BACKGROUND:Post-traumatic confusional state (PTCS) frequently occurs during the recovery from disorders of consciousness (DoC) following severe traumatic brain injury (TBI). Confusional symptoms span multiple domains influencing consciousness, including impairments in the access and integration of mental contents, distortions in perceptual and emotional experiences, vigilance fluctuations, and deficits in memory, orientation, and executive control. While the clinical presentation can be systematically characterized using the Confusion Assessment Protocol (CAP), the underlying neurophysiological mechanisms remain poorly understood. Specifically, slowing of both periodic and aperiodic EEG activity is a consistent finding across multiple alterations of consciousness. OBJECTIVE:We assessed whether recovery from PTCS involves a renormalization of EEG slowing. METHODS:We recorded resting-state EEG from subacute severe TBI patients at admission (T0), comparing patients with PTCS (N=22) to TBI Controls who had already emerged (N = 19). Patients with PTCS were longitudinally monitored using CAP, and a follow-up EEG (T1) was acquired after rehabilitation either upon recovery (N=19) or at discharge (N=3). RESULTS:Recovery from PTCS was marked by partial normalization of the spectral profile-as indexed by the spectral exponent, and peak frequency-converging toward the profile of TBI Controls. However, marginal persistent elevations in power, indexed by spectral offset and delta power, indicated residual abnormalities. Spectral features, particularly spectral exponent and offset, correlated with CAP and robustly discriminated the presence of PTCS (bivariate model ROC AUC = 0.894). CONCLUSION:Results show that PTCS is marked by broadband EEG slowing affecting both periodic and aperiodic activity. Spectral reorganization over time provides insight into the mechanisms of recovery from PTCS and may inform rehabilitation pathways.

Post-traumatic amnesia (PTA), recently conceptualized as part of the broader syndrome known as post-traumatic confusional state (PTCS), marks a critical phase of recovery following traumatic brain injury (TBI). Indeed, this state is characterized not only by anterograde memory impairment but also by disorientation, agitation, and attention deficits. Given the phenotypic overlap between PTA/PTCS and delirium—both marked by fluctuating cognitive and attentional disturbances—electroencephalography (EEG) represents a promising tool for elucidating shared pathophysiological mechanisms. While delirium is typically associated with diffuse EEG slowing and the presence of slow-wave activity (SWA), thought to reflect underlying global cortical disruption, it remains unclear whether PTCS exhibits similar EEG underpinnings. In this prospective longitudinal study, we assessed dynamic EEG correlates of PTCS using the grand total EEG (GTE) score, a composite measure that incorporates background slowing and superimposed SWA. We enrolled 42 consecutive TBI patients (mean age = 40.3 ±15 years) classifying them at baseline (T0) into two groups based on the Confusion Assessment Protocol (CAP): those in PTA/PTCS ( N = 22; median time from injury 24 days; median CAP total score 5) and those already emerged from PTA/PTCS (i.e., TBI controls, N = 20; median time from injury 24 days; median CAP total score 0). At T0, patients with PTA/PTCS exhibited significantly higher baseline GTE scores compared with TBI controls, 16.6 ± 4.5 versus 5.1 ± 2.8; t (35.75) = 10.04, p < 0.0001; d = 3.04, reflecting severe EEG abnormalities characterized by diffuse slowing and disrupted rhythmic activity, as captured by the GTE subdomains. Longitudinal follow-up (T1) at emergence from PTCS revealed a significant EEG improvement paralleling clinical recovery, with GTE scores dropping from 16.5 (interquartile range [IQR]: 6.5) to 8, IQR: 3.75; t (21) = 8.03, p < 0.0001; d = 1.71, confirming EEG’s sensitivity to dynamic clinical changes. Furthermore, the severity of EEG abnormalities at follow-up (T1) significantly correlated with the total duration of PTA/PTCS (ρ = 0.56, p < 0.0001), underscoring EEG’s potential as an objective biomarker for disease burden and for monitoring recovery trajectories. Notably, these findings were independent of pharmacological confounders, as medication regimens were not significantly different across groups and time points. Our results support a reconceptualization of PTA/PTCS as a functional (i.e., non-structural) encephalopathy that shares key clinical and neurophysiological features with delirium, with EEG slowing reflecting widespread, often reversible cortical dysfunction. By capturing these transient yet clinically critical changes, clinical EEG—quantified via the granular, multifaceted GTE—offers a novel tool for diagnosing PTA/PTCS, stratifying its severity, and objectively monitoring its evolution in intensive care unit and subacute rehabilitation settings.

Severely brain-injured patients may enter a spectrum of conditions collectively known as disorders of consciousness. This spectrum includes clinical conditions such as unresponsive wakefulness syndrome or minimally conscious state, where the behavioural assessment of consciousness can often be deceptive. To bridge this dissociation, neuroimaging techniques are employed to identify the residual brain functions. Each neuroimaging modality imperfectly captures distinct aspects of brain preservation—functional, anatomical, or both. In this study, we adopt a comprehensive approach by integrating the neurophysiology and neuroimaging modalities available from the standard and advanced clinical assessments through interpretable machine learning. The electrophysiological modalities included high-density EEG (resting state and task), whereas neuroimaging modalities included anatomical and resting-state functional MRI, diffusion MRI and 18F-fluorodeoxyglucose PET. Our investigation reveals that specific modalities, such as functional assessments, provide comprehensive insights into the currently evaluated state of consciousness, the diagnosis of the patients. Conversely, structural modalities offer valuable information about the patient's evolution within the consciousness spectrum. We validate the proposed analysis with data coming from other centres with different acquisition parameters. Importantly, we demonstrate that model performance improves with an increase in the number of modalities. We observe a higher inter-modality disagreement for minimally conscious state patients and those patients who improve. Lastly, we observe a difference in feature importances between diagnosis and prognosis, with an interaction between modality and anatomical structures: some subcortical markers tend to contribute more to prognosis, while other cortical markers are more informative for diagnosis. This integrative multimodal and machine learning methodology presents a promising avenue for a more nuanced understanding of disorders of consciousness, contributing to enhanced diagnostic precision, prognostic capabilities and the personalization of rehabilitative strategies in clinical practice.

Historically, individuals with disorders of consciousness (DoC) have often been subject to prognostic pessimism and therapeutic nihilism, leading to clinical decisions that became self-fulfilling prophecies. Recent advances in neurodiagnostics -particularly multimodal assessments of consciousness- offer new opportunities to reduce diagnostic ambiguity and to potentially improve rehabilitation outcomes. These developments have the potential to support more effective care planning. Given their central role in surrogate decision-making, informal caregivers are increasingly recognised as key participants in this evolving process. Yet, little is known about the distribution of their preferred roles in decision-making, especially in light of emerging, technology-informed models of diagnosis. Two research questions guided a multicenter study within the PerBrain project: (1) To what extent do informal caregivers differ in their preferences regarding control over decision-making and (2) does a majority of informal caregivers prefer a collaborative model over other forms of decision-making? A cross-sectional survey using a modified version of the Control Preferences Scale (CPS) -which measures a person’s preferred level of control in medical decision-making- was conducted with informal caregivers of persons with DoC in three medical units in Italy and Germany between March 2021 and June 2023. The participating medical centers were part of the PerBrain project, which investigates multimodal consciousness assessment. Caregivers were recruited consecutively, and data were analysed using descriptive statistics, chi-square tests, and t-tests to assess cross-national differences. Seventy caregivers completed the survey. Preferences regarding decision-making roles varied: 34 (48.6

Abstract Identifying which severely brain-injured patients retain the capacity for consciousness remains a major challenge in neurocritical care. The perturbational complexity index (PCI) provides a reliable assessment of consciousness capacity, but its reliance on transcranial magnetic stimulation and EEG (TMS-EEG) limits bedside scalability. PCI and brain criticality capture complementary dimensions of brain dynamics: PCI quantifies the complexity of the brain’s evoked response to perturbation, whereas criticality characterizes the intrinsic organization of spontaneous activity. Here, we tested whether resting-state EEG signatures of criticality predict PCI max in disorders of consciousness, extending prior findings from anesthesia to severe brain injury. In 26 patients with vascular, traumatic, or anoxic brain injury, multivariate criticality related features did not generalize PCI max prediction across the full heterogeneous cohort. However, criticality features predicted PCI max when analyses were restricted to non-anoxic patients and when restricting analyses to patients with non-zero PCI max values. These findings suggest that spontaneous criticality measures index the brain’s intrinsic dynamical regime that supports complex perturbational responses, while their correspondence with PCI max depends on whether the injured brain retains sufficient capacity to sustain large-scale evoked responses. Together, our results extend the relationship between resting-state criticality and evoked perturbational complexity to disorders of consciousness and support the development of stratified EEG measures in severe brain injury.

Sleep–wake disturbances are common during post-traumatic confusional state (PTCS), but their objective characterization across the day–night cycle remains limited. In this prospective observational study, 33 adults with subacute moderate-to-severe traumatic brain injury underwent 7 days of wrist actigraphy during inpatient rehabilitation and repeated Confusion Assessment Protocol (CAP) assessment; 15 had ongoing PTCS and 18 had cleared PTCS. Sleep efficiency (SE) quantified nocturnal sleep continuity, whereas wake efficiency (WE) indexed sustained daytime engagement. Patients with ongoing PTCS had lower SE (72.3% vs 82.8%; p = 0.019; d = 0.92) and WE (64.4% vs 84.2%; p = 0.001; d = 1.37). SE and WE were moderately correlated (ρ = 0.42; VIF = 1.15). In univariable models, higher SE (OR per 10-point increase 0.37, 95% CI 0.15–0.90) and WE (OR 0.28, 95% CI 0.11–0.67) were associated with lower odds of ongoing PTCS; WE remained independently associated in the joint model (OR 0.33, 95% CI 0.14–0.81). Associations with confusional severity persisted after excluding CAP sleep and arousal items. Lower SE was associated with agitation, lower WE with spatiotemporal disorientation, and psychotic-type symptoms with lower values of both. These findings indicate complementary nocturnal and daytime alterations during PTCS and support actigraphy as a complement to clinical characterization, warranting validation in larger cohorts.

BACKGROUND AND OBJECTIVE:Our primary aim was to externally validate previously developed machine-learning (ML) models for predicting the probability of tracheostomy decannulation after 3 months from admission to rehabilitation inpatient in patients with severe Acquired Brain Injury (sABI) using a new external and temporally-independent multicentric prospective dataset. A secondary aim was to evaluate the timing of decannulation and to assess model calibration and clinical net benefit. METHODS:External validation data was collected within the PRABI study, comprising 435 sABI patients admitted between January 2020 and April 2024 across four centers. A previously trained ensemble model and a AdaBoost SVR model were used to predict decannulation probability and timing on such external dataset, respectively. Performance was assessed using metrics such as accuracy, Area Under the Receiver Operating Characteristic curve (AUROC), sensitivity, and median absolute error. RESULTS:The external validation dataset included 402 patients. The ensemble model achieved an accuracy of 81.8 % and an AUROC of 0.85 for decannulation probability, with sensitivity and specificity of 76.4 % and 86.2 %, respectively. The AdaBoost SVR model predicted decannulation timing with a median absolute error of 26.2 days and an accuracy of 76.2 % when predictions were dichotomized at the 90-days threshold. CONCLUSIONS:This study successfully validated the ML models on an independent dataset, demonstrating their robustness and generalizability. Accurate prediction of decannulation probability and timing is crucial for optimizing the management of sABI patients, reducing infection risks, enhancing recovery, and facilitating smoother transitions to home care. External validation is a critical step for ensuring the reliability of ML models in diverse clinical settings, paving the way for their integration into clinical practice.

BackgroundGuillain-Barré syndrome (GBS) is an acute immune-mediated polyradiculoneuropathy that may follow infectious triggers and can progress to severe weakness, cranial nerve involvement, autonomic dysfunction, and respiratory failure. Cytomegalovirus (CMV)-associated GBS is often linked to a more severe clinical course. Although intravenous immunoglobulin (IVIG) and plasma exchange are established first-line treatments, management becomes challenging when patients deteriorate after initial therapy, particularly when distinguishing poor prognosis from treatment-related fluctuation (TRF).Case presentationWe report the case of a 42-year-old woman who developed progressive paresthesias, diffuse pain, gait disturbance, areflexia, facial involvement, dysphagia, dysarthria, autonomic dysfunction, and later respiratory failure. Cerebrospinal fluid analysis showed albuminocytologic dissociation, electrodiagnostic studies supported acute polyradiculoneuropathy, and MRI demonstrated contrast enhancement of the facial nerve roots and cauda equina. Serum testing revealed CMV IgM positivity with detectable CMV DNA, consistent with CMV-associated GBS. The patient received IVIG and ganciclovir. After initial stabilization following the first IVIG course, she experienced sudden respiratory deterioration requiring intubation. Given the temporal pattern of stabilization followed by worsening, the episode was interpreted as TRF occurring in a patient with otherwise poor prognostic features. A second IVIG cycle was administered, followed by gradual respiratory and neurological improvement.DiscussionThis case illustrates the clinical difficulty of deciding whether repeated immunotherapy is justified in severe GBS. Current evidence discourages routine second IVIG courses in patients with poor prognosis who fail to respond; however, this recommendation does not necessarily apply to TRF, where renewed immunotherapy may be considered. In this patient, post-IVIG stabilization followed by acute deterioration supported the interpretation of TRF; persistent CMV viremia was considered a possible marker of ongoing immune stimulation.ConclusionCMV-associated GBS may follow a severe and fluctuating course. Careful distinction between poor prognosis, nonresponse, and treatment-related fluctuation is essential because it directly influences therapeutic decision-making. Close monitoring, individualized immunotherapy, intensive supportive care, and early rehabilitation remain central to optimizing outcomes in severe GBS.

Chronic migraine (CM) is a highly disabling condition, affecting about 2% of the global population. Non-pharmacological treatments can be optimal for their non-invasive nature. This prospective, randomized, double-blind, controlled trial aimed to test the efficacy of therapeutic neuroscience education (TNE) in CM. Early response biomarkers were also evaluated. A total of 80 CM patients were consecutively enrolled and randomly allocated to TNE or a general education program. Treatment effectiveness was evaluated at baseline (T1) and 2 months after the end of treatment (T4). We collected the responses to disability and comorbidity questionnaires at the start (T1) and end of treatment (T3, 10 weeks after start). Early response biomarkers were evaluated at screening (T0) and mid-way through the process (T2, 5 weeks after start). We expected that TNE would provide a greater benefit than the general education program, which served as the primary outcome of this study. We also expected that a change in clinical and neurophysiological measures could potentially occur, reflecting plasticity-induced reorganization and predicting clinical response. This is the first study selectively exploring the effect of TNE as a standalone treatment for CM. A new, effective treatment regime without interactions with other medication could be of great interest as an addition to migraine therapeutic strategies.

IntroductionPatients with severe acquired brain injury have a high risk of developing clinical complications that affect clinical outcome and rehabilitation program. Early identification of clinical complications would allow to treat them appropriately and to prevent their worsening. However, available clinical scales for recording clinical complications are not appropriately tailored for this population. The present multicenter study aimed at developing and validating a new scale to categorize the clinical complications: the Clinical Complication Scale of the Fondazione Don Gnocchi (FDG-CCS).MethodsSix Intensive Neurorehabilitation Units enrolled consecutively admitted patients with severe brain injury. Demographic, anamnestic, and clinical data were collected at study entry. For each enrolled patient, two independent examiners (A and B) administered the FDG-CCS considering 2 weeks as an observation time window. Concurrently, a third examiner (C) administered the Comorbidities Coma Scale. The blinded examinations were analyzed to assess the inter-rater agreement (A vs. B) and the concurrent validity of the FDG-CCS with respect to the Comorbidities Coma Scale (C).ResultsA total of 42 patients (22 patients with and 20 emerged from prolonged disorder of consciousness) were enrolled. The FDG-CCS total score did not differ in the two subgroups of patients. Metabolic (examiner A = 33%; examiner B = 43%), gastro-intestinal (A = 31%; B = 26%), cardio-vascular (A = 26%; B = 29%), respiratory (A = 21%; B = 21%), and musculo-skeletal disorders (A = 19%; B = 14%) were the most frequent complications. Inter-rater agreement for the total score of the FDG-CCS resulted to be good (intra-class correlation coefficient = 0.865; p < 0.05), and the FDG-CCS total score correlated significantly with the total score of the Comorbidities Coma Scale (A, ρ = 0.356; p = 0.01; B, ρ = 0.317; p = 0.02).DiscussionThe present multicenter study proposed and validated a novel clinical tool for the categorization of clinical complications of patients with severe brain injury. This clinical tool could help the rehabilitation team for planning tailored treatment and prevention of clinical complications that negatively impact patients’ outcomes and hamper rehabilitation programs.

Background: Action Observation Therapy (AOT) and Neuromuscular Electrical Stimulation (NMES) are widely adopted techniques for upper-limb rehabilitation in post-stroke patients. Although AOT and NMES are individually effective, studies investigating a potential synergistic effect on enhancing rehabilitative outcomes are lacking. Objectives: This study aims at comparing the effect of AOT and NMES applied together (AOT-NMES) on muscle synergies with respect to either AOT alone or a Motor Neutral Observation treatment alone (MNO, involving neither AOT nor NMES) on motor function recovery of upper limb. Design: Randomized Controlled Trial (RCT) with n = 60 post-stroke patients with resulting upper limb disability, randomly allocated (1:1:1 ratio) in three interventional arms: AOT-NMES (n = 20), AOT (n = 20) and MNO (n = 20). Methods and Analyses: All rehabilitation treatments will consist of n°15 60 min-long rehabilitative sessions. Primary outcome measure will be upper limb motor function, assessed using the Fugl-Meyer Assessment scale for upper limb (FM-UL), collected at the baseline (T0), post-intervention (T1) and at follow-up (T2, 6-months after T1). Other outcome measures will be collected through a multidimensional evaluation including assessing stroke-associated quality of life, neurophysiological data, biomechanical and MRI measures. The innovative protocol will also be evaluated for usability and safety. Discussion: We expect to determine the efficacy, usability and safety of the AOT-NMES rehabilitation approach for the recovery of upper limb motor function in post-stroke patients. The obtained results will also help reveal the neural underpinnings of motor recovery, as assessed by neurophysiological data, biomechanical and MRI measures.

Traumatic brain injury (TBI) affects millions of people worldwide and often results in long-term disabilities. Clinical outcomes vary widely even among patients with similar injury severity, partly due to systemic neuroinflammatory responses mediated by pro- and anti-inflammatory cytokines. Genetic polymorphisms in cytokine-coding genes may influence cytokine expression, thereby affecting rehabilitation and prognosis. We analyzed genetic polymorphisms in the TNF-α, IL-6, IL-6 receptor, IL-1β, and IL-10 genes in 28 subacute TBI patients undergoing rehabilitation. Clinical outcomes were assessed using the Glasgow Outcome Scale Extended (GOSE) and domain-specific scales for cognitive, motor, and functional recovery. Results were correlated with genetic profiles to identify potential predictive biomarkers. The IL-6-174 (GG) and IL-6R 1073 (AA) genotypes correlated with worse GOSE scores (p = 0.02 and p = 0.01, respectively). Co-segregation of IL-6-174 - IL-6R 1073 G-A alleles was linked to poorer outcomes (p = 0.01). Patients with the TNF-α-308 (GA) genotype showed less improvement in Barthel and Mobility scores (p = 0.001 and p = 0.01, respectively) and had a higher incidence of post-traumatic confusional state after rehabilitation (p = 0.03). Overall, the TNF-α-308(GA), IL-6 -174(GG), and IL-6R 1073(AA) genotypes negatively impact rehabilitation outcomes, likely due to their role in enhancing neuroinflammation. Larger studies are needed to develop personalized therapies tailored to genetic profiles, aiming to improve rehabilitation outcomes for TBI patients.

Post-traumatic amnesia (PTA), recently conceptualized as part of the broader syndrome known as post-traumatic confusional state (PTCS), marks a critical phase of recovery following traumatic brain injury (TBI). Indeed, this state is characterized not only by anterograde memory impairment but also by disorientation, agitation, and attention deficits. Given the phenotypic overlap between PTA/PTCS and delirium-both marked by fluctuating cognitive and attentional disturbances-electroencephalography (EEG) represents a promising tool for elucidating shared pathophysiological mechanisms. While delirium is typically associated with diffuse EEG slowing and the presence of slow-wave activity (SWA), thought to reflect underlying global cortical disruption, it remains unclear whether PTCS exhibits similar EEG underpinnings. In this prospective longitudinal study, we assessed dynamic EEG correlates of PTCS using the grand total EEG (GTE) score, a composite measure that incorporates background slowing and superimposed SWA. We enrolled 42 consecutive TBI patients (mean age = 40.3 ±15 years) classifying them at baseline (T0) into two groups based on the Confusion Assessment Protocol (CAP): those in PTA/PTCS (N = 22; median time from injury 24 days; median CAP total score 5) and those already emerged from PTA/PTCS (i.e., TBI controls, N = 20; median time from injury 24 days; median CAP total score 0). At T0, patients with PTA/PTCS exhibited significantly higher baseline GTE scores compared with TBI controls, 16.6 ± 4.5 versus 5.1 ± 2.8; t(35.75) = 10.04, p < 0.0001; d = 3.04, reflecting severe EEG abnormalities characterized by diffuse slowing and disrupted rhythmic activity, as captured by the GTE subdomains. Longitudinal follow-up (T1) at emergence from PTCS revealed a significant EEG improvement paralleling clinical recovery, with GTE scores dropping from 16.5 (interquartile range [IQR]: 6.5) to 8, IQR: 3.75; t(21) = 8.03, p < 0.0001; d = 1.71, confirming EEG's sensitivity to dynamic clinical changes. Furthermore, the severity of EEG abnormalities at follow-up (T1) significantly correlated with the total duration of PTA/PTCS (ρ = 0.56, p < 0.0001), underscoring EEG's potential as an objective biomarker for disease burden and for monitoring recovery trajectories. Notably, these findings were independent of pharmacological confounders, as medication regimens were not significantly different across groups and time points. Our results support a reconceptualization of PTA/PTCS as a functional (i.e., non-structural) encephalopathy that shares key clinical and neurophysiological features with delirium, with EEG slowing reflecting widespread, often reversible cortical dysfunction. By capturing these transient yet clinically critical changes, clinical EEG-quantified via the granular, multifaceted GTE-offers a novel tool for diagnosing PTA/PTCS, stratifying its severity, and objectively monitoring its evolution in intensive care unit and subacute rehabilitation settings.

BACKGROUND:Improving prognostication in patients with a prolonged disorder of consciousness (pDoC) is among the most challenging issues in neurorehabilitation. The aim of this Italian multisite prospective longitudinal study was to identify valuable predictors of the complete recovery of consciousness (emergence from Minimally Conscious State, eMCS) at 3 months (T1) from the admission in intensive rehabilitation units (IRUs) in pDoC (T0). METHODS:Patients with Unresponsive Wakefulness Syndrome (UWS) or MCS admitted within 3 months of injury to 4 Italian IRUs were included. Demographic, clinical, and neurophysiological data were collected at T0, and a clinical diagnosis of consciousness (UWS, MCS-, MCS+) was established at T0 and T1 using the Coma Recovery Scale-Revised (CRS-R). RESULTS:One hundred forty-three patients were initially included and 131 completed follow-ups at T1: (76 males; median age: 69 years [IQR = 23]; VS/UWS: 51, MCS-: 29, MCS+: 51; etiology: 33 traumatic, 14 anoxic, 24 ischemic, 55 hemorrhagic, 5 other; median time post-injury: 40 days [IQR = 23]). At T1, 77 patients were eMCS, and 10 improved their clinical diagnosis. Among the clinical and neurophysiological independent variables, a higher CRS-R visual sub-score and the presence of EEG reactivity to eye opening at T0 were the best independent predictors of eMCS. Out of 77 eMCS, 18 reached a moderate disability (Glasgow Outcome Scale Extended-GOSE > 4), while the others persisted with a severe disability (GOS-E ≤ 4). CONCLUSIONS:A multimodal assessment can help identify patients who achieve functionally relevant improvements and thus better support clinicians when communicating with caregivers. TRIAL REGISTRATION:ClinicalTrials.gov registration number: NCT04495192.

IntroductionStroke-related brain changes have traditionally been studied through oscillatory electroencephalographic (EEG) activity, but recent evidence highlights the value of aperiodic components. This pilot randomized controlled trial aimed to assess stroke-related aperiodic EEG changes following virtual reality-based robotic rehabilitation using the Spectral Exponent Index (SEI).MethodsNineteen patients with subacute stroke were randomized to unilateral (n = 9) or bilateral (n = 10) upper limb training with a robotic exoskeleton (30 sessions). EEG was recorded at rest before (T0), after (T1), and at 1-week follow-up (T2). SEI was computed for hemispheric and sensorimotor clusters, in affected (AH) and unaffected (UH) hemispheres. Clinical evaluation was performed at T0 and T1 with validated clinical scales.ResultsAt T0, the SEI in the sensorimotor cluster of the AH was significantly lower than in the UH. At T1, the SEI in the AH increased together with clinical improvements in upper limb motor function. At T2, the SEI in the AH decreased again and was lower than in the UH. No differences were found between unilateral and bilateral groups.DiscussionRobotic rehabilitation modulated the aperiodic EEG background in the affected hemisphere of patients with stroke, particularly in sensorimotor areas. These SEI changes mirrored motor recovery, suggesting that it may represent a useful biomarker to track localized neural mechanisms of functional improvement after stroke. No differences between unilateral and bilateral training likely reflect the pilot sample size or shared cortical mechanisms of action activated by both rehabilitation approaches.Clinical Trial RegistrationClinicalTrials.gov registration number: NCT05176600.

Traumatic brain injury (TBI), a leading cause of mortality and disability, recognizes a primary, immediate injury due to external forces, and a secondary phase that includes inflammation that can lead to complications such as the post-traumatic confusional state (PTCS), potentially impacting long-term neurological recovery. An earlier identification of these complications, including PTCS, upon admission to intensive rehabilitation units (IRU) could possibly allow the design of personalized rehabilitation protocols in the immediate post-acute phase of moderate-to-severe TBI. The present study aims to identify potential biomarkers to distinguish between TBI patients with and without PTCS. We analyzed cellular and molecular mechanisms involved in neuroinflammation (IL-6, IL-1β, IL-10 cytokines), neuroendocrine function (norepinephrine, NE, epinephrine, E, dopamine), and neurogenesis (glial cell line-derived neurotrophic factor, GDNF, insuline-like growth factor 1, IGF-1, nerve growth factor, NGF, brain-derived growth factor, BDNF) using enzyme-linked immunosorbent assay (ELISA), comparing results between 29 TBI patients (17 with PTCS and 12 non-confused) and 34 healthy controls (HC), and correlating results with an actigraphy-derived sleep efficiency parameter. In TBI patients compared to HC, serum concentration of (1) pro-inflammatory IL-1β cytokine was significantly increased while that of anti-inflammatory IL-10 cytokine was significantly decreased; (2) NE, E and DA were significantly increased; (3) GDNF, NGF and IGF-1 were significantly increased while that of BDNF was significantly decreased. Importantly, IL-10 serum concentration was significantly lower in PTCS than in non-confused patients, correlating positively with an improved actigraphy-derived sleep efficiency parameter. An anti-inflammatory environment may be associated with better prognosis after TBI.

Background: Healthy cognitive functioning is a primary component of well-being, independence, and successful aging. Cognitive deficits can arise from various conditions, such as brain injury, mental illness, and neurological disorders. Rehabilitation is a highly specialized service limited to patients who have access to institutional settings. In response to this unmet need, telehealth solutions are ideal for triggering the migration of care from clinics to patients’ homes. Objectives: The aim of EARLY-COGN^3 will be threefold: (1) to test the efficacy of a digital health at-home intervention (tele@cognitive protocol) as compared to an unstructured cognitive at-home rehabilitation in a cohort of patients with Chronic Neurological Diseases (CNDs); (2) to investigate its effects on the biomolecular and neurophysiological marker hypothesizing that people with CNDs enrolled in this telerehabilitation program will develop changes in biological markers and cortical and subcortical patterns of connectivity; (3) to analyze potential cognitive, neurobiological, and neurophysiological predictors of response to the tele@cognitive treatment. Method: In this single-blind, randomized, and controlled pilot study, we will assess the short- and long-term efficacy of cognitive telerehabilitation protocol (tele@cognitive) as compared to an unstructured cognitive at-home rehabilitation (Active Control Group—ACG) in a cohort of 60 people with Mild Cognitive Impairment (MCI), Subjective Cognitive Complaints (SCCs), or Parkinson’s Disease (PD). All participants will undergo a clinical, functional, neurocognitive, and quality of life assessment at the baseline (T0), post-treatment (5 weeks, T1), and at the 3-month (T2) follow-up. Neurophysiological markers and biomolecular data will be collected at T0 and T1. Conclusions: EARLY-COGN^3 project could lead to a complete paradigm shift from the traditional therapeutic approach, forcing a reassessment on how CNDs could take advantage of a digital solution. (clinicaltrials.gov database, ID: NCT06657274)