Score on Coma Recovery Scale-Revised at admission predicts outcome at discharge in intensive rehabilitation after severe brain injury

Prognosis of patients with prolonged disorders of consciousness after brain injury: a longitudinal cohort study

Background

The findings regarding the prognosis of prolonged disorders of consciousness (PDOC) vary widely among different studies. This study aims to investigate the mortality, consciousness recovery and disabilities of patients with PDOC after brain injury.

Methods

A total of 204 patients with PDOC were included in a longitudinal cohort study, including 129 males and 75 females. There were 112 cases of traumatic brain injury (TBI), 62 cases of cerebral hemorrhage (CH), 13 cases of cerebral infarction (CI) and 17 cases of ischemic hypoxic encephalopathy (IHE). The status of consciousness at 1, 2, 3, 6, 12, 18, 24, 36, 48 months of the disease course was assessed or followed up using the Revised Coma Recovery Scale (CRS-R). If the patients were conscious, the disability Rating Scale (DRS) was also performed. The prognosis of different PDOC including coma, vegetative state (VS) and minimal conscious state (MCS) was analyzed. The survival patients were screened for variables and included in multivariate binary Logistic regression to screen the factors affecting the recovery of consciousness.

Results

The mortality rates at 12, 24, 36, and 48 months were 10.7, 23.4, 38.9, and 68.4%, respectively. The median time of death was 18 months (8.75, 29). The probability of MCS regaining consciousness was higher than VS (p < 0.05), with the degree of disability left lower than VS (p < 0.05). There was no significant difference between MCS- and MCS+ groups in terms of the probability of regaining consciousness, the extent of residual disability, and mortality rates (p > 0.05). The mortality rate of coma was higher than that of other PDOC (p < 0.05). The mortality rate of MCS was lower than that of VS, but the difference was not statistically significant (p > 0.05). The probability of consciousness recovery after TBI was the highest and the mortality rate was the lowest. The possibility of consciousness recovery in IHE was the least, and the mortality rate of CI was the highest. The cause of brain injury and initial CRS-R score were the factors affecting the consciousness recovery of patients (p < 0.05).

Conclusion

The prognosis of MCS is more favorable than VS, with comparable outcomes between MCS- and MCS+, while comatose patients was the poorest. TBI has the best prognosis and IHE has the worst prognosis.

Establishment and validation of a bad outcomes prediction model based on EEG and clinical parameters in prolonged disorder of consciousness

Objective

This study aimed to explore the electroencephalogram (EEG) indicators and clinical factors that may lead to poor prognosis in patients with prolonged disorder of consciousness (pDOC), and establish and verify a clinical predictive model based on these factors.

Methods

This study included 134 patients suffering from prolonged disorder of consciousness enrolled in our department of neurosurgery. We collected the data of sex, age, etiology, coma recovery scales (CRS-R) score, complications, blood routine, liver function, coagulation and other laboratory tests, resting EEG data and follow-up after discharge. These patients were divided into two groups: training set (n = 107) and verification set (n = 27). These patients were divided into a training set of 107 and a validation set of 27 for this study. Univariate and multivariate regression analysis were used to determine the factors affecting the poor prognosis of pDOC and to establish nomogram model. We use the receiver operating characteristic (ROC) and calibration curves to quantitatively test the effectiveness of the training set and the verification set. In order to further verify the clinical practical value of the model, we use decision curve analysis (DCA) to evaluate the model.

Result

The results from univariate and multivariate logistic regression analyses suggested that an increased frequency of occurrence microstate A, reduced CRS-R scores at the time of admission, the presence of episodes associated with paroxysmal sympathetic hyperactivity (PSH), and decreased fibrinogen levels all function as independent prognostic factors. These factors were used to construct the nomogram. The training and verification sets had areas under the curve of 0.854 and 0.920, respectively. Calibration curves and DCA demonstrated good model performance and significant clinical benefits in both sets.

Conclusion

This study is based on the use of clinically available and low-cost clinical indicators combined with EEG to construct a highly applicable and accurate model for predicting the adverse prognosis of patients with prolonged disorder of consciousness. It provides an objective and reliable tool for clinicians to evaluate the prognosis of prolonged disorder of consciousness, and helps clinicians to provide personalized clinical care and decision-making for patients with prolonged disorder of consciousness and their families.

Predicting outcome in disorders of consciousness: A mega-analysis

OBJECTIVE

Assessing recovery potential in patients with disorders of consciousness (DoC) is pivotal for guiding clinical and ethical decisions. We conducted a mega-analysis of individual patient data to understand (1) if a time threshold exists, beyond which regaining consciousness is almost impossible, and (2) how recovery varies based on factors such as diagnosis, etiology, age, sex, and neuropsychological status.

METHODS

A systematic literature search revealed a total of 3290 patients. In this sample, we performed a Cox proportional hazards analysis for interval censored data.

RESULTS

We observed a late saturation of probability to regain consciousness in Kaplan-Meier curves, and the annual rate of recovery was remarkably stable, in that approximately 35% of patients regained consciousness per year. Patients in minimally conscious state (MCS) recovered more frequently than patients in unresponsive wakefulness syndrome (UWS). No significant difference was observed between the recovery dynamics of MCS subgroups: MCS+ and MCS-. Patients with hypoxic brain lesions showed worse recovery rate than patients with traumatic brain injury and patients with vascular brain lesions, while the latter two categories did not differ from each other. Male patients had moderately better chance to regain consciousness. While younger UWS patients recovered more frequently than older patients, it was not the case in MCS.

INTERPRETATION

Our findings highlight the necessity for neurologists to exercise caution when making negative predictions in individual cases, challenge traditional beliefs regarding recovery timelines, and underscore the importance of conducting detailed and prolonged assessments to better understand recovery prospects in DoC.

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.

Reliability and validation of the Japanese version of the coma recovery scale-revised (CRS-R)

PRIMARY OBJECTIVE

This study aimed to verify the reliability and validity of the Japanese version of the Coma Recovery Scale-Revised (CRS-R).

METHODS

Subjects included 59 patients with disorders of consciousness (DOC) due to acquired brain injury. To validate test-retest reliability, Evaluator A assessed the CRS-R twice on the same day (A1, A2). To examine inter-rater reliability, Evaluators A (A2) and B (B) assessed the CRS-R without a time interval. To test concurrent validity, Evaluator A (A1) assessed the CRS-R, Japan Coma Scale (JCS), and the Glasgow Coma Scale (GCS) consecutively. To validate diagnostic accuracy, we evaluated the degree of agreement between A1 and A2 and between A2 and B in their diagnosis of DOC by CRS-R.

RESULTS

The test-retest (ρ = 0.92) and inter- (ρ = 0.98) reliability of CRS-R were excellent" and Concurrent validity of CRS-R with JCS (ρ =  -0.82) and GCS (ρ = 0.92) were high. Results of DOC diagnosis were consistent for 48/59 cases (κ = 0.82) for A1 and A2 and for 54/59 cases (κ = 0.92) for A2 and B.

CONLCUSION

The Japanese version of the CRS-R may be as reliable and valid as the original English and other language versions.

[Diagnostic criteria for prolonged and chronic disturbances of consciousness after aneurysmal subarachnoid hemorrhages]

BACKGROUND

In recent years, prolonged states of impaired consciousness became widespread among patients with aneurysmal subarachnoid hemorrhage. Treatment and maintenance of vital functions in such patients represent a complex medical, economic and social problem. In this regard, searching for the causes of prolonged states of impaired consciousness and predicting the outcomes are important.

OBJECTIVE

To analyze available literature data on prevention and treatment of prolonged states of impaired consciousness after aneurysmal subarachnoid hemorrhage.

RESULTS

We reviewed the PubMed database using the keywords «unresponsive wakefulness syndrome», «persistent vegetative state2, «minimal consciousness state» and «outcome of subarachnoid hemorrhage». Only 4 reports devoted to the causes and treatment outcomes in patients with prolonged impairment of consciousness after aneurysmal subarachnoid hemorrhage were found. At the same time, patients with aneurysmal subarachnoid hemorrhage comprise up to 11% among all cases of prolonged states of impaired consciousness. Examination, management and treatment of patients with prolonged impairment of consciousness after aneurysmal subarachnoid hemorrhage are carried out according to general principles without taking into account specific etiological and pathogenetic factors.

CONCLUSION

Increased number of patients with prolonged impairment of consciousness after aneurysmal subarachnoid hemorrhage necessitates analysis of etiopathogenesis and outcomes of these disorders based on modern clinical, instrumental and laboratory assessment of the brain.

Assessing consciousness and cognition in disorders of consciousness

Detecting willful cognition in these patients is known to be challenging due to the patients' motor disabilities and high vigilance fluctuations but also due to the lack of expertise and use of adequate tools to assess these patients in specific settings. This review will discuss the main disorders of consciousness after severe brain injury, how to assess consciousness and cognition in these patients, as well as the challenges and tools available to overcome these challenges and reach an accurate diagnosis.

Coma Recovery Scale-Revised Predicts Disability Rating Scale in Acute Rehabilitation of Severe Traumatic Brain Injury

OBJECTIVE

To explore the prognostic value of the Coma Recovery Scale-Revised (CRS-R) in predicting disability outcomes in patients with severe traumatic brain injury using the Disability Rating Scale (DRS).

DESIGN

Secondary analysis including linear and logistic regressions were performed.

SETTING

Data were collected in a previous clinical trial.

PARTICIPANTS

One hundred eighty-four participants across 3 countries (N=184).

MAIN OUTCOME MEASURES

Disability Rating Scales.

RESULTS

Analyses showed an inverse relation between CRS-R scores obtained at baseline and change in DRS scores at 6 weeks. Similarly, changes in CRS-R scores between baseline and 4 weeks were also found to have an inverse relation to change in DRS scores at 6 weeks.

CONCLUSIONS

This study generates a tool that can be used to predict the probability that a patient with severe traumatic brain injury lands in 1 of 3 disability categories. The CRS-R may be useful in prognostication of disability in patients with severe traumatic brain injury.

Heart rate variability for the evaluation of patients with disorders of consciousness

OBJECTIVE

Clinical responsiveness of patients with a Disorder of Consciousness (DoC) correlates to sympathetic/parasympathetic homeostatic balance. Heart Rate Variability (HRV) metrics result in non-invasive proxies of modulation capabilities of visceral states. In this work, our aim was to evaluate whether HRV measures could improve the differential diagnosis between Unresponsive Wakefulness Syndrome (UWS) and Minimally Conscious State (MCS) with respect to multivariate models based on standard clinical electroencephalography (EEG) labeling only in a rehabilitation setting.

METHODS

A prospective observational study was performed consecutively enrolling 82 DoC patients. Polygraphic recordings were performed. HRV-metrics and EEG descriptors derived from the American Clinical Neurophysiology Society's Standardized Critical Care terminology were included. Descriptors entered univariate and then multivariate logistic regressions with the target set to the UWS/MCS diagnosis.

RESULTS

HRV measures resulted significantly different between UWS and MCS patients, with higher values being associated with better consciousness levels. Specifically, adding HRV-related metrics to ACNS EEG descriptors increased the Nagelkerke R² from 0.350 (only EEG descriptors) to 0.565 (HRV-EEG combination) with the outcome set to the consciousness diagnosis.

CONCLUSIONS

HRV changes across the lowest states of consciousness. Rapid changes in heart rate, occurring in better consciousness levels, confirm the mutual correlation between visceral state functioning patterns and consciousness alterations.

SIGNIFICANCE

Quantitative analysis of heart rate in patients with a DoC paves the way for the implementation of low-cost pipelines supporting medical decisions within multimodal consciousness assessments.

A prediction model of clinical outcomes in prolonged disorders of consciousness: A prospective cohort study

Objective

This study aimed to establish and validate a prediction model for clinical outcomes in patients with prolonged disorders of consciousness (pDOC).

Methods

A total of 170 patients with pDOC enrolled in our rehabilitation unit were included and divided into training (n = 119) and validation sets (n = 51). Independent predictors for improved clinical outcomes were identified by univariate and multivariate logistic regression analyses, and a nomogram model was established. The nomogram performance was quantified using receiver operating curve (ROC) and calibration curves in the training and validated sets. A decision curve analysis (DCA) was performed to evaluate the clinical usefulness of this nomogram model.

Results

Univariate and multivariate logistic regression analyses indicated that age, diagnosis at entry, serum albumin (g/L), and pupillary reflex were the independent prognostic factors that were used to construct the nomogram. The area under the curve in the training and validation sets was 0.845 and 0.801, respectively. This nomogram model showed good calibration with good consistency between the actual and predicted probabilities of improved outcomes. The DCA demonstrated a higher net benefit in clinical decision-making compared to treating all or none.

Conclusion

Several feasible, cost-effective prognostic variables that are widely available in hospitals can provide an efficient and accurate prediction model for improved clinical outcomes and support clinicians to offer suitable clinical care and decision-making to patients with pDOC and their family members.

Can Respiration Complexity Help the Diagnosis of Disorders of Consciousness in Rehabilitation?

BACKGROUND

Autonomic Nervous System (ANS) activity, as cardiac, respiratory and electrodermal activity, has been shown to provide specific information on different consciousness states. Respiration rates (RRs) are considered indicators of ANS activity and breathing patterns are currently already included in the evaluation of patients in critical care.

OBJECTIVE

The aim of this work was to derive a proxy of autonomic functions via the RR variability and compare its diagnostic capability with known neurophysiological biomarkers of consciousness.

METHODS

In a cohort of sub-acute patients with brain injury during post-acute rehabilitation, polygraphy (ECG, EEG) recordings were collected. The EEG was labeled via descriptors based on American Clinical Neurophysiology Society terminology and the respiration variability was extracted by computing the Approximate Entropy (ApEN) of the ECG-derived respiration signal. Competing logistic regressions were applied to evaluate the improvement in model performances introduced by the RR ApEN.

RESULTS

Higher RR complexity was significantly associated with higher consciousness levels and improved diagnostic models' performances in contrast to the ones built with only electroencephalographic descriptors.

CONCLUSIONS

Adding a quantitative, instrumentally based complexity measure of RR variability to multimodal consciousness assessment protocols may improve diagnostic accuracy based only on electroencephalographic descriptors. Overall, this study promotes the integration of biomarkers derived from the central and the autonomous nervous system for the most comprehensive diagnosis of consciousness in a rehabilitation setting.

Long-Term Outcomes among Patients with Prolonged Disorders of Consciousness

PURPOSE

To evaluate the long-term survival and functional outcomes of patients with prolonged disorders of consciousness (pDoC) 1-8 years after brain injuries.

METHODS

Retrospective study to assess the long-term survival and functional outcomes of patients with pDoC was conducted. We performed Cox regression and multivariate logistic regression to calculate hazard ratios (HRs) for the outcome of survival and to identify risk factors of the functional outcome.

RESULTS

We recruited 154 patients with pDoC. The duration of follow-up from disease onset was 1-8 years. The median age was 46 years (IQR, 32-59), and 65.6% (n = 101) of them were men. During the follow-up period, one hundred and ten patients (71.4%) survived; among them, 52 patients had a good outcome. From the overall survival curve, the 1-, 3-, and 8-year survival rates of patients were about 80.5%, 72.0%, and 69.7%, respectively. Cox regression analysis revealed a significant association between the lower APACHE II score (p = 0.005) (cut-off score ≥ 18) and the presence of sleep spindles (p = 0.001) with survival. Logistic regression analysis demonstrated a higher CRS-R score (cut-off score ≥ 7), and presence of sleep spindles were related to a favorable outcome among patients with pDoC.

CONCLUSIONS

Sleep spindles are correlated with both long-term survival and long-term functional outcome in pDoC patients.

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.

Predicting Long-Term Recovery of Consciousness in Prolonged Disorders of Consciousness Based on Coma Recovery Scale-Revised Subscores: Validation of a Machine Learning-Based Prognostic Index

Prognosis of prolonged Disorders of Consciousness (pDoC) is influenced by patients' clinical diagnosis and Coma Recovery Scale-Revised (CRS-R) total score. We compared the prognostic accuracy of a novel Consciousness Domain Index (CDI) with that of clinical diagnosis and CRS-R total score, for recovery of full consciousness at 6-, 12-, and 24-months post-injury. The CDI was obtained by a combination of the six CRS-R subscales via an unsupervised machine learning technique. We retrospectively analyzed data on 143 patients with pDoC (75 in Minimally Conscious State; 102 males; median age = 53 years; IQR = 35; time post-injury = 1-3 months) due to different etiologies enrolled in an International Brain Injury Association Disorders of Consciousness Special Interest Group (IBIA DoC-SIG) multicenter longitudinal study. Univariate and multivariate analyses were utilized to assess the association between outcomes and the CDI, compared to clinical diagnosis and CRS-R. The CDI, the clinical diagnosis, and the CRS-R total score were significantly associated with a good outcome at 6, 12 and 24 months. The CDI showed the highest univariate prediction accuracy and sensitivity, and regression models including the CDI provided the highest values of explained variance. A combined scoring system of the CRS-R subscales by unsupervised machine learning may improve clinical ability to predict recovery of consciousness in patients with pDoC.

Prognosis of Chronically Ventilated Patients in a Long-Term Ventilation Facility: Association with Age, Consciousness and Cognitive State

Background: The number of adults requiring prolonged mechanical ventilation (PMV) including those with cognitive impairment or disorders of consciousness is escalating. We aimed to compare in a long-term acute care hospital (LTACH) mortality and length of stay (LOS) among three age groups (40-59y, 60-79y, ≥80y) of hospitalized PMV patients, and according to consciousness and cognitive state at admission. Methods: We obtained data from the health records of 308 adults aged ≥40 years requiring PMV hospitalized at a Chronic Ventilator Dependent Unit in a LTACH between 01/01/2015 to 06/30/2019 and followed-up until discharge or death or until 12/31/2019. Results: At admission to LTACH, 42.2% of PMV patients were in a vegetative state/ minimally conscious state (VS/MCS); 32.5% were severely cognitively impaired, 11.0% were mildly to moderately cognitively impaired, 12.3% had no cognitive impairment, and 1.9% had intellectual disability/psychiatric disorder. In-LTACH LOS (months) decreased from 34.6 ± 42.6 at age 40-59y, 19.1 ± 22.3 at 60-79y to 14.4 ± 19.3 at age ≥80y (p = .006). In-LTACH mortality was 30.6% for 40-59y, 41.1% for 60-79y and 54.8% for age ≥80y. In-LTACH LOS (months) was 23.8 ± 30.7 for VS/MCS, 15.1 ± 19.5 for the severely cognitively impaired, 10.0 ± 12.8 for mild to moderate cognitive impairment and 18.9 ± 21.9 for those without cognitive impairment (p = .02). In-LTACH mortality was 50.8% for VS/MCS, 58.0% for the severely cognitively impaired, 26.5% for mild to moderate cognitive impairment and 13.2% for those without cognitive impairment (p < .001). Conclusion: In this population requiring PMV, mortality and in-LTACH LOS worsened with age. In-LTACH LOS was longest for VS/MCS patients, who had a mean survival of about two years, followed by those without cognitive impairment and then those with severe cognitive impairment. Mortality was associated with worse consciousness and cognitive state. These findings highlight the importance of discussing end-of-life decisions with patients and family members regarding resuscitation/intubation and the long-term management of these patients.

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.

Predicting outcome of patients with prolonged disorders of consciousness using machine learning models based on medical complexity

Patients with severe acquired brain injury and prolonged disorders of consciousness (pDoC) are characterized by high clinical complexity and high risk to develop medical complications. The present multi-center longitudinal study aimed at investigating the impact of medical complications on the prediction of clinical outcome by means of machine learning models. Patients with pDoC were consecutively enrolled at admission in 23 intensive neurorehabilitation units (IRU) and followed-up at 6 months from onset via the Glasgow Outcome Scale-Extended (GOSE). Demographic and clinical data at study entry and medical complications developed within 3 months from admission were collected. Machine learning models were developed, targeting neurological outcomes at 6 months from brain injury using data collected at admission. Then, after concatenating predictions of such models to the medical complications collected within 3 months, a cascade model was developed. One hundred seventy six patients with pDoC (M: 123, median age 60.2 years) were included in the analysis. At admission, the best performing solution (k-Nearest Neighbors regression, KNN) resulted in a median validation error of 0.59 points [IQR 0.14] and a classification accuracy of dichotomized GOS-E of 88.6%. Coherently, at 3 months, the best model resulted in a median validation error of 0.49 points [IQR 0.11] and a classification accuracy of 92.6%. Interpreting the admission KNN showed how the negative effect of older age is strengthened when patients' communication levels are high and ameliorated when no communication is present. The model trained at 3 months showed appropriate adaptation of the admission prediction according to the severity of the developed medical complexity in the first 3 months. In this work, we developed and cross-validated an interpretable decision support tool capable of distinguishing patients which will reach sufficient independence levels at 6 months (GOS-E > 4). Furthermore, we provide an updated prediction at 3 months, keeping in consideration the rehabilitative path and the risen medical complexity.

Consciousness-Domain Index: a data-driven clustering-based consciousness labeling

Assessing consciousness results in one of the most complex neurological diagnosis. Even more complex and uncertain is prognosticating on consciousness recovery. Currently, consciousness is assessed by using a six-items scale, the Coma Recovery Scale-Revised. Namely, scores on the sub-items can individually assign or not a specific level of consciousness to a patient. In our work, by using solely the six sub-items of the CRS-R, we implemented a clustering algorithm labeling patients with the Consciousness-Domains Index (CDI) starting from a dataset of 190 patients with a Disorder of Consciousness (DoC). Then, the CDI is compared with the clinical state at admission and at six months via univariate analysis. The number of clusters best dividing the groups resulted equal to two and the most influencing sub-items resulted the visual and motor one. The CDI closely resembles the clinical state at admission (CSA) (Cohen's k=0.85). On the other hand, when comparing CDI and CSA, a net improvement was found in the prognostic power of the neurological outcome at six months, targeted as presence/absence of a DoC ( ). Data-driven techniques pave the way for automated and model-based search of prognostic factors, together with the use of such prognostic factors in multivariate prognostic models. Future works will address the external validation of the CDI, together with the inclusion of the CDI in a multivariate supervised model, in order to assess the true potential of such novel index. Clinical Relevance- A completely data-driven index was derived from a clustering of CRS-R sub-items. It correlates with the neurological outcome at six months better than the state of consciousness at admission.

Merging Clinical and EEG Biomarkers in an Elastic-Net Regression for Disorder of Consciousness Prognosis Prediction

Patients with Disorder of Consciousness (DoC) entering Intensive Rehabilitation Units after a severe Acquired Brain Injury have a highly variable evolution of the state of consciousness which is a complex aspect to predict. Besides clinical factors, electroencephalography has clearly shown its potential into the identification of prognostic biomarkers of consciousness recovery. In this retrospective study, with a dataset of 271 patients with DoC, we proposed three different Elastic-Net regressors trained on different datasets to predict the Coma Recovery Scale-Revised value at discharge based on data collected at admission. One dataset was completely EEG-based, one solely clinical data-based and the last was composed by the union of the two. Each model was optimized, validated and tested with a robust nested cross-validation pipeline. The best models resulted in a median absolute test error of 4.54 [IQR = 4.56], 3.39 [IQR = 4.36], 3.16 [IQR = 4.13] for respectively the EEG, clinical and hybrid model. Furthermore, the hybrid model for what concerns overcoming an unresponsive wakefulness state and exiting a DoC results in an AUC of 0.91 and 0.88 respectively. Small but useful improvements are added by the EEG dataset to the clinical model for what concerns overcoming an unresponsive wakefulness state. Data-driven techniques and namely, machine learning models are hereby shown to be capable of supporting the complex decision-making process the practitioners must face.

Behavioral Assessment of Patients with Disorders of Consciousness

Severe brain injury is associated with a period of impaired level of consciousness that can last from days to months and results in chronic impairment. Systematic assessment of level of function in patients with disorders of consciousness (DoC) is critical for diagnosis, prognostication, and evaluation of treatment efficacy. Approximately 40% of patients who are thought to be unconscious based on clinical bedside behavioral assessment demonstrate some signs of consciousness on standardized behavioral assessment. This finding, in addition to a growing body of literature demonstrating the advantages of standardized behavioral assessment of DoC, has led multiple professional societies and clinical guidelines to recommend standardized assessment over routine clinical evaluation of consciousness. Nevertheless, even standardized assessment is susceptible to biases and misdiagnosis, and examiners should consider factors, such as fluctuating arousal and aphasia, that may confound evaluation. We review approaches to behavioral assessment of consciousness, recent clinical guideline recommendations for use of specific measures to evaluate patients with DoC, and strategies for mitigating common biases that may confound the examination.

Clinical, Neurophysiological, and Genetic Predictors of Recovery in Patients With Severe Acquired Brain Injuries (PRABI): A Study Protocol for a Longitudinal Observational Study

Background

Due to continuous advances in intensive care technology and neurosurgical procedures, the number of survivors from severe acquired brain injuries (sABIs) has increased considerably, raising several delicate ethical issues. The heterogeneity and complex nature of the neurological damage of sABIs make the detection of predictive factors of a better outcome very challenging. Identifying the profile of those patients with better prospects of recovery will facilitate clinical and family choices and allow to personalize rehabilitation. This paper describes a multicenter prospective study protocol, to investigate outcomes and baseline predictors or biomarkers of functional recovery, on a large Italian cohort of sABI survivors undergoing postacute rehabilitation.

Methods

All patients with a diagnosis of sABI admitted to four intensive rehabilitation units (IRUs) within 4 months from the acute event, aged above 18, and providing informed consent, will be enrolled. No additional exclusion criteria will be considered. Measures will be taken at admission (T0), at three (T1) and 6 months (T2) from T0, and follow-up at 12 and 24 months from onset, including clinical and functional data, neurophysiological results, and analysis of neurogenetic biomarkers.

Statistics

Advanced machine learning algorithms will be cross validated to achieve data-driven prediction models. To assess the clinical applicability of the solutions obtained, the prediction of recovery milestones will be compared to the evaluation of a multiprofessional, interdisciplinary rehabilitation team, performed within 2 weeks from admission.

Discussion

Identifying the profiles of patients with a favorable prognosis would allow customization of rehabilitation strategies, to provide accurate information to the caregivers and, possibly, to optimize rehabilitation outcomes.

Conclusions

The application and validation of machine learning algorithms on a comprehensive pool of clinical, genetic, and neurophysiological data can pave the way toward the implementation of tools in support of the clinical prognosis for the rehabilitation pathways of patients after sABI.

Critical Illness Polyneuropathy and Myopathy and Clinical Detection of the Recovery of Consciousness in Severe Acquired Brain Injury Patients with Disorders of Consciousness after Rehabilitation

Background: Disorders of consciousness (DoCs) include unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS). Critical illness polyneuropathy and myopathy (CIPNM) is frequent in severe acquired brain injuries and impacts functional outcomes at discharge from the intensive rehabilitation unit (IRU). We investigated the prevalence of CIPNM in DoCs and its relationship with the consciousness assessment. Methods: Patients with DoCs were retrospectively selected from the database including patients admitted to the IRU of the IRCCS Don Gnocchi Foundation, Florence, from August 2012 to May 2020. Electroneurography/electromyography was performed at admission. Consciousness was assessed using the Coma Recovery Scale-Revised (CRS-R) at admission and discharge. Patients transitioning from a lower consciousness state to a higher one were classified as improved responsiveness (IR). Results: A total of 177 patients were included (UWS: 81 (45.8%); MCS: 96 (54.2%); 78 (44.1%) women; 67 years (IQR: 20). At admission, 108 (61.0%) patients had CIPNM. At discharge, 117 (66.1%) patients presented an IR. In the multivariate analysis, CRS-R at admission (p = 0.006; OR: 1.462) and CIPNM (p = 0.039; OR: −1.252) remained significantly associated with IR only for the UWS patients. Conclusions: CIPNM is frequent in DoCs and needs to be considered during the clinical consciousness assessment, especially in patients with UWS.

One-year outcome of brain injured patients undergoing early neurological rehabilitation: a prospective observational study

Background

The present study intended to analyze the outcome of patients with severe brain injury one-year after discharge from early rehabilitation.

Methods

Early neurological rehabilitation patients admitted to intensive or intermediate care units and discharged between June 2018 and May 2020 were screened for eligibility. The level of consciousness was evaluated using the Coma Recovery Scale-Revised (CRS-R) upon admission and at discharge. At one-year follow-up, the outcome was assessed with the Glasgow Outcome Scale-extended (GOSE). Demographical and clinical data collected during inpatient rehabilitation were used to predict the outcome 1 year after discharge.

Results

Two hundred sixty-four patients (174 males, 90 females) with a median age of 62 years (IQR = 51–75) and a median duration of their disease of 18 days (IQR = 12–28) were included in the study. At follow-up, the mortality rate was 27% (n = 71). Age and discharge CRS-R total score were independent predictors in a Cox proportional hazards model with death (yes/no) as the dependent variable. According to the GOSE interviews, most patients were either dead (n = 71; 27%), in a vegetative state (n = 28; 11%) or had a severe disability (n = 124; 47%), whereas only a few patients showed a moderate disability (n = 18; 7%) or a good recovery (n = 23; 9%) 1 year after discharge. Age, non-traumatic etiology, discharge CRS-R total score and length of stay independently predicted whether the outcome was good or poor at follow-up.

Conclusion

Age was an important predictor for outcome at one-year follow-up, which might be due to altered brain plasticity and more comorbidities in elderly subjects. In addition, the present study demonstrated that the CRS-R total score at discharge might be more important for the prediction of one-year outcome than the initial assessment upon admission.

The neuroethics of disorders of consciousness: a brief history of evolving ideas

Neuroethical questions raised by recent advances in the diagnosis and treatment of disorders of consciousness are rapidly expanding, increasingly relevant and yet underexplored. The aim of this thematic review is to provide a clinically applicable framework for understanding the current taxonomy of disorders of consciousness and to propose an approach to identifying and critically evaluating actionable neuroethical issues that are frequently encountered in research and clinical care for this vulnerable population. Increased awareness of these issues and clarity about opportunities for optimizing ethically responsible care in this domain are especially timely given recent surges in critically ill patients with prolonged disorders of consciousness associated with coronavirus disease 2019 around the world. We begin with an overview of the field of neuroethics: what it is, its history and evolution in the context of biomedical ethics at large. We then explore nomenclature used in disorders of consciousness, covering categories proposed by the American Academy of Neurology, the American Congress of Rehabilitation Medicine and the National Institute on Disability, Independent Living and Rehabilitation Research, including definitions of terms such as coma, the vegetative state, unresponsive wakefulness syndrome, minimally conscious state, covert consciousness and the confusional state. We discuss why these definitions matter, and why there has been such evolution in this nosology over the years, from Jennett and Plum in 1972 to the Multi-Society Task Force in 1994, the Aspen Working Group in 2002 and the 2018 American and 2020 European Disorders of Consciousness guidelines. We then move to a discussion of clinical aspects of disorders of consciousness, the natural history of recovery and ethical issues that arise within the context of caring for people with disorders of consciousness. We conclude with a discussion of key challenges associated with assessing residual consciousness in disorders of consciousness, potential solutions and future directions, including integration of crucial disability rights perspectives.

Risk factors for 2-year mortality in patients with prolonged disorders of consciousness: An international multicentre study

BACKGROUND AND PURPOSE

Patients with prolonged disorders of consciousness (pDoC) have a high mortality rate due to medical complications. Because an accurate prognosis is essential for decision-making on patients' management, we analysed data from an international multicentre prospective cohort study to evaluate 2-year mortality rate and bedside predictors of mortality.

METHODS

We enrolled adult patients in prolonged vegetative state/unresponsive wakefulness syndrome (VS/UWS) or minimally conscious state (MCS) after traumatic and nontraumatic brain injury within 3 months postinjury. At enrolment, we collected demographic (age, sex), anamnestic (aetiology, time postinjury), clinical (Coma Recovery Scale-Revised [CRS-R], Disability Rating Scale, Nociception Coma Scale-Revised), and neurophysiologic (electroencephalogram [EEG], somatosensory evoked and event-related potentials) data. Patients were followed up to gather data on mortality up to 24 months postinjury.

RESULTS

Among 143 traumatic (n = 55) and nontraumatic (n = 88) patients (VS/UWS, n = 68, 19 females; MCS, n = 75, 22 females), 41 (28.7%) died within 24 months postinjury. Mortality rate was higher in VS/UWS (42.6%) than in MCS (16%; p < 0.001). Multivariate regression in VS/UWS showed that significant predictors of mortality were older age and lower CRS-R total score, whereas in MCS female sex and absence of alpha rhythm on EEG at study entry were significant predictors.

CONCLUSIONS

This study demonstrated that a feasible multimodal assessment in the postacute phase can help clinicians to identify patients with pDoC at higher risk of mortality within 24 months after brain injury. This evidence can help clinicians and patients' families to navigate the complex clinical decision-making process and promote an international standardization of prognostic procedures for patients with pDoC.

Coma recovery scale: Key clinical tool ignored enough in disorders of consciousness

Background:

Disorders of consciousness (DoC) includes coma, vegetative state (VS), minimally conscious state (MCS), and emergence from the MCS. Aneurysmal rupture with high-grade SAH, traumatic brain injury, and neoplastic brain lesions are some of the frequent pathologies leading to DoC. The diagnostic errors among these DoC are as high as ranging from 25% to 45%, with a probable error in the conclusion of patients’ state, treatment choice, end-of-life decision-making, and prognosis. Some studies also reported that 37–43% of patients were misdiagnosed in VS while demonstrating signs of awareness. Despite its wide acceptance, Coma Recovery Scale-Revised (CRS-r) remained underused or inappropriately utilized, which may lead to substandard or unprofessional patient care. Literature is rare on the knowledge of CRS-r among physicians published from India and across the globe. Therefore, we carried out the present study to ascertain physicians’ knowledge on CRS-r and raise awareness about its justifiable clinical utilization. We also explored the factors associated with this perceived level of experience among participants and recommend frequent physicians’ training for care of patients with DoC.

Methods:

An institution-based cross-sectional online survey was conducted from June 8 to July 7, 2020, among Ninety-six physicians recruited using a convenient sampling technique. Twenty-item, validated, reliable, and a pilot-tested questionnaire was used to assess the knowledge regarding CRS-r and collect socio-demographic variables. The analysis was performed using the Statistical Package for the Social Sciences version 23. Bivariate and multivariate logistic regression analyses were employed to assess the association of participants’ socio-demographic variables and their parent department of work with the knowledge. P < 0.05 was considered statistically significant in the multivariate analysis.

Results:

A total of Ninety-six participants were included in the analysis, and only 33.3% of them were found to have adequate knowledge of CRS-r. Multivariate analysis revealed that age (adjusted odds ratio [AOR] = 31.66; 95% CI: 6.25–160.36), gender (AOR = 44.16; 95% CI: 7.43–268.23), and parent department of working (AOR = 0.148; 95% CI: 0.06–0.39) were significantly associated with the knowledge.

Conclusion:

Knowledge of the physicians on CRS-r is found to be exceptionally low. It has a strong tendency to adversely affect patients’ optimal care with disorders of consciousness (DoC). Therefore, it is crucial to expand physicians’ knowledge and awareness regarding CRS-r to adequately screen patients with DoC.

Somatosensory evoked potential amplitudes correlate with long-term consciousness recovery in patients with unresponsive wakefulness syndrome

OBJECTIVE

To prospectively investigate relationships of cortical somatosensory evoked potential (SEP) amplitudes with consciousness recovery and disability in the year following brain injury in patients with vegetative state/unresponsive wakefulness syndrome (VS/UWS).

METHODS

SEPs of 42 patients with VS/UWS were recorded 51.7 ± 23.3 days post-injury. N20-P25 amplitudes were compared between patients with and without consciousness recovery at 6 months and 1 year post-injury.

RESULTS

SEPs were present in 21 patients and bilaterally absent in 21 patients. N20-P25 amplitudes were significantly higher in patients who recovered consciousness than in those who died or did not recover consciousness at 6 months (median, 4.6 vs. 1.9 μV; P = 0.004) and 1 year (median, 4.6 vs. 2.1 μV; P = 0.02) after injury. The lowest N20-P25 amplitude in a patient who recovered consciousness was 2.15 μV. N20-P25 amplitudes correlated significantly with Coma Recovery Scale-Revised and Disability Rating Scale scores at 6 months and 1 year post-injury (both P < 0.05).

CONCLUSIONS

In patients with VS/UWS, SEP amplitudes are related to consciousness recovery and disability at 6 months and 1 year post-injury.

SIGNIFICANCE

The evaluation of SEP amplitudes can help to refine prognoses for patients with VS/UWS.

Outcome registry of early intensive neurorehabilitation in patients with disorders of consciousness: study protocol of a prospective cohort study

BACKGROUND

Prolonged disorders of consciousness (PDOC) may occur after severe brain injury. Two diagnostic entities are distinguished within PDOC: unresponsive wakefulness syndrome (UWS, previously known as vegetative state) and minimally conscious state (MCS). Patients with PDOC may benefit from early intensive neurorehabilitation (EIN). In the Netherlands, the EIN programme is provided by one designated expert rehabilitation centre and forms the starting point of a dedicated chain of specialised rehabilitation and care for this group. This study project, called DOCTOR: Disorders of Consciousness; Treatment and Outcomes Registry, sets up a registry and systematically investigates multiple short- and long-term outcomes of patients with PDOC who receive EIN.

METHODS

Single-centre prospective cohort study with a 2-year follow-up period. Patients with PDOC due to acute brain injury who receive EIN, aged 16 years and older are included. Measurements will take place at start EIN, in week 5, 10, and at discharge from the EIN programme (duration = max 14 weeks) and at week 28, 40, 52, and 104 after admission to the EIN programme, following patients through the health-care chain. Outcome measures are the changes over time in level of consciousness, using the Coma Recovery Scale-Revised; the frequency and type of medical complications; the mortality rate; level of disability, including the level of motor, cognitive, behavioural and emotional functioning; participation; and quality of life. Secondary outcomes include self-efficacy of caregivers, caregivers' strain and cost-effectiveness of the programme.

DISCUSSION

The DOCTOR study will provide insight in the recovery patterns and predictors of recovery for multiple outcomes in PDOC patients after following EIN. The results of the study will enable us to benchmark and improve EIN and the organisation of the health-care chain, both for patients with PDOC and for their families.

TRIAL REGISTRATION

Netherlands Trial Register, NL 8138 . Retrospectively registered 6 November 2019.

The influence of the CRS-R score on functional outcome in patients with severe brain injury receiving early rehabilitation

Background

The aim of the study was to determine the role of the Coma Recovery Scale-Revised (CRS-R) in the prediction of functional status at the end of neurological early rehabilitative treatment.

Methods

Patients consecutively admitted to intensive or intermediate care units of a neurological rehabilitation center were enrolled in the study. Consciousness and functional status were assessed with the Coma Recovery Scale-Revised (CRS-R) and the Early Rehabilitation Barthel Index (ERBI), respectively. Both assessments were carried out weekly within the first month and at the end of early rehabilitation. Patient and clinical data were entered into a binary logistic regression model to predict functional status at discharge.

Results

327 patients (112 females, 215 males) with a median age of 63 years (IQR = 53–75) and a median disease duration of 18 days (IQR = 12–28) were included. Most patients suffered from stroke (59 %), followed by traumatic brain injury (31 %), and hypoxic ischemic encephalopathy (10 %). Upon admission, 12 % were diagnosed as comatose, 31 % as unresponsive wakefulness syndrome (UWS), 35 % as minimally conscious state (MCS) and 22 % already emerged from MCS (eMCS). Of all patients undergoing complete early rehabilitative treatment (n = 180), 72 % showed improvements in level of consciousness (LOC). In this group, age, initial CRS-R score and gains in CRS-R score after four weeks independently predicted functional outcome at discharge.

Conclusions

The study confirms the relevance of the CRS-R score for functional outcome prediction. High CRS-R scores and young age facilitate functional improvements and increase the probability to continue treatment in subsequent rehabilitation phases. Moreover, results indicate that recovery might occur over a period of time that extends beyond acute care.

Predicting Outcome of Acquired Brain Injury by the Evolution of Paroxysmal Sympathetic Hyperactivity Signs

In this multi-center study, we provide a systematic evaluation of the clinical variability associated with paroxysmal sympathetic hyperactivity (PSH) in patients with acquired brain injury (ABI) to determine how these signs can impact outcomes. A total of 156 ABI patients with a disorder of consciousness (DoC) were admitted to neurorehabilitation subacute units (intensive rehabilitation unit; IRU) and evaluated at baseline (T0), after 4 months from event (T1), and at discharge (T2). The outcome measure was the Glasgow Outcome Scale-Extended, whereas age, sex, etiology, Coma Recovery Scale-Revised (CRS-r), Rancho Los Amigos Scale (RLAS), Early Rehabilitation Barthel Index (ERBI), PSH-Assessment Measure (PSH-AM) scores and other clinical features were considered as predictive factors. A machine learning (ML) approach was used to identify the best predictive model of clinical outcomes. The etiology was predominantly vascular (50.8%), followed by traumatic (36.2%). At admission, prevalence of PSH was 31.3%, which decreased to 16.6% and 4.4% at T1 and T2, respectively. At T2, 2.8% were dead and 61.1% had a full recovery of consciousness, whereas 36.1% remained in VS or MCS. A support vector machine (SVM)-based ML approach provides the best model with 82% accuracy in predicting outcomes. Analysis of variable importance shows that the most important clinical factors influencing the outcome are the PSH-AM scores measured at T0 and T1, together with neurological diagnosis, CRS-r, and RLAS scores measured at T0. This joint multi-center effort provides a comprehensive picture of the clinical impact of PSH signs in ABI patients, demonstrating its predictive value in comparison with other well-known clinical measurements.

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.

Multi-center study on overall clinical complexity of patients with prolonged disorders of consciousness of different etiologies

Aim: to assess overall clinical complexity of patients with acquired disorders of consciousness (DoC) in vegetative state/unresponsive wakefulness syndrome (VS/UWS) vs. minimally conscious state- MCS) and in different etiologies..Design: Multi-center cross-sectional observational study.Setting: 23 intensive neurorehabilitation units.Subjects: 264 patients with DoC in the post-acute phase: VS/UWS = 141, and MCS = 123 due to vascular (n = 125), traumatic (n = 83) or anoxic (n = 56) brain injury.Main Measures: Coma Recovery Scale-Revised, and Disability Rating Scale (DRS); presence of medical devices (e.g., for eating or breathing); occurrence and severity of medical complications.Results: patients in DoC, and particularly those in VS/UWS, showed severe overall clinical complexity. Anoxic patients had higher overall clinical complexity, lower level of responsiveness/consciousness, higher functional disability, and higher needs of medical devices. Vascular patients had worse premorbid clinical comorbidities. The two etiologies showed a comparable rate of MC, higher than that observed in traumatic etiology.Conclusion: overall clinical complexity is significantly higher in VS/UWS than in MCS, and in non-traumatic vs. traumatic etiology. These findings could explain the worse clinical evolution reported in anoxic and vascular etiologies and in VS/UWS patients and contribute to plan patient-tailored care and rehabilitation programmes.

Decannulation and improvement of responsiveness in patients with disorders of consciousness

Decannulation is a rehabilitation milestone in patients with Disorders of Consciousness (DoC). investigate the relationship between decannulation and improvement of responsiveness (IR) in DoC. 236 tracheostomized patients with severe Acquired Brain Injury and DoC admitted in the Intensive Rehabilitation Unit were retrospectively included. They received personalized interdisciplinary rehabilitation. At discharge, IR was evaluated. The association between IR and demographic/clinical data was investigated using a logistic regression analysis, both in the Unresponsive Wakefulness Syndrome (UWS) and Minimal Consciousness State (MCS) group, divided according to their Coma Recovery Scale-Revised score at admission. In the UWS group (N = 107), only decannulation was associated with IR at discharge (OR: 5.94, CI: 2.08-16.91, p = .001). In the MCS group (N = 129) time post-injury (OR: 0.983, CI: 0.97-0.99, p = .012) and decannulation were associated with IR at discharge (OR: 17.9, CI: 6.39-50.13, p < .001). Decannulation and IR were found to be strongly related, independently from the initial clinical state. While the retrospective nature of the study could not exclude that decannulation may be a consequence of a spontaneous recovery, the obtained results may disclose its potential influence on the clinical history of patients with DoC.

Developing an instrument for an early prediction model of long-term functional outcomes in people with acquired injuries of the central nervous system: protocol and methodological aspects

Severe acquired brain injury (ABI) is a major cause of long-term disability and is the main determinant of health and societal costs. Early identification of favourable long-term recovery would allow personalized rehabilitative programs and better health care resources allocation. In light of the higher survival rate from intensive care units (ICU) in recent years, there is a growing need for early prognostication markers of functional recovery; to date, these data have been mainly collected at rehabilitation unit admission and not during the acute phase. We present the protocol and methodology to develop prediction models in people with severe acquired brain injury (GCS at admission to ICU < 8) for the functional and cognitive outcome at 12 months from the event. Predictors will be collected during the acute stage. Participants will be recruited within the first 72 h from the event in the ICUs of two teaching hospitals (Padova and Treviso). Participants will be followed up at discharge from ICU, admission and discharge from Neurorehabilitation and after 12 months from the event. Clinical and functional scales, electroencephalography, evoked potentials, magnetic resonance imaging and serological markers will be entered into a digital registry. Survival will be estimated using the Cox proportional hazard model. A multivariate prediction model will be developed for each of the functional and cognitive outcomes at 12 months from the event.

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.

Update on diagnosis in disorders of consciousness

INTRODUCTION

New guidelines regarding the diagnosis of disorders of consciousness (DOC) (such as vegetative state and minimally conscious state) have recently been published by the American Academy of Neurology and the European Academy of Neurology. This follows an impressive number of prospective studies performed on DOC and recent multi-centric studies with larger sample size, which have gathered precious information on the recovery of cohort of patients through years and which now call for a better management of patients with DOC.

AREAS COVERED

This review will discuss recent updates on the clinical entities of DOC, the challenges for an accurate diagnosis and the last developments in diagnostic tools.

EXPERT OPINION

The authors will also discuss the impact of the new guidelines on their way of diagnosing patients and how diagnosis will most likely change in a near future.

Multicenter prospective study on predictors of short-term outcome in disorders of consciousness

OBJECTIVE

This international multicenter, prospective, observational study aimed at identifying predictors of short-term clinical outcome in patients with prolonged disorders of consciousness (DoC) due to acquired severe brain injury.

METHODS

Patients in vegetative state/unresponsive wakefulness syndrome (VS/UWS) or in minimally conscious state (MCS) were enrolled within 3 months from their brain injury in 12 specialized medical institutions. Demographic, anamnestic, clinical, and neurophysiologic data were collected at study entry. Patients were then followed up for assessing the primary outcome, that is, clinical diagnosis according to standardized criteria at 6 months postinjury.

RESULTS

We enrolled 147 patients (44 women; mean age 49.4 [95% confidence interval 46.1-52.6] years; VS/UWS 71, MCS 76; traumatic 55, vascular 56, anoxic 36; mean time postinjury 59.6 [55.4-63.6] days). The 6-month follow-up was complete for 143 patients (VS/UWS 70; MCS 73). With respect to study entry, the clinical diagnosis improved in 72 patients (VS/UWS 27; MCS 45). Younger age, shorter time postinjury, higher Coma Recovery Scale-Revised total score, and presence of EEG reactivity to eye opening at study entry predicted better outcome, whereas etiology, clinical diagnosis, Disability Rating Scale score, EEG background activity, acoustic reactivity, and P300 on event-related potentials were not associated with outcome.

CONCLUSIONS

Multimodal assessment could identify patients with higher likelihood of clinical improvement in order to help clinicians, families, and funding sources with various aspects of decision-making. This multicenter, international study aims to stimulate further research that drives international consensus regarding standardization of prognostic procedures for patients with DoC.

Decannulation After a Severe Acquired Brain Injury

OBJECTIVE

To identify the effect of some clinical characteristics of severe acquired brain injury (sABI) patients on decannulation success during their intensive rehabilitation unit (IRU) stay.

DESIGN

Nonconcurrent cohort study.

SETTING

Don Gnocchi Foundation Institute.

PARTICIPANTS

Patients (N=351) with sABI and tracheostomy were retrospectively selected from the database of the IRU of the Don Gnocchi Foundation Institute.

MAIN OUTCOME MEASURES

Potential predictors of decannulation were screened from variables collected at admission during clinical examination, conducted by trained and experienced examiners. The association between clinical characteristics and decannulation status was investigated through a Cox regression model. Kaplan-Meier curves were then created for time-event analysis.

RESULTS

Among the patients (mean age, 64.1±15.5y), 54.1% were decannulated during their IRU stay. Absence of pulmonary infections (P<.001), sepsis (P=.001), tracheal alteration at the fibrobronchoscopy examination (P=.004) and a higher Coma Recovery Scale-Revised (CRS-R) score (P<.001) or a better state of consciousness at admission (P=.001) were associated with a higher probability of decannulation.

CONCLUSIONS

Fibrobronchoscopy assessment of patency of airways and accurate evaluation of the state of consciousness using the CRS-R are relevant in this setting of care to better identify patients who are more likely to have the tracheostomy tube removed. These results may help clinicians choose the appropriate timing and intensity of rehabilitation interventions and plan for discharge.

Transcranial Direct Current Stimulation Over Prefrontal Areas Improves Psychomotor Inhibition State in Patients With Traumatic Brain Injury: A Pilot Study

Objectives

Many post-traumatic patients with minimally conscious state are complicated by psychomotor inhibition state (PIS), which impedes further rehabilitation. The treatment of PIS is not satisfactory. This pilot study aimed to investigate effects of anodal transcranial direct current stimulation (A-tDCS) on PIS in post-traumatic patients and examine the altered cortical activation after tDCS using non-linear electroencephalogram (EEG).

Methods

The study included 10 patients with post-traumatic PIS. An A–B design was used. The patients received 4 weeks of sham tDCS during Phase A, and they received A-tDCS over the prefrontal area and left dorsolateral prefrontal cortex (DLPFC) for 4 weeks (40 sessions) during Phase B. Conventional treatments were administered throughout both phases. JFK Coma Recovery Scale-Revised (CRS-R), apathy evaluation scale (AES), and the EEG non-linear indices of approximate entropy (ApEn) and cross approximate entropy (C-ApEn) were measured before Phase A, before Phase B, and after Phase B.

Results

After A-tDCS treatment, CRS-R and AES were improved significantly. ApEn and C-ApEn results showed that the local cortical connection of bilateral sensorimotor areas with their peripheral areas could be activated by affected painful stimuli, while bilateral cerebral hemispheres could be activated by the unaffected painful-stimuli condition. Linear regression analysis revealed that the affected sensorimotor cortex excitability and unaffected local and distant cortical networks connecting the sensorimotor area to the prefrontal area play a major role in AES improvement.

Conclusion

A-tDCS over the prefrontal area and left DLPFC improves PIS. The recovery might be related to increased excitability in local and distant cortical networks connecting the sensorimotor area to the prefrontal area. Thus, tDCS may be an alternative treatment for post-traumatic PIS.