p values = 0.018) and change in BAEP grades (p values = 0.013) were significantly different between the two groups. The parameters in neural connectivity (N20-P25 amplitudes, N20 latencies, and BAEP grades) were significantly correlated with the total CRS-R and GCS scores at postintervention, and the changes of CRS-R before and after interventions have a positive relationship with N20-P25 amplitudes. No adverse events related to the rTMS protocol were recorded.

Conclusion

Neural connectivity levels are affected by HF-rTMS and are significantly related to clinical responses in DOC patients with the presence of bilateral N20. The elevation of neural connectivity levels may lay a foundation for successful HF-rTMS treatment for DOC patients.

The role of autophagy and apoptosis in early brain injury after subarachnoid hemorrhage: an updated review

Subarachnoid hemorrhage (SAH) is a worldwide devastating type of stroke with high mortality and morbidity. Accumulating evidence show early brain injury (EBI) as the leading cause of mortality after SAH. The pathological processes involved in EBI include decreased cerebral blood flow, increased intracranial pressure, vasospasm, and disruption of the blood-brain barrier. In addition, neuroinflammation, oxidative stress, apoptosis, and autophagy have also been proposed to contribute to EBI. Among the various processes involved in EBI, neuronal apoptosis has been proven to be a key factor contributing to the poor prognosis of SAH patients. Meanwhile, as another important catabolic process maintaining the cellular and tissue homeostasis, autophagy has been shown to be neuroprotective after SAH. Studies have shown that enhancing autophagy reduced apoptosis, whereas inhibiting autophagy aggravate neuronal apoptosis after SAH. The physiological substrates and mechanisms of neuronal autophagy and apoptosis by which defects in neuronal function are largely unknown. In this review, we summarize and discuss the role of autophagy and apoptosis after SAH and contribute to further study for investigation of the means to control the balance between them.