The prognostic value of sleep patterns in disorders of consciousness in the sub-acute phase

EEG connectivity and network analyses predict outcome in patients with disorders of consciousness - A systematic review and meta-analysis

Outcome prediction in prolonged disorders of consciousness (DOC) remains challenging. This can result in either inappropriate withdrawal of treatment or unnecessary prolongation of treatment. Electroencephalography (EEG) is a cheap, portable, and non-invasive device with various opportunities for complex signal analysis. Computational EEG measures, such as EEG connectivity and network metrics, might be ideal candidates for the investigation of DOC, but their capacity in prognostication is still undisclosed. We conducted a meta-analysis aiming to compare the prognostic power of the widely used clinical scale, Coma Recovery Scale-Revised - CRS-R and EEG connectivity and network metrics. We found that the prognostic power of the CRS-R scale was moderate (AUC: 0.67 (0.60-0.75)), but EEG connectivity and network metrics predicted outcome with significantly (p = 0.0071) higher accuracy (AUC:0.78 (0.70-0.86)). We also estimated the prognostic capacity of EEG spectral power, which was not significantly (p = 0.3943) inferior to that of the EEG connectivity and graph-theory measures (AUC:0.75 (0.70-0.80)). Multivariate automated outcome prediction tools seemed to outperform clinical and EEG markers.

Which information derived from the Coma Recovery Scale-Revised provides the most reliable prediction of clinical diagnosis and recovery of consciousness? A comparative study using machine learning techniques

BACKGROUND

The Coma Recovery Scale-Revised (CRS-R) is the most recommended clinical tool to examine the neurobehavioral condition of individuals with disorders of consciousness (DOCs). Different studies have investigated the prognostic value of the information provided by the conventional administration of the scale, while other measures derived from the scale have been proposed to improve the prognosis of DOCs. However, the heterogeneity of the data used in the different studies prevents a reliable comparison of the identified predictors and measures.

AIM

This study investigates which information derived from the CRS-R provides the most reliable prediction of both the clinical diagnosis and recovery of consciousness at the discharge of a long-term neurorehabilitation program.

DESIGN

Retrospective observational multisite study.

SETTING

The enrollment was performed in three neurorehabilitation facilities of the same hospital network.

POPULATION

A total of 171 individuals with DOCs admitted to an inpatient neurorehabilitation program for a minimum of 3 months were enrolled.

METHODS

Machine learning classifiers were trained to predict the clinical diagnosis and recovery of consciousness at discharge using clinical confounders and different metrics extracted from the CRS-R scale.

RESULTS

Results showed that the neurobehavioral state at discharge was predicted with acceptable and comparable predictive value with all the indices and measures derived from the CRS-R, but for the clinical diagnosis and the Consciousness Domain Index, and the recovery of consciousness was predicted with higher accuracy and similarly by all the investigated measures, with the exception of initial clinical diagnosis.

CONCLUSIONS

Interestingly, the total score in the CRS-R and, especially, the total score in its subscales provided the best overall results, in contrast to the clinical diagnosis, which could indicate that a comprehensive measure of the clinical diagnosis rather than the condition of the individuals could provide a more reliable prediction of the neurobehavioral progress of individuals with prolonged DOC.

CLINICAL REHABILITATION IMPACT

The results of this work have important implications in clinical practice, offering a more accurate prognosis of patients and thus giving the possibility to personalize and optimize the rehabilitation plan of patients with DoC using low-cost and easily collectable information.

The visual stimulation in disorders of consciousness

Severe brain damage usually leads to disorders of consciousness (DOC), which include coma, unresponsive wakefulness syndrome (UWS) and a minimally conscious state (MCS). Visual stimulation is widely used, especially in the diagnosis and treatment and treatment of DOC. Researchers have indicated that tests based on visual stimulation including visual pursuit, when used in conjunction with the Coma Recovery Scale-Revised, are able to differentiate between UWS from an MCS. Recently, targeting patients' circadian rhythms has been proposed to be a possible treatment target for DOC. Indeed, light therapy has been applied in some other fields, including treating seasonal affective disorder, sleep problems, and Parkinson's disease. However, at present, although visual stimulation and light therapy are frequently used in DOC, there is still no international unified standard. Therefore, we recommend the development of an international consensus in regard to the definitions, operational criteria and assessment procedures of visual stimulation and light therapy. This review combines visual stimulation, circadian rhythm recovery, and light therapy in DOC patients and presents the mechanisms and current advances in applications related to light therapy and visual stimulation in an attempt to provide additional ideas for future research and treatment of DOC.

Long-term clinical evolution of patients with prolonged disorders of consciousness due to severe anoxic brain injury: A meta-analytic study

BACKGROUND AND PURPOSE

The prognosis of prolonged (28 days to 3 months post-onset) disorders of consciousness (pDoC) due to anoxic brain injury is uncertain. The present study aimed to evaluate the long-term outcome of post-anoxic pDoC and identify the possible predictive value of demographic and clinical information.

METHOD

This is a systematic review and meta-analysis. The rates of mortality, any improvement in clinical diagnosis, and recovery of full consciousness at least 6 months after severe anoxic brain injury were evaluated. A cross-sectional approach searched for differences in baseline demographic and clinical characteristics between survivors and non-survivors, patients improved versus not improved, and patients who recovered full consciousness versus not recovered.

RESULTS

Twenty-seven studies were identified. The pooled rates of mortality, any clinical improvement and recovery of full consciousness were 26%, 26% and 17%, respectively. Younger age, baseline diagnosis of minimally conscious state versus vegetative state/unresponsive wakefulness syndrome, higher Coma Recovery Scale Revised total score, and earlier admission to intensive rehabilitation units were associated with a significantly higher likelihood of survival and clinical improvement. These same variables, except time of admission to rehabilitation, were also associated with recovery of full consciousness.

CONCLUSIONS

Patients with anoxic pDoC might improve over time up to full recovery of consciousness and some clinical characteristics can help predict clinical improvement. These new insights could support clinicians and caregivers in the decision-making on patient management.

Prognostication in Prolonged and Chronic Disorders of Consciousness

Patients with prolonged disorders of consciousness (DOCs) longer than 28 days may continue to make significant gains and achieve functional recovery. Occasionally, this recovery trajectory may extend past 3 (for nontraumatic etiologies) and 12 months (for traumatic etiologies) into the chronic period. Prognosis is influenced by several factors including state of DOC, etiology, and demographics. There are several testing modalities that may aid prognostication under active investigation including electroencephalography, functional and anatomic magnetic resonance imaging, and event-related potentials. At this time, only one treatment (amantadine) has been routinely recommended to improve functional recovery in prolonged DOC. Given that some patients with prolonged or chronic DOC have the potential to recover both consciousness and functional status, it is important for neurologists experienced in prognostication to remain involved in their care.

Sleep in Disorders of Consciousness: A Brief Overview on a Still under Investigated Issue

Consciousness is a multifaceted concept, involving both wakefulness, i.e., a condition of being alert that is regulated by the brainstem, and awareness, a subjective experience of any thoughts or perception or emotion. Recently, the European Academy of Neurology has published international guidelines for a better diagnosis of coma and other disorders of consciousness (DOC) through the investigation of sleep patterns, such as slow-wave and REM, and the study of the EEG using machine learning methods and artificial intelligence. The management of sleep disorders in DOC patients is an increasingly hot topic and deserves careful diagnosis, to allow for the most accurate prognosis and the best medical treatment possible. The aim of this review was to investigate the anatomo-physiological basis of the sleep/wake cycle, as well as the main sleep patterns and sleep disorders in patients with DOC. We found that the sleep characteristics in DOC patients are still controversial. DOC patients often present a theta/delta pattern, while epileptiform activity, as well as other sleep elements, have been reported as correlating with outcomes in patients with coma and DOC. The absence of spindles, as well as REM and K-complexes of NREM sleep, have been used as poor predictors for early awakening in DOC patients, especially in UWS patients. Therefore, sleep could be considered a marker of DOC recovery, and effective treatments for sleep disorders may either indirectly or directly favor recovery of consciousness.

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

Major advances have been made over the past few decades in identifying and managing disorders of consciousness (DOC) in patients with acquired brain injury (ABI), bringing the transformation from a conceptualized definition to a complex clinical scenario worthy of scientific exploration. Given the continuously-evolving framework of precision medicine that integrates valuable behavioral assessment tools, sophisticated neuroimaging, and electrophysiological techniques, a considerably higher diagnostic accuracy rate of DOC may now be reached. During the treatment of patients with DOC, a variety of intervention methods are available, including amantadine and transcranial direct current stimulation, which have both provided class II evidence, zolpidem, which is also of high quality, and non-invasive stimulation, which appears to be more encouraging than pharmacological therapy. However, heterogeneity is profoundly ingrained in study designs, and only rare schemes have been recommended by authoritative institutions. There is still a lack of an effective clinical protocol for managing patients with DOC following ABI. To advance future clinical studies on DOC, we present a comprehensive review of the progress in clinical identification and management as well as some challenges in the pathophysiology of DOC. We propose a preliminary clinical decision protocol, which could serve as an ideal reference tool for many medical institutions.

EEG-based methods for recovery prognosis of patients with disorders of consciousness: A systematic review

OBJECTIVE

Disorders of consciousness (DoC) are acquired conditions of severely altered consciousness. Electroencephalography (EEG)-derived biomarkers have been studied as clinical predictors of consciousness recovery. Therefore, this study aimed to systematically review the methods, features, and models used to derive prognostic EEG markers in patients with DoC in a rehabilitation setting.

METHODS

We conducted a systematic literature search of EEG-based strategies for consciousness recovery prognosis in five electronic databases.

RESULTS

The search resulted in 2964 papers. After screening, 15 studies were included in the review. Our analyses revealed that simpler experimental settings and similar filtering cut-off frequencies are preferred. The results of studies were categorised by extracting qualitative and quantitative features. The quantitative features were further classified into evoked/event-related potentials, spectral measures, entropy measures, and graph-theory measures. Despite the variety of methods, features from all categories, including qualitative ones, exhibited significant correlations with DoC prognosis. Moreover, no agreement was found on the optimal set of EEG-based features for the multivariate prognosis of patients with DoC, which limits the computational methods applied for outcome prediction and correlation analysis to classical ones. Nevertheless, alpha power, reactivity, and higher complexity metrics were often found to be predictive of consciousness recovery.

CONCLUSIONS

This study's findings confirm the essential role of qualitative EEG and suggest an important role for quantitative EEG. Their joint use could compensate for their reciprocal limitations.

SIGNIFICANCE

This study emphasises the need for further efforts toward guidelines on standardised EEG analysis pipeline, given the already proven role of EEG markers in the recovery prognosis of patients with DoC.

A Potential Prognosis Indicator Based on P300 Brain-Computer Interface for Patients with Disorder of Consciousness

For patients with disorders of consciousness, such as unresponsive wakefulness syndrome (UWS) patients and minimally conscious state (MCS) patients, their long treatment cycle and high cost commonly put a heavy burden on the patient's family and society. Therefore, it is vital to accurately diagnose and predict consciousness recovery for such patients. In this paper, we explored the role of the P300 signal based on an audiovisual BCI in the classification and prognosis prediction of patients with disorders of consciousness. This experiment included 18 patients: 10 UWS patients and 8 MCS- patients. At the three-month follow-up, we defined patients with an improved prognosis (from UWS to MCS-, from UWS to MCS+, or from MCS- to MCS+) as "improved patients" and those who stayed in UWS/MCS as "not improved patients". First, we compared and analyzed different types of patients, and the results showed that the P300 detection accuracy rate of "improved" patients was significantly higher than that of "not improved" patients. Furthermore, the P300 detection accuracy of traumatic brain injury (TBI) patients was significantly higher than that of non-traumatic brain injury (NTBI, including acquired brain injury and cerebrovascular disease) patients. We also found that there was a positive linear correlation between P300 detection accuracy and CRS-R score, and patients with higher P300 detection accuracy were likely to achieve higher CRS-R scores. In addition, we found that the patients with higher P300 detection accuracies tend to have better prognosis in this audiovisual BCI. These findings indicate that the detection accuracy of P300 is significantly correlated with the level of consciousness, etiology, and prognosis of patients. P300 can be used to represent the preservation level of consciousness in clinical neurophysiology and predict the possibility of recovery in patients with disorders of consciousness.

Validity of the Early Functional Ability scale (EFA) among critically ill patients undergoing early neurological rehabilitation

Background

A reliable assessment of the functional abilities of patients after severe brain damage is crucial for valid prognostication and treatment decisions, but most clinical scales are of limited use among this specific group of patients.

Aim

The present study investigates the usefulness of the Early Functional Ability (EFA) scale, which determines the functional abilities of severely impaired patients.

Methods

Critically ill patients consecutively admitted to early neurological rehabilitation were screened for eligibility. We assessed the correlation between the EFA scale and (i) the Early Rehabilitation Barthel Index (ERBI), and (ii) the Coma Recovery Scale-Revised (CRS-R). The 1-year outcome on the Glasgow Outcome Scale-extended (GOSE) was used to examine the predictive validity. Demographical and medical variables were entered into univariate and multivariate binary regression models to identify independent predictors of 1-year outcome.

Results

Two hundred fifty-seven patients (168 men) with a median age of 62 years (IQR = 51–75) were enrolled. The correlation of the EFA scale with the CRS-R was high but low with the ERBI upon admission. Multivariate regression analysis yielded the vegetative subscale of the EFA scale as the only independent predictor for the 1-year outcome of patients admitted to early neurological rehabilitation.

Conclusions

This study shows a high correlation of the EFA scale with the CRS-R but a weak correlation with the ERBI in patients with low functional abilities. With improving patient abilities, these correlations were partly reversed. Thus, the EFA scale is a useful tool to assess the functional abilities and the prognosis of critically ill patients adequately and may be more feasible than other scales.

The importance of instrumental assessment in disorders of consciousness: a comparison between American, European, and UK International recommendations

The use of instrumental tools for improving both the diagnostic accuracy and the prognostic soundness in patients with disorders of consciousness (DOC) plays an important role. However, the most recent international guidelines on DOC published by the American and the European Academies of Neurology and by the UK Royal College of Physicians contain heterogeneous recommendations on the implementation of these techniques in the clinical routine for both diagnosis and prognosis. With the present work, starting from the comparison of the DOC guidelines’ recommendations, we look for possible explanations behind such discrepancies considering the adopted methodologies and the reference health systems that could have affected the guidelines’ perspectives. We made a provocative argument about the need to find the most appropriate common methodology to retrieve and grade the evidence, increase the meta-analytic studies, and reduce the health policies that influence on the guidelines development that, in turn, should inform the health policies with the strongest scientific evidence.

A simple intervention for disorders of consciousness- is there a light at the end of the tunnel?

Sleep is a physiological state necessary for memory processing, learning and brain plasticity. Patients with disorders of consciousness (DOC) show none or minimal sign of awareness of themselves or their environment but appear to have sleep-wake cycles. The aim of our study was to assess baseline circadian rhythms and sleep in patients with DOC; to optimize circadian rhythm using an intervention combining blue light, melatonin and caffeine, and to identify the impact of this intervention on brain function using event related potentials. We evaluated baseline circadian rhythms and sleep in 17 patients with DOC with 24-h polysomnography (PSG) and 4-hourly saliva melatonin measurements for 48 h. Ten of the 17 patients (5 female, age 30–71) were then treated for 5 weeks with melatonin each night and blue light and caffeine treatment in the mornings. Behavioral assessment of arousal and awareness [Coma recovery scale-revised (CRS-R)], 24-h polysomnography and 4-hourly saliva melatonin measurements, oddball mismatch negativity (MMN) and subject's own name (SON) experiments were performed twice at baseline and following intervention. Baseline sleep was abnormal in all patients. Cosinor analysis of saliva melatonin results revealed that averaged baseline % rhythmicity was low (M: 31%, Range: 13–66.4%, SD: 18.4). However, increase in % Melatonin Rhythm following intervention was statistically significant (p = 0.012). 7 patients showed improvement of CRS-R scores with intervention and this was statistically significant (p = 0.034). All the patients who had improvement of clinical scores also had statistically significant improvement of neurophysiological responses on MMN and SON experiments at group level (p = 0.001). Our study shows that sleep and circadian rhythms are severely deranged in DOC but optimization is possible with melatonin, caffeine and blue light treatment. Clinical and physiological parameters improved with this simple and inexpensive intervention. Optimization of sleep and circadian rhythms should be integrated into rehabilitation programs for people with DOC.

Sleep Treatments in Disorders of Consciousness: A Systematic Review

Sleep disorders are among the main comorbidities in patients with a Disorder of Consciousness (DOC). Given the key role of sleep in neural and cognitive functioning, detecting and treating sleep disorders in DOCs might be an effective therapeutic strategy to boost consciousness recovery and levels of awareness. To date, no systematic reviews have been conducted that explore the effect of sleep treatments in DOCs; thus, we systematically reviewed the existing studies on both pharmacological and non-pharmacological treatments for sleep disorders in DOCs. Among 2267 assessed articles, only 7 were included in the systematic review. The studies focused on two sleep disorder categories (sleep-related breathing disorders and circadian rhythm dysregulation) treated with both pharmacological (Modafinil and Intrathecal Baclofen) and non-pharmacological (positive airway pressure, bright light stimulation, and central thalamic deep brain stimulation) interventions. Although the limited number of studies and their heterogeneity do not allow generalized conclusions, all the studies highlighted the effectiveness of treatments on both sleep disorders and levels of awareness. For this reason, clinical and diagnostic evaluations able to detect sleep disorders in DOC patients should be adopted in the clinical routine for the purpose of intervening promptly with the most appropriate treatment.

A Systematic Review of Sleep in Patients with Disorders of Consciousness: From Diagnosis to Prognosis

With the development of intensive care technology, the number of patients who survive acute severe brain injury has increased significantly. At present, it is difficult to diagnose the patients with disorders of consciousness (DOCs) because motor responses in these patients may be very limited and inconsistent. Electrophysiological criteria, such as event-related potentials or motor imagery, have also been studied to establish a diagnosis and prognosis based on command-following or active paradigms. However, the use of such task-based techniques in DOC patients is methodologically complex and requires careful analysis and interpretation. The present paper focuses on the analysis of sleep patterns for the evaluation of DOC and its relationships with diagnosis and prognosis outcomes. We discuss the concepts of sleep patterns in patients suffering from DOC, identification of this challenging population, and the prognostic value of sleep. The available literature on individuals in an unresponsive wakefulness syndrome (UWS) or minimally conscious state (MCS) following traumatic or nontraumatic severe brain injury is reviewed. We can distinguish patients with different levels of consciousness by studying sleep patients with DOC. Most MCS patients have sleep and wake alternations, sleep spindles and rapid eye movement (REM) sleep, while UWS patients have few EEG changes. A large number of sleep spindles and organized sleep-wake patterns predict better clinical outcomes. It is expected that this review will promote our understanding of sleep EEG in DOC.

Cognitive Dysfunction After Analgesia and Sedation: Out of the Operating Room and Into the Pediatric Intensive Care Unit

In the midst of concerns for potential neurodevelopmental effects after surgical anesthesia, there is a growing awareness that children who require sedation during critical illness are susceptible to neurologic dysfunctions collectively termed pediatric post-intensive care syndrome, or PICS-p. In contrast to healthy children undergoing elective surgery, critically ill children are subject to inordinate neurologic stress or injury and need to be considered separately. Despite recognition of PICS-p, inconsistency in techniques and timing of post-discharge assessments continues to be a significant barrier to understanding the specific role of sedation in later cognitive dysfunction. Nonetheless, available pediatric studies that account for analgesia and sedation consistently identify sedative and opioid analgesic exposures as risk factors for both in-hospital delirium and post-discharge neurologic sequelae. Clinical observations are supported by animal models showing neuroinflammation, increased neuronal death, dysmyelination, and altered synaptic plasticity and neurotransmission. Additionally, intensive care sedation also contributes to sleep disruption, an important and overlooked variable during acute illness and post-discharge recovery. Because analgesia and sedation are potentially modifiable, understanding the underlying mechanisms could transform sedation strategies to improve outcomes. To move the needle on this, prospective clinical studies would benefit from cohesion with regard to datasets and core outcome assessments, including sleep quality. Analyses should also account for the wide range of diagnoses, heterogeneity of this population, and the dynamic nature of neurodevelopment in age cohorts. Much of the related preclinical evidence has been studied in comparatively brief anesthetic exposures in healthy animals during infancy and is not generalizable to critically ill children. Thus, complementary animal models that more accurately "reverse translate" critical illness paradigms and the effect of analgesia and sedation on neuropathology and functional outcomes are needed. This review explores the interactive role of sedatives and the neurologic vulnerability of critically ill children as it pertains to survivorship and functional outcomes, which is the next frontier in pediatric intensive care.

Sleep in disorders of consciousness: diagnostic, prognostic, and therapeutic considerations

PURPOSE OF REVIEW

Sleep is important in the evaluation of patients with disorders of consciousness (DOC). However, it remains unclear whether reconstitution of sleep could enable consciousness or vice versa. Here we synthesize recent evidence on natural recovery of sleep in DOC, and sleep-promoting therapeutic interventions for recovery of consciousness.

RECENT FINDINGS

In subacute DOC, physiological sleep--wake cycles and complex sleep patterns are related to better outcomes. Moreover, structured rapid-eye-movement (REM), non-REM (NREM) stages, and presence of sleep spindles correlate with full or partial recovery. In chronic DOC, sleep organization may reflect both integrity of consciousness-supporting brain networks and engagement of those networks during wakefulness. Therapeutic strategies have integrated improvement of sleep and sleep--wake cycles in DOC patients; use of bright light stimulation or drugs enhancing sleep and/or vigilance, treatment of sleep apneas, and neuromodulatory stimulations are promising tools to promote healthy sleep architecture and wakeful recovery.

SUMMARY

Sleep features and sleep--wake cycles are important prognostic markers in subacute DOC and can provide insight into covert recovery in chronic DOC. Although large-scale studies are needed, preliminary studies in limited patients suggest that therapeutic options restoring sleep and/or sleep--wake cycles may improve cognitive function and outcomes in DOC.

Narrative Review: Quantitative EEG in Disorders of Consciousness

In this narrative review, we focus on the role of quantitative EEG technology in the diagnosis and prognosis of patients with unresponsive wakefulness syndrome and minimally conscious state. This paper is divided into two main parts, i.e., diagnosis and prognosis, each consisting of three subsections, namely, (i) resting-state EEG, including spectral power, functional connectivity, dynamic functional connectivity, graph theory, microstates and nonlinear measurements, (ii) sleep patterns, including rapid eye movement (REM) sleep, slow-wave sleep and sleep spindles and (iii) evoked potentials, including the P300, mismatch negativity, the N100, the N400 late positive component and others. Finally, we summarize our findings and conclude that QEEG is a useful tool when it comes to defining the diagnosis and prognosis of DOC patients.

EEG Assessment in Patients With Disorders of Consciousness: Aims, Advantages, Limits, and Pitfalls

This study presents a brief review of literature exploring simple EEG-polygraphic examinations and procedures that can be carried out at a patient's bedside. These include EEG with a common electrode array and sleep evaluation. The review briefly discusses more complex analytical techniques, such as the application of advanced EEG signal processing methods developed by our research group, to define what type of consistent markers are suitable for clinical use or to better understand complex patient conditions. These advanced analytical techniques aim to detect relevant EEG-based markers that could be useful in evaluating patients and predicting outcomes. These data could contribute to future developments in research.

Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies

Substantial progress has been made over the past two decades in detecting, predicting and promoting recovery of consciousness in patients with disorders of consciousness (DoC) caused by severe brain injuries. Advanced neuroimaging and electrophysiological techniques have revealed new insights into the biological mechanisms underlying recovery of consciousness and have enabled the identification of preserved brain networks in patients who seem unresponsive, thus raising hope for more accurate diagnosis and prognosis. Emerging evidence suggests that covert consciousness, or cognitive motor dissociation (CMD), is present in up to 15-20% of patients with DoC and that detection of CMD in the intensive care unit can predict functional recovery at 1 year post injury. Although fundamental questions remain about which patients with DoC have the potential for recovery, novel pharmacological and electrophysiological therapies have shown the potential to reactivate injured neural networks and promote re-emergence of consciousness. In this Review, we focus on mechanisms of recovery from DoC in the acute and subacute-to-chronic stages, and we discuss recent progress in detecting and predicting recovery of consciousness. We also describe the developments in pharmacological and electrophysiological therapies that are creating new opportunities to improve the lives of patients with DoC.

When, How, and to What Extent Are Individuals with Unresponsive Wakefulness Syndrome Able to Progress? Neurobehavioral Progress

Accurate estimation of the neurobehavioral progress of patients with unresponsive wakefulness syndrome (UWS) is essential to anticipate their most likely clinical course and guide clinical decision making. Although different studies have described this progress and possible predictors of neurobehavioral improvement in these patients, they have methodological limitations that could restrict the validity and generalization of the results. This study investigates the neurobehavioral progress of 100 patients with UWS consecutively admitted to a neurorehabilitation center using systematic weekly assessments based on standardized measures, and the prognostic factors of changes in their neurobehavioral condition. Our results showed that, during the analyzed period, 34% of the patients were able to progress from UWS to minimally conscious state (MCS), 12% of the total sample (near one third from those who progressed to MCS) were able to emerge from MCS, and 10% of the patients died. Transition to MCS was mostly denoted by visual signs, which appeared either alone or in combination with motor signs, and was predicted by etiology and the score on the Coma Recovery Scale-Revised at admission with an accuracy of 75%. Emergence from MCS was denoted in the same proportion by functional communication and object use. Predictive models of emergence from MCS and mortality were not valid and the identified predictors could not be accounted for.

Retrospective analysis of sleep patterns in patients with chronic disorders of consciousness

Analysis of sleep patterns in patients with chronic disorders of consciousness attracts attention from the perspective of the diagnosis and prognosis of the disease as well as the treatment. Yet, the very existence of normal sleep in patients in a vegetative or minimally conscious state is still a matter of debate. This paper presents a retrospective analysis of overnight polysomnographic records of 40 patients with chronic disorders of consciousness aimed at the possibility of establishing the connection between the degree of impaired consciousness and the presence and organization of polysomnographic graphical elements, associated with stages of sleep in normal individuals. Specialized software based on expert system artificial intelligence was developed to calculate indices and parameters that characterize sleep. It was shown that a remarkably low percentage of patients have a rhythmic change in sleep patterns, what indicates the prevalence of violations of the Sleep-Wake cycle in a vegetative state and minimally conscious state. Sleep spindles were not found in records, however, the absence can originate from the limitations of polysomnographic method applied to patients with severe brain damage. A positive correlation between the rhythmic change of sleep patterns, better outcome and CRS-R scores was confirmed.

Sleep in disorders of consciousness: behavioral and polysomnographic recording

BACKGROUND

Sleep-wakefulness cycles are an essential diagnostic criterion for disorders of consciousness (DOC), differentiating prolonged DOC from coma. Specific sleep features, like the presence of sleep spindles, are an important marker for the prognosis of recovery from DOC. Based on increasing evidence for a link between sleep and neuronal plasticity, understanding sleep in DOC might facilitate the development of novel methods for rehabilitation. Yet, well-controlled studies of sleep in DOC are lacking. Here, we aimed to quantify, on a reliable evaluation basis, the distribution of behavioral and neurophysiological sleep patterns in DOC over a 24-h period while controlling for environmental factors (by recruiting a group of conscious tetraplegic patients who resided in the same hospital).

METHODS

We evaluated the distribution of sleep and wakefulness by means of polysomnography (EEG, EOG, EMG) and video recordings in 32 DOC patients (16 unresponsive wakefulness syndrome [UWS], 16 minimally conscious state [MCS]), and 10 clinical control patients with severe tetraplegia. Three independent raters scored the patients' polysomnographic recordings.

RESULTS

All but one patient (UWS) showed behavioral and electrophysiological signs of sleep. Control and MCS patients spent significantly more time in sleep during the night than during daytime, a pattern that was not evident in UWS. DOC patients (particularly UWS) exhibited less REM sleep than control patients. Forty-four percent of UWS patients and 12% of MCS patients did not have any REM sleep, while all control patients (100%) showed signs of all sleep stages and sleep spindles. Furthermore, no sleep spindles were found in 62% of UWS patients and 21% of MCS patients. In the remaining DOC patients who had spindles, their number and amplitude were significantly lower than in controls.

CONCLUSIONS

The distribution of sleep signs in DOC over 24 h differs significantly from the normal sleep-wakefulness pattern. These abnormalities of sleep in DOC are independent of external factors such as severe immobility and hospital environment.

EEG and Coma Recovery Scale-Revised prediction of neurological outcome in Disorder of Consciousness patients

OBJECTIVE

According to electroencephalogram (EEG) descriptors included in the American Clinical Neurophysiology Society (ACNS) terminology, we generated a score, and we compared it to the EEG scores previously proposed in order to identify the one with the best prognostic power for neurological outcome at post-acute stages in patients with severe disorders of consciousness (DoC).

MATERIALS AND METHODS

Patients included in the analysis were clinically evaluated with the Coma Recovery Scale-Revised (CRS-R). An EEG was performed within the first week after admission to Intensive Rehabilitation Unit (IRU). EEGs were classified according to the ACNS terminology and to the scores of Bagnato and Estraneo.

RESULTS

A total of 260 patients admitted to the IRU were analysed. A total of 160 patients (61%) improved their consciousness level during IRU stay. EEG score based on the ANCS terminology showed higher overall performance (receiver-operating area under the curve = 0.79) and greater sensitivity (65%), at comparable specificities (80%), for clinical improvement as compared to both CRS-R admission score and other EEG scores. Combining our EEG score with CRS-R score at admission, the cumulative sensitivity increased to 76% when at least one good prognostic index test was present in the same patient, whereas specificity increased up to 93% if both the good prognostic patterns of clinical and instrumental parameters were simultaneously present.

CONCLUSION

The EEG scored according to the ACNS terminology is the best among those looked at for the prediction of short-term clinical improvement in patients with DoC and represents a useful instrumental test, complementary to clinical evaluation at admission, to be added in post-acute neurological prognostication methods.

Clinical and advanced neurophysiology in the prognostic and diagnostic evaluation of disorders of consciousness: review of an IFCN-endorsed expert group

The analysis of spontaneous EEG activity and evoked potentialsis a cornerstone of the instrumental evaluation of patients with disorders of consciousness (DoC). Thepast few years have witnessed an unprecedented surge in EEG-related research applied to the prediction and detection of recovery of consciousness after severe brain injury,opening up the prospect that new concepts and tools may be available at the bedside. This paper provides a comprehensive, critical overview of bothconsolidated and investigational electrophysiological techniquesfor the prognostic and diagnostic assessment of DoC.We describe conventional clinical EEG approaches, then focus on evoked and event-related potentials, and finally we analyze the potential of novel research findings. In doing so, we (i) draw a distinction between acute, prolonged and chronic phases of DoC, (ii) attempt to relate both clinical and research findings to the underlying neuronal processes and (iii) discuss technical and conceptual caveats.The primary aim of this narrative review is to bridge the gap between standard and emerging electrophysiological measures for the detection and prediction of recovery of consciousness. The ultimate scope is to provide a reference and common ground for academic researchers active in the field of neurophysiology and clinicians engaged in intensive care unit and rehabilitation.

Prognostic roles of sleep electroencephalography pattern and circadian rhythm biomarkers in the recovery of consciousness in patients with coma: a prospective cohort study

OBJECTIVE

To investigate the potential prognostic value of sleep electroencephalography (EEG) pattern and serum circadian rhythm biomarkers in the recovery of consciousness in patients at the acute stage of coma.

METHODS

A prospective observational study which included 75 patients with coma was conducted. Twenty-four-hour continuous polysomnography (PSG) was performed to determine the sleep EEG pattern according to the modified Valente's Grade (mVG) that we proposed. Serum levels of melatonin and orexin-A at four consecutive time points during the PSG were examined. Patients were then followed for one month to determine their level of consciousness. Multivariate logistic regression analysis was performed to examine associations between demographics, aetiology, baseline clinical features (pupillary and corneal reflex, and neuron-specific enolase [NSE]), clinical scores (Glasgow Coma Scale-Motor Response [GCS-M], Full Outline of Unresponsiveness [FOUR] scale, Acute Physiology and Chronic Health Evaluation II [APACHE II] scale), mVG, serum circadian biomarkers, and recovery of consciousness within one month.

RESULTS

Within one month of enrolment, 34 patients regained consciousness and 36 patients remained non-conscious. Spearman rank correlation revealed a significant association between mVG and state of consciousness after one month. Significant variation in serum melatonin or orexin-A was not detected in either the conscious or non-conscious groups. Hypoxic aetiology, APACHE II, and mVG were independently associated with recovery of consciousness within one month.

CONCLUSION

Sleep EEG structure, hypoxic aetiology, and APACHE II can independently predict recovery of consciousness in patients with acute coma. Taken together, we encourage neurologists to use sleep elements to assess patients with acute coma.

Toward Improving Diagnostic Strategies in Chronic Disorders of Consciousness: An Overview on the (Re-)Emergent Role of Neurophysiology

The differential diagnosis of patients with Disorder of Consciousness (DoC), in particular in the chronic phase, is significantly difficult. Actually, about 40% of patients with unresponsive wakefulness syndrome (UWS) and the minimally conscious state (MCS) are misdiagnosed. Indeed, only advanced paraclinical approaches, including advanced EEG analyses, can allow achieving a more reliable diagnosis, that is, discovering residual traces of awareness in patients with UWS (namely, functional Locked-In Syndrome (fLIS)). These approaches aim at capturing the residual brain network models, at rest or that may be activated in response to relevant stimuli, which may be appropriate for awareness to emerge (despite their insufficiency to generate purposeful motor behaviors). For this, different brain network models have been studied in patients with DoC by using sensory stimuli (i.e., passive tasks), probing response to commands (i.e., active tasks), and during resting-state. Since it can be difficult for patients with DoC to perform even simple active tasks, this scoping review aims at summarizing the current, innovative neurophysiological examination methods in resting state/passive modality to differentiate and prognosticate patients with DoC. We conclude that the electrophysiologically-based diagnostic procedures represent an important resource for diagnosis, prognosis, and, therefore, management of patients with DoC, using advance passive and resting state paradigm analyses for the patients who lie in the “greyzones” between MCS, UWS, and fLIS.

Color density spectral array for early evaluation of prognosis of patients with coma in pediatric intensive care unit

The aim of this study was to assess the bedside brain function monitoring of color density spectral array (CDSA) for early prognostic evaluation of coma patients in pediatric intensive care unit (PICU).Forty-two consecutive pediatric coma patients were enrolled. The individual conscious state was evaluated according to the Glasgow coma scale (GCS). CDSA parameters including CDSA pattern (CDSAP), sleep-wake cycle (SWC), sleep stage (SS), and drug-induced fast wave activity (DIFWA) were recorded. Three months later, prognosis was evaluated according to pediatric cerebral performance category (PCPC) score, based on which the patients were divided into FP-group (favorable prognosis) and PP-group (poor prognosis).The changeable type of CDSAP, appearance of SWC, SS, and DIFWA were significantly correlated with favorable prognosis. Both GCS and SWC were significantly correlated with the prognosis. However, there was substantial overlap in GCS between FP-group and PP-group. Although the absence of SWC was statistically an independent risk factor for poor prognosis but with a high false positive rate (0.143), a linear logistic regression showed the odds ratio of GCS for predicting prognosis was 0.93 (95% confidence interval: 0.48-1.80; P = .83) and that of SWC was 0.12 (95% confidence interval: 0.03-0.47; P = .03). Furthermore, the absence of SWC was correlated with poor prognosis in nonintracranial infection patients.Our study found that several CDSA factors are associated with prognosis of coma patients in PICU. SWC may be a potential indicator for evaluating the prognosis of coma patients in PICU.

Parametric Description of EEG Profiles for Assessment of Sleep Architecture in Disorders of Consciousness

We propose a fully parametric approach to the assessment of sleep architecture, based upon the classical electroencephalographic criteria, applicable also to the recordings of patients with disorders of consciousness (DOC). Sleep spindles and slow waves are automatically detected from the matching pursuit decomposition of overnight EEG recordings. Their evolution can be presented in the form of EEG profiles, yielding a continuous description of sleep architecture, compatible with the classical criteria used in sleep staging. We propose assessment of these EEG profiles by five parameters, which can be combined by a linear classifier, assessing the quality of sleep architecture. Proposed methodology is evaluated on 59 overnight EEG recordings from 19 patients from a hospital for children with severe brain damage, in relation to their behavioral diagnosis according to the Coma Recovery Scale-Revised. Presented results indicate robustness of the proposed approach, which may serve as a valuable aid in diagnosis of DOC patients. Complete software environment for computing and presentation of EEG profiles is freely available from http://svarog.pl .

Daytime Central Thalamic Deep Brain Stimulation Modulates Sleep Dynamics in the Severely Injured Brain: Mechanistic Insights and a Novel Framework for Alpha-Delta Sleep Generation

Loss of organized sleep electrophysiology is a characteristic finding following severe brain injury. The return of structured elements of sleep architecture has been associated with positive prognosis across injury etiologies, suggesting a role for sleep dynamics as biomarkers of wakeful neuronal circuit function. In a continuing study of one minimally conscious state patient studied over the course of ~8½ years, we sought to investigate whether changes in daytime brain activation induced by central thalamic deep brain stimulation (CT-DBS) influenced sleep electrophysiology. In this patient subject, we previously reported significant improvements in sleep electrophysiology during 5½ years of CT-DBS treatment, including increased sleep spindle frequency and SWS delta power. We now present novel findings that many of these improvements in sleep electrophysiology regress following CT-DBS discontinuation; these regressions in sleep features correlate with a significant decrease in behavioral responsiveness. We also observe the re-emergence of alpha-delta sleep, which had been previously suppressed by daytime CT-DBS in this patient subject. Importantly, CT-DBS was only active during the daytime and has been proposed to mediate recovery of consciousness by driving synaptic activity across frontostriatal systems through the enhancement of thalamocortical output. Accordingly, the improvement of sleep dynamics during daytime CT-DBS and their subsequent regression following CT-DBS discontinuation implicates wakeful synaptic activity as a robust modulator of sleep electrophysiology. We interpret these findings in the context of the “synaptic homeostasis hypothesis,” whereby we propose that daytime upregulation of thalamocortical output in the severely injured brain may facilitate organized frontocortical circuit activation and yield net synaptic potentiation during wakefulness, providing a homeostatic drive that reconstitutes sleep dynamics over time. Furthermore, we consider common large-scale network dynamics across several neuropsychiatric disorders in which alpha-delta sleep has been documented, allowing us to formulate a novel mechanistic framework for alpha-delta sleep generation. We conclude that the bi-directional modulation of sleep electrophysiology by daytime thalamocortical activity in the severely injured brain: (1) emphasizes the cyclical carry-over effects of state-dependent circuit activation on large-scale brain dynamics, and (2) further implicates sleep electrophysiology as a sensitive indicator of wakeful brain activation and covert functional recovery in the severely injured brain.

Early rehabilitation of Disorders of Consciousness (DOC): management, neuropsychological evaluation and treatment

In order to ensure the best possible rehabilitation plan and best outcome for patients with Disorders of Consciousness (DOC), optimal management of the early phase of rehabilitation is fundamental. This includes a correct diagnosis, accurate assessment of the patient's state of alertness and the main comorbidities, appropriate neurophysiological and neuroradiology examinations, and education of the caregiver and family so that they can provide the best assistance. Thirty years ago, specialists first began applying a systematic approach to the rehabilitation of patients with DOC, but still today many problems remain unsolved: the rate of misdiagnosis is still high, and recommendations about the most appropriate mode of rehabilitation are lacking, both as regards the timing of interventions and what the best techniques to use are. In a medical sector where nosography has changed over the last decade and where the documented evidence, though increasing, still remains insufficient, we discuss in this brief review the main assessment tools and disability scales to use and the key issues that need to be considered when a patient with DOC is admitted to the rehabilitation unit and decisions about the early rehabilitation plan are made.

A Systematic Review and Meta-Analysis of the Relationship Between Brain Data and the Outcome in Disorders of Consciousness

A systematic search revealed 68 empirical studies of neurophysiological [EEG, event-related brain potential (ERP), fMRI, PET] variables as potential outcome predictors in patients with Disorders of Consciousness (diagnoses Unresponsive Wakefulness Syndrome [UWS] and Minimally Conscious State [MCS]). Data of 47 publications could be presented in a quantitative manner and systematically reviewed. Insufficient power and the lack of an appropriate description of patient selection each characterized about a half of all publications. In more than 80% studies, neurologists who evaluated the patients' outcomes were familiar with the results of neurophysiological tests conducted before, and may, therefore, have been influenced by this knowledge. In most subsamples of datasets, effect size significantly correlated with its standard error, indicating publication bias toward positive results. Neurophysiological data predicted the transition from UWS to MCS substantially better than they predicted the recovery of consciousness (i.e., the transition from UWS or MCS to exit-MCS). A meta-analysis was carried out for predictor groups including at least three independent studies with N > 10 per predictor per improvement criterion (i.e., transition to MCS versus recovery). Oscillatory EEG responses were the only predictor group whose effect attained significance for both improvement criteria. Other perspective variables, whose true prognostic value should be explored in future studies, are sleep spindles in the EEG and the somatosensory cortical response N20. Contrary to what could be expected on the basis of neuroscience theory, the poorest prognostic effects were shown for fMRI responses to stimulation and for the ERP component P300. The meta-analytic results should be regarded as preliminary given the presence of numerous biases in the data.

Sleep patterns associated with the severity of impairment in a large cohort of patients with chronic disorders of consciousness

OBJECTIVE

We assessed sleep patterns in 85 patients with chronic disorders of consciousness (DOC) in order to reveal any relationship with the degree of the impairment.

METHODS

Nocturnal polysomnography (PSG) was scored in patients classified as being in an unresponsive wakefulness syndrome/vegetative state (UWS/VS; n = 49) or a minimally conscious state (MCS; n = 36) in accordance with the rules of the American Academy of Sleep Medicine. The PSG data in the two diagnostic groups were compared, and the PSG parameters associated with the degree of impairment were analysed.

RESULTS

In 19/49 UWS/VS patients, signal attenuation was the only EEG pattern detectable in sleep. Non-REM 2 (NREM2) and slow-wave sleep (SWS) (but not REM) stages were more frequent in the MCS patients. The presence of SWS was the most appropriate factor for classifying patients as UWS/VS or MCS, and the duration of SWS was the main factor that significantly correlated with revised Coma Recovery Scale scores.

CONCLUSION

The presence of NREM sleep (namely SWS) reflects better preservation of the circuitry and structures needed to sustain this stage of sleep in DOC patients.

SIGNIFICANCE

PSG is a simple and effective technique, and sleep patterns may reflect the degree of impairment in chronic DOC patients.

Period3 gene in disorder of consciousness: The role of neuroimaging in understanding the relationship between genotype and sleep. A brief communication

BACKGROUND

Several methodologies including neuroimaging and sleep evaluation are being developed to complement the clinical bedside examinations in patients with disorder of consciousness (DOC). Recently, we demonstrated a possible association between Period3 (Per3) variable number tandem repeat (VNTR) polymorphism and functional impairment of DOC patients, speculating a possible role of this gene in sleep regulation.

AIM

To assess whether the degree of structural and metabolic damage of the main brain areas involved in the sleep generation and homeostasis may influence the different outcome of DOC patients carrying the Per3^5/5 genotype in comparison to Per3^4/4 ones.

METHODS

For the present study, we reviewed 44 DOC patients from the Coma Research Centre of the Fondazione IRCCS Istituto Neurologico "C. Besta" of Milan. All patients underwent to polysomnographic sleep evaluation, cerebral structural magnetic resonance imaging (MRI) and ¹⁸F-fluoro-2-deoxyglucose positron emission tomography (FDG-PET) analysis.

RESULTS

Our DOC patients presented a moderate anatomical (median score 2) and metabolic damage (median value 2.36 SUVmean) of the sleep areas at both MRI and FDG-PET evaluation. Total sleep time seemed to be higher in 5/5 genotype DOC patients (median value Per3^5/5, 221min, range 126-323min; median value Per3^4/4, 167min, range 36-477min; and median value Per3^4/5, 187min, range 29-422min). However, the MRI scores and FDG-PET values of whole brain, overall sleep areas, hypothalamus, midbrain and thalamus did not differ by genotype distribution.

CONCLUSION

Although limited by the small sample size, our data might support the idea that Per3 genetic predisposition in DOC patients could affect impairment and residual cognitive functions through sleep homeostasis independently from structural and/or metabolic integrity of sleep areas.

A Review of Resting-State Electroencephalography Analysis in Disorders of Consciousness

Recently, neuroimaging technologies have been developed as important methods for assessing the brain condition of patients with disorders of consciousness (DOC). Among these technologies, resting-state electroencephalography (EEG) recording and analysis has been widely applied by clinicians due to its relatively low cost and convenience. EEG reflects the electrical activity of the underlying neurons, and it contains information regarding neuronal population oscillations, the information flow pathway, and neural activity networks. Some features derived from EEG signal processing methods have been proposed to describe the electrical features of the brain with DOC. The computation of these features is challenging for clinicians working to comprehend the corresponding physiological meanings and then to put them into clinical applications. This paper reviews studies that analyze spontaneous EEG of DOC, with the purpose of diagnosis, prognosis, and evaluation of brain interventions. It is expected that this review will promote our understanding of the EEG characteristics in DOC.

Coherence in P300 as a predictor for the recovery from disorders of consciousness

Accurate and reliable prognostic judgments for disorders of consciousness (DOCs) can provide useful information for clinicians in the establishment of appropriate care plan, and may affect end-of-life decisions of caregivers. But until now no certain or standardized prognostic indicator has been constructed to predict the probability of awareness recovery. This study aims to assess higher-order cortical information processing in DOCs by event-related potential (ERP) and determine the value of P300 to predict the long-term prognosis. Two locked-in (LIS) patients and eighteen DOCs were evaluated with a hierarchical cognitive assessment by ERP. We used subject's own name (SON) as a deviant stimulus, 1000Hz tone and subject's derived name (SDN) as a standard stimulus in two paradigms respectively. P300 elicited by SON was used to assess the information processing. The patients' clinical outcomes were followed up at 2, 6 and 12 months after ERP recordings. The results showed that a P300 component was observed in both paradigms in two LIS patients. All of MCS and four out of nine UWS/VS showed an intact P300 in either paradigm. All of the five patients with P300 in both paradigms were finally awake after 12 months, while none of the eight patients without P300 regained consciousness. A highly significant relationship between P300 and subsequent recovery was found. The results provide evidence that P300 in the hierarchical bedside neurophysiologic oddball procedure can accurately characterize the level of cognitive preservation, and may serve as an alternative tool to predict the likelihood of recovery of DOCs.

Night sleep in patients with vegetative state

Polysomnographic recording of night sleep was carried out in 15 patients with the diagnosis vegetative state (syn. unresponsive wakefulness syndrome). Sleep scoring was performed by three raters, and confirmed by means of a spectral power analysis of the electroencephalogram, electrooculogram and electromyogram. All patients but one exhibited at least some signs of sleep. In particular, sleep stage N1 was found in 13 patients, N2 in 14 patients, N3 in nine patients, and rapid eye movement sleep in 10 patients. Three patients exhibited all phenomena characteristic for normal sleep, including spindles and rapid eye movements. However, in all but one patient, sleep patterns were severely disturbed as compared with normative data. All patients had frequent and long periods of wakefulness during the night. In some apparent rapid eye movement sleep episodes, no eye movements were recorded. Sleep spindles were detected in five patients only, and their density was very low. We conclude that the majority of vegetative state patients retain some important circadian changes. Further studies are necessary to disentangle multiple factors potentially affecting sleep pattern of vegetative state patients.

Night and day variations of sleep in patients with disorders of consciousness

Brain injuries substantially change the entire landscape of oscillatory dynamics and render detection of typical sleep patterns difficult. Yet, sleep is characterized not only by specific EEG waveforms, but also by its circadian organization. In the present study we investigated whether brain dynamics of patients with disorders of consciousness systematically change between day and night. We recorded ~24 h EEG at the bedside of 18 patients diagnosed to be vigilant but unaware (Unresponsive Wakefulness Syndrome) and 17 patients revealing signs of fluctuating consciousness (Minimally Conscious State). The day-to-night changes in (i) spectral power, (ii) sleep-specific oscillatory patterns and (iii) signal complexity were analyzed and compared to 26 healthy control subjects. Surprisingly, the prevalence of sleep spindles and slow waves did not systematically vary between day and night in patients, whereas day-night changes in EEG power spectra and signal complexity were revealed in minimally conscious but not unaware patients.