Low-density EEG-based Functional Connectivity Discriminates Minimally Conscious State plus from minus.

OBJECTIVE: Within the continuum of consciousness, patients in a Minimally Conscious State (MCS) may exhibit high-level behavioral responses (MCS+) or may not (MCS-). The evaluation of residual consciousness and related classification is crucial to propose tailored rehabilitation and pharmacological treatments, considering the inherent differences among groups in diagnosis and prognosis. Currently, differential diagnosis relies on behavioral assessments posing a relevant risk of misdiagnosis. In this context, EEG offers a non-invasive approach to model the brain as a complex network. The search for discriminating features could reveal whether behavioral responses in post-comatose patients have a defined physiological background. Additionally, it is essential to determine whether the standard behavioral assessment for quantifying responsiveness holds physiological significance. METHODS: In this prospective observational study, we investigated whether low-density EEG-based graph metrics could discriminate MCS+/- patients by enrolling 57 MCS patients (MCS-: 30; males: 28). At admission to intensive rehabilitation, 30 min resting-state closed-eyes EEG recordings were performed together with consciousness diagnosis following international guidelines. After EEG preprocessing, graphs' metrics were estimated using different connectivity measures, at multiple connection densities and frequency bands (α,θ,δ). Metrics were also provided to cross-validated Machine Learning (ML) models with outcome MCS+/-. RESULTS: A lower level of brain activity integration was found in the MCS- group in the α band. Instead, in the δ band MCS- group presented an higher level of clustering (weighted clustering coefficient) respect to MCS+. The best-performing solution in discriminating MCS+/- through the use of ML was an Elastic-Net regularized logistic regression with a cross-validation accuracy of 79% (sensitivity and specificity of 74% and 85% respectively). CONCLUSION: Despite tackling the MCS+/- differential diagnosis is highly challenging, a daily-routine low-density EEG might allow to differentiate across these differently responsive brain networks. SIGNIFICANCE: Graph-theoretical features are shown to discriminate between these two neurophysiologically similar conditions, and may thus support the clinical diagnosis.

Implications of the Consciousness State on Decannulation in Patients With a Prolonged Disorder of Consciousness.

OBJECTIVE: To prospectively investigate the evolution of the consciousness state and the cannula-weaning progression in patients with prolonged disorders of consciousness. DESIGN: Nonconcurrent cohort study. SETTING: A rehabilitation unit. PARTICIPANTS: Adult patients (N=144) with prolonged disorders of consciousness after a severe acquired brain injury admitted between June 2020 and September 2022. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Consciousness state was assessed by repeated Coma Recovery Scale-Revised (CRS-R) questionnaire administration at admission and weekly afterward. The dates of the first improvement of consciousness state and the achievement of decannulation were recorded. Decannulation followed an internal protocol of multiprofessional rehabilitation. RESULTS: One hundred forty-four patients were included: age, 69 years; 64 (44.4%) with hemorrhagic etiology; time post onset, 40 days, CRS-R score at admission, 9, median length of stay, 90 days. Seventy-three (50.7%) patients were decannulated. They showed a significantly higher CRS-R (P<.001) and states of consciousness (P<.001) at admission, at the first improvement of the consciousness state (P=.003), and at discharge (P<.001); a lower severity in the Cumulative Illness Rating Scale at admission (P=.01); and a lower rate of pulmonary infections with recurrence (P=.021), compared with nondecannulated patients. Almost all decannulated patients (97.3%) improved their consciousness before decannulation. Consciousness states at decannulation were as follows: unresponsive wakefulness syndrome, 0 (0%); minimally conscious state (MCS) minus, 4 (5.5%); MCS plus, 7 (9.6%); and emergence from MCS, 62 (84.9%). Kaplan-Meier analysis showed a significant divergence between the curves with a higher probability of decannulation in patients who improved consciousness (P<.001). CONCLUSIONS: This study showed that the presence of signs of consciousness, even subtle, is a necessary condition for decannulation, suggesting that consciousness may influence some of the components implied in the decannulation process.

Brain microstate spatio-temporal dynamics as a candidate endotype of consciousness.

Consciousness can be defined as a phenomenological experience continuously evolving. Current research showed how conscious mental activity can be subdivided into a series of atomic brain states converging to a discrete spatiotemporal pattern of global neuronal firing. Using the high temporal resolution of EEG recordings in patients with a severe Acquired Brain Injury (sABI) admitted to an Intensive Rehabilitation Unit (IRU), we detected a novel endotype of consciousness from the spatiotemporal brain dynamics identified via microstate analysis. Also, we investigated whether microstate features were associated with common neurophysiological alterations. Finally, the prognostic information comprised in such descriptors was analysed in a sub-cohort of patients with prolonged Disorder of Consciousness (pDoC). Occurrence of frontally-oriented microstates (C microstate), likelihood of maintaining such brain state or transitioning to the C topography and complexity were found to be indicators of consciousness presence and levels. Features of left-right asymmetric microstates and transitions toward them were found to be negatively correlated with antero-posterior brain reorganization and EEG symmetry. Substantial differences in microstates' sequence complexity and presence of C topography were found between groups of patients with alpha dominant background, cortical reactivity and antero-posterior gradient. Also, transitioning from left-right to antero-posterior microstates was found to be an independent predictor of consciousness recovery, stronger than consciousness levels at IRU's admission. In conclusions, global brain dynamics measured with scale-free estimators can be considered an indicator of consciousness presence and a candidate marker of short-term recovery in patients with a pDoC.

Relationship between Nutritional Risk, Clinical and Demographic Characteristics, and Pressure Ulcers in Patients with Severe Acquired Brain Injuries Attending a Rehabilitative Program.

Preliminary evidence in the literature suggests a high prevalence of malnutrition (undernutrition) in patients with severe acquired brain injuries (sABI), with an expected negative impact on clinical outcomes and pressure ulcers (PUs) in particular. In a retrospective cohort study on patients discharged from intensive care units (ICU) and admitted to an intensive rehabilitation unit (IRU), the risk of malnutrition was systematically assessed, in addition to standard clinical procedures (including PUs evaluation), using two different tools: the Malnutrition Universal Screening Tool (MUST) and the Controlling Nutritional Status (CONUT) tool. Eighty-eight patients were included in the analysis. A high proportion (79.5%) of patients with sABI suffered from PUs, being older and more frequently men, with a longer ICU stay between the event and admission to IRU, and a greater MUST score. At discharge, when compared to patients whose PUs had healed, those with persisting PUs were more often men and had the worst cognitive performance at admission. As for nutritional risk, the baseline CONUT score was identified as an independent negative predictor of PUs at discharge by the logistic regression model. In conclusion, the assessment of nutritional risk using simple standard tools may be useful in the clinical evaluation of sABI patients with PUs.

Neural coding of autonomic functions in different states of consciousness.

Detecting signs of residual neural activity in patients with altered states of consciousness is a crucial issue for the customization of neurorehabilitation treatments and clinical decision-making. With this large observational prospective study, we propose an innovative approach to detect residual signs of consciousness via the assessment of the amount of autonomic information coded within the brain. The latter was estimated by computing the mutual information (MI) between preprocessed EEG and ECG signals, to be then compared across consciousness groups, together with the absolute power and an international qualitative labeling. One-hundred seventy-four patients (73 females, 42%) were included in the study (median age of 65 years [IQR = 20], MCS +: 29, MCS -: 23, UWS: 29). Electroencephalography (EEG) information content was found to be mostly related to the coding of electrocardiography (ECG) activity, i.e., with higher MI (p < 0.05), in Unresponsive Wakefulness Syndrome and Minimally Consciousness State minus (MCS -). EEG-ECG MI, besides clearly discriminating patients in an MCS - and +, significantly differed between lesioned areas (sides) in a subgroup of unilateral hemorrhagic patients. Crucially, such an accessible and non-invasive measure of residual consciousness signs was robust across electrodes and patient groups. Consequently, exiting from a strictly neuro-centric consciousness detection approach may be the key to provide complementary insights for the objective assessment of patients' consciousness levels and for the patient-specific planning of rehabilitative interventions.

EEG fractal dimensions predict high-level behavioral responses in minimally conscious patients.

Objective.Brain-injured patients may enter a state of minimal or inconsistent awareness termed minimally conscious state (MCS). Such patient may (MCS+) or may not (MCS-) exhibit high-level behavioral responses, and the two groups retain two inherently different rehabilitative paths and expected outcomes. We hypothesized that brain complexity may be treated as a proxy of high-level cognition and thus could be used as a neural correlate of consciousness.Approach.In this prospective observational study, 68 MCS patients (MCS-: 30; women: 31) were included (median [IQR] age 69 [20]; time post-onset 83 [28]). At admission to intensive rehabilitation, 30 min resting-state closed-eyes recordings were performed together with consciousness diagnosis following international guidelines. The width of the multifractal singularity spectrum (MSS) was computed for each channel time series and entered nested cross-validated interpretable machine learning models targeting the differential diagnosis of MCS±.Main results.Frontal MSS widths (p< 0.05), as well as the ones deriving from the left centro-temporal network (C3:p= 0.018, T3:p= 0.017; T5:p= 0.003) were found to be significantly higher in the MCS+ cohort. The best performing solution was found to be the K-nearest neighbor model with an aggregated test accuracy of 75.5% (median [IQR] AuROC for 100 executions 0.88 [0.02]). Coherently, the electrodes with highest Shapley values were found to be Fz and Cz, with four out the first five ranked features belonging to the fronto-central network.Significance.MCS+ is a frequent condition associated with a notably better prognosis than the MCS-. High fractality in the left centro-temporal network results coherent with neurological networks involved in the language function, proper of MCS+ patients. Using EEG-based interpretable algorithm to complement differential diagnosis of consciousness may improve rehabilitation pathways and communications with caregivers.

Cognitive reserve index and long-term disability in patients with severe traumatic brain injury discharged from the intensive rehabilitation unit.

Objectives: The "cognitive reserve" (CR) theory posits that higher premorbid cognitive activities can mitigate the effects of brain damage. This study aimed to investigate the association between CR and long-term functional autonomy in patients surviving a severe traumatic brain injury (sTBI). Setting: Data were collected from the database of inpatients with severe acquired brain injury in a rehabilitation unit admitted from August 2012 to May 2020. Participants: Patients that had incurred an sTBI, aged 18+ years, completing the phone Glasgow Outcome Scale-Expanded at follow-up (pGOS-E) in absence of previous brain trauma or neurological disease, or cognitive disorders were included. Patients with severe brain injury from non-traumatic etiologies were not included in the study. Design: In this longitudinal study, all patients underwent a multidimensional assessment including the cognitive reserve index questionnaire (CRIq), the coma recovery scale-revised, the level of cognitive functioning, the Disability Rating Scale (DRS), and the Galveston Orientation and Amnesia Test at admission. At discharge, functional scales were administered again together with the Glasgow Outcome Scale. The pGOS-E was assessed at follow-up. Main measures: pGOS-E. Results: A total of 106 patients/caregivers underwent the pGOS-E after 5.8 [3.6] years from the event. Among them, 46 (43.4%) died after discharge, and 60 patients [men: 48 (80%); median age: 54 years; median time post-onset: 37 days; median education level: 10 years; median CRIq total score: 91] were included in the analysis exploring the association between pGOS-E and demographic data, cognitive reserve surrogates, and clinical variables at admission and discharge from the rehabilitation unit. A younger age (B = -0.035, p = 0.004) and a lower DRS category at discharge (B = -0.392, p = 0.029) were significantly related to a higher long-term functional autonomy in the multivariate analysis. Conclusion: Long-term functional autonomy was not influenced by CR as assessed through the educational level and the CRIq.

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.

The Impact of Cerebral Amyloid Angiopathy on Functional Outcome of Patients Affected by Spontaneous Intracerebral Hemorrhage Discharged from Intensive Inpatient Rehabilitation: A Cohort Study.

Background: Sporadic CAA is recognized as a major cause of sICH and sABI. Even if intensive rehabilitation is recommended to maximize functional recovery after sICH, no data are available on whether CAA may affect rehabilitation outcomes. In this observational prospective study, to explore the impact of CAA on rehabilitation results, functional outcomes after intensive rehabilitation have been compared between patients affected by sICH with and without a diagnosis of CAA. Methods: All adults affected by sABI due to sICH and admitted to the IRU of IRCCS-Don-Gnocchi-Foundation were consecutively enrolled for 12 months. Demographic and clinical data were recorded upon admission and discharge. Results: Among 102 sICH patients (age: 66 (IQR = 16), 53% female), 13% were diagnosed as probable/possible-CAA. TPO and functional assessment were comparable upon admission, but CAA patients were significantly older (p = 0.001). After a comparable LOS, CAA patients presented higher care burden (ERBI: p = 0.025), poorer functional recovery (FIM: p = 0.02) and lower levels of global independence (GOSE > 4: p = 0.03). In multivariate analysis, CAA was significantly correlated with a lower FIM (p = 0.019) and a lower likelihood of reaching GOS-E > 4, (p = 0.041) at discharge, independently from age. Conclusions: CAA seems to be independently associated with poorer rehabilitation outcomes, suggesting the importance of improving knowledge about CAA to better predict rehabilitation outcomes.

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.

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.

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.

Impact of decompressive craniectomy on functional outcome of severe acquired brain injuries patients, at discharge from intensive inpatient rehabilitation.

PURPOSE: Decompressive craniectomy (DC) is a life-saving procedure conducted to treat refractory intracranial hypertension. Although DC reduces mortality of severe Acquired Brain Injury (sABI) survivors, it has been associated with severe long-term disability. This observational study compares functional outcomes at discharge from an Intensive Rehabilitative Unit (IRU) between sABI patients with and without DC. MATERIAL AND METHODS: sABI patients undergoing DC before entering the Don Gnocchi Foundation IRU were compared with a group of sABI patients who did not undergo DC (No-DC group), after matching it by age, sex, aetiology, time post-onset, and clinical status. Inclusion criteria were: diagnosis of sABI, age 18+, time from the event <90 days. RESULTS: A total of 87 (DC: 47) patients were included (median age: 60.5 [IQR = 17.47]). The two groups did not differ for admission clinical features except for the tracheostomy presence (more frequent in DC, p < 0.001). No significant differences were also found at discharge. DC group presented a significantly longer length-of-stay than No-DC group (p < 0.001) and a longer time to tracheostomy removal (p = 0.036). DC was not found to influence outcomes as consciousness improvement, tracheostomy removal, oral intake and functional independence. CONCLUSIONS: sABI patients with DC improved after rehabilitation as much as No-DC patients did but they required a longer stay.Implications for RehabilitationDecompressive craniectomy (DC) is practiced during the acute phase after hemorrhagic, ischemic, traumatic severe brain injury as a life-saving procedure to treat refractory intracranial hypertensionDC has been associated with follow-up severe long-term disability, but no study yet addressed whether DC may affect intensive rehabilitation outcomes.Undergoing a DC is not a negative prognostic factor for achieving rehabilitation goals after a severe acquired brain injuryDC must be taken into account when customizing rehabilitation pathway especially because these patients required a longer time to reach the outcomes.

Data-driven prediction of decannulation probability and timing in patients with severe acquired brain injury.

BACKGROUND AND OBJECTIVES: From a rehabilitation perspective, removal of tracheostomy in patients with severe acquired brain injuries (sABI) is a crucial step. Predictive parameters for a successful decannulation are currently still a focus of the research for sABI patients, especially for those presenting a disorder of consciousness. For this reason, we adopted a data-driven approach predicting decannulation probability and timing using ensemble learning models in patients in intensive rehabilitation units. METHODS: 327 patients, 186 of which were successfully decannulated during their intensive rehabilitative stay, were recruited in a non-concurrent retrospective study. Decannulation probability and timing were predicted using data available within one week from admission at the rehabilitation unit. Two predictive models were trained and cross-validated independently, with the first being an ensemble of a Support Vector Machine and Random Forests and the second an Adaptive Boosting with a Support Vector Regression as weak learner. Confusion matrix, accuracy and AUC were considered as evaluation metrics for the classifier and median absolute error was considered for the regressor. To quantify the advantages in the clinical practice of using the latter prediction, we compared timing estimation with a timing guess (median) calculated on available data. The comparison was based on a Wilcoxon signed rank test. RESULTS: Decannulation probability was successfully predicted with an accuracy of 84.8% (AUC = 0.85) and timing with a median absolute error of 25.7 days [IQR = 25.6]. This resulted in a significant improvement with respect to the weaning time guess (p<0.05) with an effect size of 71.7%. Furthermore, dichotomizing the regression prediction with a threshold (3 months from the event), resulted in a prediction accuracy of 77.5% (AUC = 0.82) on the test set. DISCUSSIONS: A model capable of providing a prediction on decannulation probability and timing was developed and cross-validated, built on data taken at admission to the intensive rehabilitation unit. Translated in clinical practice, this information can support the clinical decision process and provide a mean to improve both in-hospital and domiciliary care organization.

Critical illness polyneuromyopathy: Functional impact after severe acquired brain injuries.

OBJECTIVES: Critical illness polyneuropathy and myopathy (CIPNM) frequently affects critical patients and can occur after severe acquired brain injuries (sABI) influencing the functional recovery. We aimed to assess how the concomitance between CIPNM and sABI might influence the rehabilitative outcomes in terms of functional autonomy, oral feeding recovery and endotracheal tube weaning. MATERIALS AND METHODS: Adult patients with sABI admitted to an intensive rehabilitation unit and underwent an electromyography examination within seven days after admission were included. Assessed rehabilitative outcomes at discharge were decannulation success and its timing, functional autonomy measured by the Functional Independence Measure (FIM) and the Glasgow outcome scale expanded (GOS-E) and oral feeding recovery assessed by the Functional Oral Intake Scale (FOIS) score. RESULTS: Among the 224 included patients (81 (36%) females, age (median[IQR]): 68.73[21.66] years), 119 (53.1%) presented CIPNM at admission. Albeit the change of rehabilitative outcomes between admission and discharge was significant in all the sABI patients (P < .001 for ΔFOIS, ΔFIM and ΔGOS-E), those with a concomitant CIPNM achieved significantly lower scores as evaluated by Mann-Whitney tests (P < .001 for ΔFIM Δ and GOS-E; P < .005 for ΔFOIS). The CIPNM absence was associated with a higher probability to achieve functional autonomy (GOS-E > 4) (OR:4.57 (1.49/14.06); P < .01) and oral feeding recovery (FOIS ≥ 4) (OR:2.07 (1.07/3.99); P = .03) at discharge. CIPNM presence did not influence decannulation success but a longer time to cannula weaning was required (P < .01 in the log-rank test). CONCLUSIONS: CIPMN significantly affects the rehabilitative outcomes after a sABI and should be taken into account for better rehabilitative handling.

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.

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.