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The new scale (Unified Balance Scale) holds proven measurement properties and may be a candidate tool for "bed to community" balance measurement for patients with balance problems within the neuro-rehabilitation setting. Future studies are warranted to explore further its external validity and other clinical properties, as well as to improve its usability.

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Accurate outcome detection in neuro-rehabilitative settings is crucial for appropriate long-term rehabilitative decisions in patients with disorders of consciousness (DoC). EEG measures derived from high-density EEG can provide helpful information regarding diagnosis and recovery in DoC patients. However, the accuracy rate of EEG biomarkers to predict the clinical outcome in DoC patients is largely unknown. This study investigated the accuracy of psychophysiological biomarkers based on clinical EEG in predicting clinical outcomes in DoC patients. To this aim, we extracted a set of EEG biomarkers in 33 DoC patients with traumatic and nontraumatic etiologies and estimated their accuracy to discriminate patients’ etiologies and predict clinical outcomes 6 months after the injury. Machine learning reached an accuracy of 83.3% (sensitivity = 92.3%, specificity = 60%) with EEG-based functional connectivity predicting clinical outcome in nontraumatic patients. Furthermore, the combination of functional connectivity and dominant frequency in EEG activity best predicted clinical outcomes in traumatic patients with an accuracy of 80% (sensitivity = 85.7%, specificity = 71.4%). These results highlight the importance of functional connectivity in predicting recovery in DoC patients. Moreover, this study shows the high translational value of EEG biomarkers both in terms of feasibility and accuracy for the assessment of DoC.

Background Due to the lack of high-quality evidence which has hindered the development of evidence-based guidelines, there is a need to provide general guidance on cranioplasty (CP) following traumatic brain injury (TBI), as well as identify areas of ongoing uncertainty via a consensus-based approach. Methods The international consensus meeting on post-traumatic CP was held during the International Conference on Recent Advances in Neurotraumatology (ICRAN), in Naples, Italy, in June 2018. This meeting was endorsed by the Neurotrauma Committee of the World Federation of Neurosurgical Societies (WFNS), the NIHR Global Health Research Group on Neurotrauma, and several other neurotrauma organizations. Discussions and voting were organized around 5 pre-specified themes: (1) indications and technique, (2) materials, (3) timing, (4) hydrocephalus, and (5) paediatric CP. Results The participants discussed published evidence on each topic and proposed consensus statements, which were subject to ratification using anonymous real-time voting. Statements required an agreement threshold of more than 70% for inclusion in the final recommendations. Conclusions This document is the first set of practical consensus-based clinical recommendations on post-traumatic CP, focusing on timing, materials, complications, and surgical procedures. Future research directions are also presented.

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Objective: To assess the internal construct validity (ICV) of the five Brain Injury Rehabilitation Trust Personality Questionnaires (BIRT-PQ) with Classical Test Theory methods. Methods: Multicenter cross-sectional study involving 11 Italian rehabilitation centers. BIRT-PQs were administered to patients with severe Acquired Brain Injury and their respective caregivers. ICV was assessed by the mean of an internal consistency analysis (ICA) and a Confirmatory Factor Analysis (CFA). Results: Data from 154 patients and their respective caregivers were pooled, giving a total sample of 308 subjects. Despite good overall values (alphas ranging from 0.811 to 0.937), the ICA revealed that several items within each scale did not contribute as expected to the total score. This result was confirmed by the CFA, which showed the misfit of the data to a unidimensional model (RMSEA ranging from 0.077 to 0.097). However, after accounting for local dependency found within the data, fitness to a unidimensional model improved significantly (RMSEA ranging from 0.050 to 0.062). Conclusion: Despite some limitations, our analyses demonstrated the lack of ICV for the BIRT-PQ total scores. It is envisaged that a more comprehensive ICV analysis will be performed with Rasch analysis, aiming to improve both the measurement properties and the administrative burden of each BIRT-PQ.

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