Artificial neural network analysis of factors affecting functional independence recovery in patients with lumbar stenosis after neurosurgery treatment: An observational cohort study

Background and aim

Lumbar spinal stenosis (LSS) is a leading cause of low back pain and lower limbs pain often associated with functional impairment which entails the loss or the impairment of independence in older adults. Conservative treatment is effective in a small percentage of patients, while a significant percentage undergo surgery, even if often without a complete resolution of clinical symptoms and motor deficits. The aim of the study is to identify clinical and demographic prognostic factors characterising the patients who would benefit most from surgical treatment in relation to the functional independence recovery using an innovative approach based on an artificial neural network.

Methods

Adult patients with LSS and indication of neurosurgical treatment were enrolled in the study. Clinical evaluation was performed in the preoperative-phase (into the 48 h before surgery) and after two months. Clinical battery investigated the motor, functional, cognitive, behavioural, and pain status. Demographics and clinical characteristics were analysed via Artificial Neural Network (ANN) using 24 input variables, 2 hidden layers and a single final output layer to predict the outcome. ANN results were compared with those of a multiple linear regression.

Results

108 patients were included in the study and 90 of them [66.5 ± 12.8 years; 27.8 % F] were submitted to surgery treatment and completed longitudinal evaluation. Statistically significant improvement was recorded in all clinical scales comparing pre- and post-surgery. The ANN results showed a prediction ability up to 81 %. Disability, functional limitations, and pain concerning clinical assessment and stature, onset and age about demographic characteristics are the main variables impacting on surgical outcome.

Conclusions

ANN can support clinical decision making, using clinical and demographic characteristics of patients with LSS identifying the characteristics of those who might benefit more from the surgical treatment in terms of global functional recovery.

Neuroanatomical correlates of peripersonal space: bridging the gap between perception, action, emotion and social cognition

Peripersonal space (PPS) is a construct referring to the portion of space immediately surrounding our bodies, where most of the interactions between the subject and the environment, including other individuals, take place. Decades of animal and human neuroscience research have revealed that the brain holds a separate representation of this region of space: this distinct spatial representation has evolved to ensure proper relevance to stimuli that are close to the body and prompt an appropriate behavioral response. The neural underpinnings of such construct have been thoroughly investigated by different generations of studies involving anatomical and electrophysiological investigations in animal models, and, recently, neuroimaging experiments in human subjects. Here, we provide a comprehensive anatomical overview of the anatomical circuitry underlying PPS representation in the human brain. Gathering evidence from multiple areas of research, we identified cortical and subcortical regions that are involved in specific aspects of PPS encoding.We show how these regions are part of segregated, yet integrated functional networks within the brain, which are in turn involved in higher-order integration of information. This wide-scale circuitry accounts for the relevance of PPS encoding in multiple brain functions, including not only motor planning and visuospatial attention but also emotional and social cognitive aspects. A complete characterization of these circuits may clarify the derangements of PPS representation observed in different neurological and neuropsychiatric diseases.

Italian adaptation of the Multidimensional Iowa Suggestibility Scale (MISS)

Background

Suggestibility is a personality trait that reflects a general tendency to accept messages. The Multidimensional Iowa Suggestibility Scale (MISS) is a self-report scale developed to measure the degree of individuals' perceptions of their suggestibility. This study aimed to adapt the MISS in an Italian sample.

Methods

We conducted two studies. In the first study, 345 subjects (270 females (78%), mean age = 36.21 years ± 14.06 SD) completed the translated Italian version of the MISS, composed of five subscales (consumer suggestibility; persuadability; sensation contagion; physiological reactivity; peer conformity). We investigated the structural validity of the scale through confirmatory factor analysis (CFA) testing four measurement models (unidimensional, four-factor, hierarchical four factors, and bifactor) and explored reliability in terms of internal consistency through the McDonald's omega. In the second study, we cross-validated the MISS on a new independent sample. We enrolled 277 participants (196 females (71%), mean age 30.56, SD = 12.58) who underwent the new version of the scale. We performed factor analyses to test structural validity and compared four measurement models. Then, we investigated reliability and conducted a latent variable analysis to explore divergent validity.

Results

The CFA in the first study revealed a bifactor solution of the MISS. This structure was interpretable and provided an adequate fit for the data. The final version of the scale was reduced to forty-six items with globally good indices of adaptation. The scale also demonstrated acceptable reliability in terms of internal consistency through the McDonald's Hierarchical Omega. In the second study, we found that the bifactor structure was confirmed. Factor loadings inspection revealed that there was no justification to report only the separate scores for the subscales. We also found that the scale showed good internal consistency, but mixed evidence for divergent validity.

Conclusions

In the end, the Italian version of the MISS demonstrated good psychometric properties which will be discussed in detail below.

Electrophysiological Screening to Assess Foot Drop Syndrome in Severe Acquired Brain Injury in Rehabilitative Settings

BACKGROUND

Foot drop syndrome (FDS), characterized by severe weakness and atrophy of the dorsiflexion muscles of the feet, is commonly found in patients with severe acquired brain injury (ABI). If the syndrome is unilateral, the cause is often a peroneal neuropathy (PN), due to compression of the nervous trunk on the neck of the fibula at the knee level; less frequently, the cause is a previous or concomitant lumbar radiculopathy. Bilateral syndromes are caused by polyneuropathies and myopathies. Central causes, due to brain or spinal injury, mimic this syndrome but are usually accompanied by other symptoms, such as spasticity. Critical illness polyneuropathy (CIP) and myopathy (CIM), isolated or in combination (critical illness polyneuromyopathy, CIPNM), have been shown to constitute an important cause of FDS in patients with ABI. Assessing the causes of FDS in the intensive rehabilitation unit (IRU) has several limitations, which include the complexity of the electrophysiological tests, limited availability of neurophysiology consultants, and the severe disturbance in consciousness and lack of cooperation from patients.

OBJECTIVES

We sought to propose a simplified electrophysiological screening that identifies FDS causes, particularly PN and CIPNM, to help clinicians to recognize the significant clinical predictors of poor outcomes in severe ABI at admission to IRU.

METHODS

This prospective, single-center study included 20 severe ABI patients with FDS (11 females/9 males, mean age 55.10 + 16.26; CRS-R= 11.90 + 6.32; LCF: 3.30 + 1.30; DRS: 21.45 + 3.33), with prolonged rehabilitation treatment (≥2 months). We applied direct tibialis anterior muscle stimulation (DMS) associated with peroneal nerve motor conduction evaluation, across the fibular head (NCS), to identify CIP and/or CIM and to exclude demyelinating or compressive unilateral PN.

RESULTS

At admission to IRU, simplified electrophysiological screening reported four unilateral PN, four CIP and six CIM with a CIPNM overall prevalence estimate of about 50%. After 2 months, the CIPNM group showed significantly poorer outcomes compared to other ABI patients without CIPNM, as demonstrated by the lower probability of achieving endotracheal-tube weaning (20% versus 90%) and lower CRS-R and DRS scores. Due to the subacute rehabilitation setting of our study, it was not possible to evaluate the motor results of recovery of the standing position, functional walking and balance, impaired by the presence of unilateral PN.

CONCLUSIONS

The implementation of the proposed simplified electrophysiological screening may enable the early identification of unilateral PN or CIPNM in severe ABI patients, thereby contributing to better functional prognosis in rehabilitative settings.

The Role of Treatment-Related Parameters and Brain Morphology in the Lesion Volume of Magnetic-Resonance-Guided Focused Ultrasound Thalamotomy in Patients with Tremor-Dominant Neurological Conditions

PURPOSE

To determine the best predictor of lesion volume induced by magnetic resonance (MR)-guided focused ultrasound (MRgFUS) thalamotomy in patients with tremor-dominant symptoms in Parkinson's disease (PD) and essential tremor (ET) patients.

METHODS

Thirty-six neurological patients with medication-refractory tremor (n°19 PD; n°17 ET) were treated using a commercial MRgFUS brain system (Exablate Neuro 4000, Insightec) integrated with a 1.5 T MRI unit (Sigma HDxt; GE Medical System). Linear regression analysis was used to determine how the demographic, clinical, radiological (Fazekas scale), volumetric (total GM/WM/CSF volume, cortical thickness), and MRgFUS-related parameters [Skull Density Ratio (SDR), n° of transducer elements, n° of sonications, skull area, maximal energy delivered (watt), maximal power delivered (joule), maximal sonication time delivered, maximal mean temperature reached (T°C_max), accumulated thermal dose (ATD)] impact on ventral intermediate (VIM)-thalamotomy-related 3D volumetric lesions of necrosis and edema.

RESULTS

The VIM thalamotomy was clinically efficacious in improving the tremor symptoms of all the patients as measured at 1 week after treatment. Multiple regression analysis revealed that T°C_max and n° of transducer elements were the best predictors of the necrosis and edema volumes. Moreover, total WM volume also predicted the size of necrosis.

CONCLUSIONS

Our study provides new insights into the clinical MRgFUS procedures that can be used to forecast brain lesion size and improve treatment outcomes.

Metaverse in Mental Health: The Beginning of a Long History

PURPOSE OF REVIEW

We review the first pilot studies applying metaverse-related technologies in psychiatric patients and discuss the rationale for using this complex federation of technologies to treat mental diseases. Concerning previous virtual-reality applications in medical care, metaverse technologies provide the unique opportunity to define, control, and shape virtual scenarios shared by multi-users to exploit the "synchronized brains" potential exacerbated by social interactions.

RECENT FINDINGS

The application of an avatar-based sexual therapy program conducted on a metaverse platform has been demonstrated to be more effective concerning traditional sexual coaching for treating female orgasm disorders. Again, a metaverse-based social skills training program has been tested on children with autism spectrum disorders, demonstrating a significant impact on social interaction abilities. Metaverse-related technologies could enable us to develop new reliable approaches for treating diseases where behavioral symptoms can be addressed using socio-attentive tasks and social-interaction strategies.

Psycho-Neuroendocrinology in the Rehabilitation Field: Focus on the Complex Interplay between Stress and Pain

Chronic stress and chronic pain share neuro-anatomical, endocrinological, and biological features. However, stress prepares the body for challenging situations or mitigates tissue damage, while pain is an unpleasant sensation due to nociceptive receptor stimulation. When pain is chronic, it might lead to an allostatic overload in the body and brain due to the chronic dysregulation of the physiological systems that are normally involved in adapting to environmental challenges. Managing stress and chronic pain (CP) in neurorehabilitation presents a significant challenge for healthcare professionals and researchers, as there is no definitive and effective solution for these issues. Patients suffering from neurological disorders often complain of CP, which significantly reduces their quality of life. The aim of this narrative review is to examine the correlation between stress and pain and their potential negative impact on the rehabilitation process. Moreover, we described the most relevant interventions used to manage stress and pain in the neurological population. In conclusion, this review sheds light on the connection between chronic stress and chronic pain and their impact on the neurorehabilitation pathway. Our results emphasize the need for tailored rehabilitation protocols to effectively manage pain, improve treatment adherence, and ensure comprehensive patient care.

Evolution of Severe Closed Head Injury: Assessing Ventricular Volume and Behavioral Measures at 30 and 90 Days Post-Injury

Background: Assessing functional outcomes in Severe Closed Head Injury (SCHI) is complex due to brain parenchymal changes. This study examines the Ventricles to Intracranial Volume Ratio (VBR) as a metric for these changes and its correlation with behavioral scales. Methods: Thirty-one SCHI patients were included. VBR was derived from CT scans at 3, 30, and 90 days post-injury and compared with Levels of Cognitive Functioning (LCF), Disability Rating Scale (DRS), and Early Rehabilitation Barthel Index (ERBI) assessments at 30 and 90 days. Results: Ten patients were excluded post-decompressive craniectomy or ventriculoperitoneal shunt. Findings indicated a VBR decrease at 3 days, suggesting acute phase compression, followed by an increase from 30 to 90 days, indicative of post-acute brain atrophy. VBR correlated positively with the Marshall score in the initial 72 h, positioning it as an early indicator of subsequent brain atrophy. Nevertheless, in contrast to the Marshall score, VBR had stronger associations with DRS and ERBI at 90 days. Conclusions: VBR, alongside behavioral assessments, presents a robust framework for evaluating SCHI progression. It supports early functional outcome correlations informing therapeutic approaches. VBR's reliability underscores its utility in neurorehabilitation for ongoing SCHI assessment and aiding clinical decisions.

Fractals in Neuropsychology and Cognitive Neuroscience

The fractal dimension of cognition refers to the idea that the cognitive processes of the human brain exhibit fractal properties. This means that certain patterns of cognitive activity, such as visual perception, memory, language, or problem-solving, can be described using the mathematical concept of fractal dimension.The idea that cognition is fractal has been proposed by some researchers as a way to understand the complex, self-similar nature of the human brain. However, it's a relatively new idea and is still under investigation, so it's not yet clear to what extent cognitive processes exhibit fractal properties or what implications this might have for our understanding of the brain and clinical practice. Indeed, the mission of the "fractal neuroscience" field is to define the characteristics of fractality in human cognition in order to differently characterize the emergence of brain disorders.

Wessex Head Injury Matrix in Patients with Prolonged Disorders of Consciousness: A Reliability Study

Introduction: The Wessex Head Injury Matrix (WHIM) was developed to assess patients with disorders of consciousness (DOC) and was tested in terms of inter-rater reliability (IRR) and test-retest reliability (TRR) in the year 2000. The American Congress of Rehabilitation and Medicine reported that IRR and TRR were unproven. We aim to assess the reliability of the WHIM in prolonged DOC patients (PDOC). Methods: A total of 51 PDOC patients (32 unresponsive wakefulness syndrome (UWS/VS) and 19 minimally conscious state (MCS)) who were hosted in a dedicated unit for long-term brain injury care were enrolled. The time from injury ranged from 182 to 3325 days. Two raters administered the Coma Recovery Scale-Revised (CRS-R) and the WHIM to test the IRR and TRR. The TRR was administered two weeks after the first assessment. Results: For the CRS-R, the agreement in IRR and TRR was perfect between the two raters. The agreement for the WHIM ranged from substantial to almost perfect for IRR and from fair to substantial for the TRR. Conclusions: The WHIM showed a strong IRR when administered by expert raters and strongly correlated with the CRS-R. This study provides further evidence of the psychometric qualities of the WHIM and the importance of its use in PDOC patients.

Inducing Cough Reflex by Capsaicin Spray Stimulation in Patients with Acquired Brain Injury: A Preliminary Test and Proof of Concept

Individuals with acquired brain injuries (ABIs) may experience various complications related to poor coughing or impaired cough reflex (including risk of aspiration pneumonia or respiratory infections). For this reason, cough assessment is an important component in the clinical evaluation since patients with ABI are not able to cough voluntarily due to severe motor deficits. When voluntarily coughing is not possible, it is essential for clinical practices to find a quick and minimally invasive way to induce a cough reflex. In the present study, we evaluated the cough reflex in ABI patients using a new method based on a capsaicin spray stimulation test. In total, 150 healthy controls demographically matched with 50 ABI patients were included in this study. Clinical observations demonstrated robust cough response in both healthy controls and ABI patients, as well as the safety and tolerability of capsaicin spray stimulation. ABI patients with dysphagia were characterized by slower and delayed cough responses. Further studies are needed to validate this feasible, less-invasive, and simple-to-comprehend technique in inducing cough reflex. According to this preliminary evidence, we believe that this test might be translated into a simple and effective treatment to improve reflexive cough modulation in ABI patients.

Robot- and Technology-Boosting Neuroplasticity-Dependent Motor-Cognitive Functional Recovery: Looking towards the Future of Neurorehabilitation

The sequelae of neurological disorders are the leading causes of disability in all industrialized countries [...].

Transient Worsening of Dysphagia and Dysarthria after Treatment with Botulinum Toxin in Patients with Acquired Brain Injury

Although botulinum toxin is widely considered an effective and safe treatment for a variety of neurological conditions (such as disabling spasticity), local or systemic adverse effects have often been reported. This study describes three cases of patients with severe acquired brain injury who were receiving speech therapy for recovering dysphagia and dysarthria but showed worsening of these symptoms after receiving BoNT treatment for motor spasticity. To increase clinicians' knowledge of these adverse effects, we present our cases and explore their significance to avoid major complications such as aspiration pneumonia.

MR-Guided Focused Ultrasound for Refractory Epilepsy: Where Are We Now?

Epilepsy is one of the most common neurological diseases in both adults and children. Despite improvements in medical care, 20 to 30% of patients are still resistant to the best medical treatment. The quality of life, neurologic morbidity, and even mortality of patients are significantly impacted by medically intractable epilepsy. Nowadays, conservative therapeutic approaches consist of increasing medication dosage, changing to a different anti-seizure drug as monotherapy, and combining different antiseizure drugs using an add-on strategy. However, such measures may not be sufficient to efficiently control seizure recurrence. Resective surgery, ablative procedures and non-resective neuromodulatory (deep-brain stimulation, vagus nerve stimulation) treatments are the available treatments for these kinds of patients. However, invasive procedures may involve lengthy inpatient stays for the patients, risks of long-term neurological impairment, general anesthesia, and other possible surgery-related complications (i.e., hemorrhage or infection). In the last few years, MR-guided focused ultrasound (MRgFUS) has been proposed as an emerging treatment for neurological diseases because of technological advancements and the goal of minimally invasive neurosurgery. By outlining the current knowledge obtained from both preclinical and clinical studies and discussing the technical opportunities of this therapy for particular epileptic phenotypes, in this perspective review, we explore the various mechanisms and potential applications (thermoablation, blood-brain barrier opening for drug delivery, neuromodulation) of high- and low-intensity ultrasound, highlighting possible novel strategies to treat drug-resistant epileptic patients who are not eligible or do not accept currently established surgical approaches. Taken together, the available studies support a possible role for lesional treatment over the anterior thalamus with high-intensity ultrasound and neuromodulation of the hippocampus via low-intensity ultrasound in refractory epilepsy. However, more studies, likely conceiving epilepsy as a network disorder and bridging together different scales and modalities, are required to make ultrasound delivery strategies meaningful, effective, and safe.

Computer-assisted cognitive rehabilitation in neurological patients: state-of-art and future perspectives

Background and aim

Advances in computing technology enabled researchers and clinicians to exploit technological devices for cognitive training and rehabilitation interventions. This expert review aims to describe the available software and device used for cognitive training or rehabilitation interventions of patients with neurological disorders.

Methods

A scoping review was carried out to analyze commercial devices/software for computerized cognitive training (CCT) in terms of feasibility and efficacy in both clinical and home settings. Several cognitive domains responding to the different patients' needs are covered.

Results

This review showed that cognitive training for patients with neurological diseases is largely covered by several devices that are widely used and validated in the hospital setting but with few translations to remote/home applications. It has been demonstrated that technology and software-based devices are potential and valuable tools to administer remotely cognitive rehabilitation with accessible costs.

Conclusion

According to our results, CCT entails the possibility to continue cognitive training also in different settings, such as home, which is a significant breakthrough for the improvement of community care. Other possible areas of use should be the increase in the amount of cognitive therapy in the free time during the hospital stay.

Application of Machine Learning Algorithms for Prognostic Assessment in Rotator Cuff Pathologies: A Clinical Data-Based Approach

AIM

The overall aim of this proposal is to ameliorate the care of rotator cuff (RC) tear patients by applying an innovative machine learning approach for outcome prediction after arthroscopic repair.

MATERIALS AND METHODS

We applied state-of-the-art machine learning algorithms to evaluate the best predictors of the outcome, and 100 RC patients were evaluated at baseline (T0), after 1 month (T1), 3 months (T2), 6 months (T3), and 1 year (T4) from surgical intervention. The outcome measure was the Costant-Murley Shoulder Score, whereas age, sex, BMI, the 36-Item Short-Form Survey, the Simple Shoulder Test, the Hospital Anxiety and Depression Scale, the American Shoulder and Elbow Surgeons Score, the Oxford Shoulder Score, and the Shoulder Pain and Disability Index were considered as predictive factors. Support vector machine (SVM), k-nearest neighbors (k-NN), naïve Bayes (NB), and random forest (RF) algorithms were employed.

RESULTS

Across all sessions, the classifiers demonstrated suboptimal performance when using both the complete and shrunken sets of features. Specifically, the logistic regression (LR) classifier achieved a mean accuracy of 46.5% ± 6%, while the random forest (RF) classifier achieved 51.25% ± 4%. For the shrunken set of features, LR obtained a mean accuracy of 48.5% ± 6%, and RF achieved 45.5% ± 4.5%. No statistical differences were found when comparing the performance metrics of ML algorithms.

CONCLUSIONS

This study underlines the importance of extending the application of AI methods to new predictors, such as neuroimaging and kinematic data, in order to better record significant shifts in RC patients' prognosis.

LIMITATIONS

The data quality within the cohort could represent a limitation, since certain variables, such as smoking, diabetes, and work injury, are known to have an impact on the outcome.

Neural Plasticity Changes Induced by Motor Robotic Rehabilitation in Stroke Patients: The Contribution of Functional Neuroimaging

Robotic rehabilitation is one of the most advanced treatments helping people with stroke to faster recovery from motor deficits. The clinical impact of this type of treatment has been widely defined and established using clinical scales. The neurofunctional indicators of motor recovery following conventional rehabilitation treatments have already been identified by previous meta-analytic investigations. However, a clear definition of the neural correlates associated with robotic neurorehabilitation treatment has never been performed. This systematic review assesses the neurofunctional correlates (fMRI, fNIRS) of cutting-edge robotic therapies in enhancing motor recovery of stroke populations in accordance with PRISMA standards. A total of 7, of the initial yield of 150 articles, have been included in this review. Lessons from these studies suggest that neural plasticity within the ipsilateral primary motor cortex, the contralateral sensorimotor cortex, and the premotor cortices are more sensitive to compensation strategies reflecting upper and lower limbs' motor recovery despite the high heterogeneity in robotic devices, clinical status, and neuroimaging procedures. Unfortunately, the paucity of RCT studies prevents us from understanding the neurobiological differences induced by robotic devices with respect to traditional rehabilitation approaches. Despite this technology dating to the early 1990s, there is a need to translate more functional neuroimaging markers in clinical settings since they provide a unique opportunity to examine, in-depth, the brain plasticity changes induced by robotic rehabilitation.

Lowered Delta Activity in Post-COVID-19 Patients with Fatigue and Cognitive Impairment

In post-COVID-19 syndrome (PCS), neurocognitive symptoms and fatigue are often associated with alterations in electroencephalographic (EEG) activity. The present study investigates the brain source activity at rest in PCS patients (PCS-pts) perceiving cognitive deficits and fatigue. A total of 18 PCS-pts and 18 healthy controls (HCs) were enrolled. A Montreal Cognitive Assessment (MoCA), Perceived Cognitive Difficulties Scale (PDCS) and Fatigue Severity Scale (FSS) were administered for assessing the symptoms' severity. Brain activity at rest, both with open (OE) and closed eyes (CE), was recorded by high-density EEG (Hd-EEG) and localized by source estimation. Compared to HCs, PCS-pts exhibited worse performance in executive functions, language and memory, and reported higher levels of fatigue. At resting OE state, PCS-pts showed lower delta source activity over brain regions known to be associated with executive processes, and these changes were negatively associated with PDCS scores. Consistent with recent literature data, our findings could indicate a dysfunction in the neuronal networks involved in executive functions in PCS-pts complaining of fatigue and cognitive impairment.

Information and communication technologies-based interventions for children with autism spectrum conditions: a systematic review of randomized control trials from a positive technology perspective

Information and communication technologies (ICTs) have become more widely used in the past years to help people with autism spectrum conditions (ASC). Serious games embedded into computers or tablets, as well as social robots, are the most employed ICT-related tools that are appealing to and appropriate for autistic children. The goal of ICT applications is to enhance behavioral abnormalities associated with ASC while also creating an interactive link between one person and one computer. Comparatively, to human-based therapy, ICT tools aid to inspire autistic children by providing predictability and regularity of tasks. Regaining social skills is the primary behavioral goal for which ICT tools have been designed and implemented. In the past several years, many studies have been created to show how effective it is at improving targeted behaviors. However, only a small number of researchers have used an RCT approach to evaluate its effectiveness. In this systematic review, we only included RCT studies where ICT technologies were used to help children with ASC in improving their social skills. Only 14 RCT studies satisfied the criteria and 12 described significant improvements, showing how the use of technology in educational contexts produced better improvement in developing several social skill facets with respect to the traditional face-to-face approach. Some studies used interventions and outcome measures focused on the core ASC symptoms, but many others addressed neurocognitive functions directly, like social cognition or emotional regulation, while other more general functions such as language or adaptive behaviors. We propose a classification based on processes and outcome measures to foster future research in this specific area of research. The behavioral intervention mediated by technological tools such as computer-based, tablet, and social robotics, undoubtedly provides a comfortable environment that promotes constant learning for people with ASC. Evidence provided in this review highlights the translational potential of this field of study in primary care practice and educational settings.

Talking about Sexuality in Stroke Individuals: The New Era of Sexual Rehabilitation

One of the largest causes of mortality and disability worldwide is stroke. In the last twenty years significant objectives have been achieved in the early and chronic treatment of motor and cognitive dysfunctions, increasing the quality of life in patients and their caregivers. However, there is an unresolved clinical issue that remains: sexual dysfunctions. Multiple etiologies, including organic (such as lesion localization, premorbid medical problems, and drugs) and psychosocial (such as fear of recurrences, loss of self-esteem, role shifts, anxiety, and depression), are associated with sexual deficits. In this perspective review, we reported the last piece of evidence about this crucial topic which drastically affects the quality of life of these patients. Indeed, although patients may often not disclose their sexual concerns, literature demonstrates that they seek help concerning this issue. On the other side, clinicians working in the rehabilitation field are not always comfortable or prepared to deal with sexuality and sexual function in neurological patients. A new phase of the training course should be launched including different physicians, nurses, rehabilitation specialists, and social workers, to learn how to deal with topics related to sexuality. As a result, professional sexual counselors should now become a structured part of stroke settings and rehabilitation with new effective tools (i.e., PLISSIT model; TDF program) for improving quality of life.

A Rare Case of Severe Diarrhea: Gastrocolic Fistula Caused by Migration of Percutaneous Endoscopic Gastrostomy Tube

Gastrocolic fistula is a rare complication of the percutaneous endoscopic gastrostomy (PEG) placement procedure. This complication occurs due to penetration of interposed colon when a PEG tube is placed into the stomach. It can go unrecognized, becoming evident only when a tube replacement is performed or tube migration occurs. We report a case of severe, intractable diarrhea occurring about one month after the PEG procedure in a patient with severe traumatic brain injury. We present our case and discuss its significance with the aim of raising clinicians' awareness of this rare condition.

Modeling outcome trajectories in patients with acquired brain injury using a non-linear dynamic evolution approach

This study describes a dynamic non-linear mathematical approach for modeling the course of disease in acquired brain injury (ABI) patients. Data from a multicentric study were used to evaluate the reliability of the Michaelis-Menten (MM) model applied to well-known clinical variables that assess the outcome of ABI patients. The sample consisted of 156 ABI patients admitted to eight neurorehabilitation subacute units and evaluated at baseline (T0), 4 months after the event (T1) and at discharge (T2). The MM model was used to characterize the trend of the first Principal Component Analysis (PCA) dimension (represented by the variables: feeding modality, RLAS, ERBI-A, Tracheostomy, CRS-r and ERBI-B) in order to predict the most plausible outcome, in terms of positive or negative Glasgow outcome score (GOS) at discharge. Exploring the evolution of the PCA dimension 1 over time, after day 86 the MM model better differentiated between the time course for individuals with a positive and negative GOS (accuracy: 85%; sensitivity: 90.6%; specificity: 62.5%). The non-linear dynamic mathematical model can be used to provide more comprehensive trajectories of the clinical evolution of ABI patients during the rehabilitation period. Our model can be used to address patients for interventions designed for a specific outcome trajectory.

Corrigendum to “The promise of the metaverse in mental health: The new era of MEDverse”[Heliyon Volume 8, Issue 11, November 2022, Article e11762]

[This corrects the article DOI: 10.1016/j.heliyon.2022.e11762.].

TeleRehabilitation of Social-Pragmatic Skills in Children with Autism Spectrum Disorder: A Principal Component Analysis

In many therapeutic settings, remote health services are becoming increasingly a viable strategy for behavior management interventions in children with autism spectrum disorder (ASD). However, there is a paucity of tools for recovering social-pragmatic skills. In this study, we sought to demonstrate the effectiveness of a new online behavioral training, comparing the performance of an ASD group carrying out an online treatment (n°8) with respect to a control group of demographically-/clinically matched ASD children (n°8) engaged in a traditional in-presence intervention (face-to-face). After a 4-month behavioral treatment, the pragmatic skills language (APL test) abilities detected in the experimental group were almost similar to the control group. However, principal component analysis (PCA) demonstrated that the overall improvement in socio-pragmatic skills was higher for ASD children who underwent in-presence training. In fact, dimensions defined by merging APL subscale scores are clearly separated in ASD children who underwent in-presence training with respect to those performing the online approach. Our findings support the effectiveness of remote healthcare systems in managing the social skills of children with ASD, but more approaches and resources are required to enhance remote services.

The relationship between maternal-fetus attachment and perceived parental bonds in pregnant women: Considering a possible mediating role of psychological distress

Maternal-Fetal Attachment (MFA) delineates the emotional, cognitive, and behavioral aspects that mothers develop toward the unborn baby during pregnancy. The literature indicates that optimal attachment in pregnancy represents a protective factor for the mother-child attachment bond after birth and child development outcomes. To date, there are few studies that have investigated associated factors of MFA. This study sets out to explore the association between perceived parental bonds and maternal-fetal bonding in pregnant women, accounting for factors such as psychological distress, socio-demographic and obstetric characteristics.

Methods

In this cross-sectional study, 1,177 pregnant women answered the Parental Bonding Instrument, the Maternal-Fetal Attachment Scale, State-Trait Anxiety Inventory (STAI-Y), and Beck-Depression Inventory (BDI-II).

Results

We found out that perceived maternal and paternal care had significant direct effects on maternal-infant bonding during the pregnancy period when controlling for some confounders, including gestational age and mother age among others. Such maternal and paternal perceived care effects were not mediated by levels of psychological distress, which in turn resulted to be a "borderline" significant predictor of prenatal attachment. Interestingly, the gestational age and the mother age emerged to have a significant and synergic nonlinear effect, suggesting the influence on the MFAS of the gestational age depends on the values of the mother age, and likewise, the effect of mother age on MFAS depends on the gestational week.

Conclusion

This study expands our knowledge of the intergenerational transmission of attachment pointing out the effects of a woman's perceived bond in relation to her parental figures during the development of the prenatal attachment process. Findings also suggests that parenting support interventions may have benefits that are realized across generations.

Heart Rate Complexity and Autonomic Modulation Are Associated with Psychological Response Inhibition in Healthy Subjects

BACKGROUND

the ability to suppress/regulate impulsive reactions has been identified as common factor underlying the performance in all executive function tasks. We analyzed the HRV signals (power of high (HF) and low (LF) frequency, Sample Entropy (SampEn), and Complexity Index (CI)) during the execution of cognitive tests to assess flexibility, inhibition abilities, and rule learning.

METHODS

we enrolled thirty-six healthy subjects, recording five minutes of resting state and two tasks of increasing complexity based on 220 visual stimuli with 12 × 12 cm red and white squares on a black background.

RESULTS

at baseline, CI was negatively correlated with age, and LF was negatively correlated with SampEn. In Task 1, the CI and LF/HF were negatively correlated with errors. In Task 2, the reaction time positively correlated with the CI and the LF/HF ratio errors. Using a binary logistic regression model, age, CI, and LF/HF ratio classified performance groups with a sensitivity and specificity of 73 and 71%, respectively.

CONCLUSIONS

this study performed an important initial exploration in defining the complex relationship between CI, sympathovagal balance, and age in regulating impulsive reactions during cognitive tests. Our approach could be applied in assessing cognitive decline, providing additional information on the brain-heart interaction.

Efficacy of Visual Feedback Training for Motor Recovery in Post-Operative Subjects with Knee Replacement: A Randomized Controlled Trial

To evaluate the effects of visual feedback training on motor recovery in postoperative patients with a total knee replacement (TKR). The performance of 40 first-ever TKR patients (27 females; mean age: 70.5 (67.2−74.0) years) was evaluated in a single center, single-blind, randomized controlled study. The patients were randomly and equally distributed into two demographically/clinically matched groups undergoing experimental or traditional treatments. All patients have been treated in a 1 h session, 2/day for 5 days a week, for six consecutive weeks. The first group (“control”) underwent conventional physical therapy, whereas the experimental group received advanced knee training with visual feedback using the TecnoBody® device (Walker View 3.0 SCX, Dalmine (BG), Italy). The clinical scales and kinematic parameters coming from the gait analysis were evaluated to demonstrate the dynamic balance function in a standing position before and after each treatment. After the treatment, both experimental and control groups improved significantly and similarly, as measured by the clinical scales (Numeric Rating Scale for Pain and Barthel index). A significant boosting of the motor performance was detected in the experimental group with respect to the control group in the terms of symmetry index 84 (80.8−85.4) vs. 87.15 (84−92.8) p = 0.001 *; single stance support 34.9 (34.1−36.5) vs. 37.8 (36.6−38.9); p < 0.001; and obliquity parameters 58.65 (51.3−70.3) vs. 73 (62.3−82.1); p < 0.001. Applying visual feedback training in addition to traditional rehabilitation strategies improves the knee function and motor control in postoperative TKR patients.

The promise of the metaverse in mental health: the new era of MEDverse

Since Mark Zuckerberg's announcement about the development of new three-dimensional virtual worlds for social communication, a great debate has been raised about the promise of such a technology. The metaverse, a term formed by combining meta and universe, could open a new era in mental health, mainly in psychological disorders, where the creation of a full-body illusion via digital avatar could promote healthcare and personal well-being. Patients affected by body dysmorphism symptoms (i.e., eating disorders), social deficits (i.e. autism) could greatly benefit from this kind of technology. However, it is not clear which advantage the metaverse would have in treating psychological disorders with respect to the well-known and effective virtual reality (VR) exposure therapy. Indeed, in the last twenty years, a plethora of studies have demonstrated the effectiveness of VR technology in reducing symptoms of pain, anxiety, stress, as well as, in improving cognitive and social skills. We hypothesize that the metaverse will offer more opportunities, such as a more complex, virtual realm where sensory inputs, and recurrent feedback, mediated by a "federation" of multiple technologies - e.g., artificial intelligence, tangible interfaces, Internet of Things and blockchain, can be reinterpreted for facilitating a new kind of communication overcoming self-body representation. However, nowadays a clear starting point does not exist. For this reason, it is worth defining a theoretical framework for applying this new kind of technology in a social neuroscience context for developing accurate solutions to mental health in the future.

Sex and Sexuality in Autism Spectrum Disorders: A Scoping Review on a Neglected but Fundamental Issue

ASD consists of a set of permanent neurodevelopmental conditions, which are studded with social and communication differences, limited interests, and repetitive behaviors. Individuals with ASD have difficulty reading eye gestures and expressions, and may also have stereotyped or repetitive language, excessive adherence to routines, fixed interests, and rigid thinking. However, sexuality in adolescents and young adults with ASD is still a poorly studied and neglected issue. This review aims to evaluate sexual function and behavior in individuals with ASD to foster a greater understanding of this important, although often overlooked, issue. This review was conducted by searching peer-reviewed articles published between 01 June 2000 and 31 May 2022 using the following databases: PubMed, Embase, Cochrane Database, and Web of Science. A comprehensive search was conducted using the terms: "Autism" OR "ASD" AND "Sexuality" OR "Romantic relation" OR "sexual behavior" AND/OR "sexual awareness". After an accurate revision of 214 full manuscripts, 11 articles satisfied the inclusion/exclusion criteria. This review found that, although individuals with ASD may have sexual functioning, their sexuality is characterized by higher prevalence rates of gender dysphoria and inappropriate sexual behavior. Furthermore, sexual awareness is reduced in this patient population, and the prevalence of other variants of sexual orientation (i.e., homosexuality, asexuality, bisexuality, etc.) is higher in adolescents with ASD than in non-autistic peers. Sexual health and education should be included in the care path of patients with ASD in order to improve their quality of life and avoid/reduce inappropriate and risky behaviors.

The Arrival of the Metaverse in Neurorehabilitation: Fact, Fake or Vision?

The metaverse is a new technology thought to provide a deeper, persistent, immersive 3D experience combining multiple different virtual approaches in a full continuum of physical–digital interaction spaces. Different from virtual reality (VR) and augmented reality (AR), the metaverse has a service-oriented solid model with an emphasis on social and content dimensions. It has widely been demonstrated that motor or cognitive deficits can be more effectively treated using VR/AR tools, but there are several issues that limit the real potential of immersive technologies applied to neurological patients. In this scoping review, we propose future research directions for applying technologies extracted from the metaverse in clinical neurorehabilitation. The multisensorial properties of the metaverse will boost the embodied cognition experience, thus influencing the internal body representations as well as learning strategies. Moreover, the immersive social environment shared with other patients will contribute to recovering social and psychoemotional abilities. In addition to the many potential pros, we will also discuss the cons, providing readers with the available information to better understand the complexity and limitations of the metaverse, which could be considered the future of neurorehabilitation.

Predicting Outcome in Patients with Brain Injury: Differences between Machine Learning versus Conventional Statistics

Defining reliable tools for early prediction of outcome is the main target for physicians to guide care decisions in patients with brain injury. The application of machine learning (ML) is rapidly increasing in this field of study, but with a poor translation to clinical practice. This is basically dependent on the uncertainty about the advantages of this novel technique with respect to traditional approaches. In this review we address the main differences between ML techniques and traditional statistics (such as logistic regression, LR) applied for predicting outcome in patients with stroke and traumatic brain injury (TBI). Thirteen papers directly addressing the different performance among ML and LR methods were included in this review. Basically, ML algorithms do not outperform traditional regression approaches for outcome prediction in brain injury. Better performance of specific ML algorithms (such as Artificial neural networks) was mainly described in the stroke domain, but the high heterogeneity in features extracted from low-dimensional clinical data reduces the enthusiasm for applying this powerful method in clinical practice. To better capture and predict the dynamic changes in patients with brain injury during intensive care courses ML algorithms should be extended to high-dimensional data extracted from neuroimaging (structural and fMRI), EEG and genetics.

Social Humanoid Robots for Children with Autism Spectrum Disorders: A Review of Modalities, Indications, and Pitfalls

Robot-assisted therapy (RAT) is a promising area of translational neuroscience for children with autism spectrum disorders (ASDs). It has been widely demonstrated that this kind of advanced technological tool provides a reliable and efficient intervention for promoting social skills and communication in children with ASD. This type of treatment consists of a human-assisted social robot acting as an intervention mediator to increase competence and skills in children with ASD. Several social robots have been validated in the literature; however, an explicit technical comparison among devices has never been performed. For this reason, in this article, we provide an overview of the main commercial humanoid robots employed for ASD children with an emphasis on indications for use, pitfalls to be avoided, and recent advances. We conclude that, in the near future, a new generation of devices with high levels of mobility, availability, safety, and acceptability should be designed for improving the complex triadic interaction among teachers, children, and robots.

Pain and agitation treatment in severe dementia patients: The need for Italian Mobilization-Observation-Behavior-Intensity-Dementia (I-MOBID2) pain scale translation, adaptation and validation with psychometric testing

The 97% of dementia patients develops fluctuant neuropsychiatric symptoms often related to under-diagnosed and unrelieved pain. Up to 80% severe demented nursing home residents experiences chronic pain due to age-related comorbidities. Patients lacking self-report skills risk not to be appropriately treated for pain. Mobilization-Observation-Behavior-Intensity-Dementia (MOBID2) is the sole pain scale to consider the frequent co-occurrence of musculoskeletal and visceral pain and to unravel concealed pain through active guided movements. Accordingly, the Italian real-world setting can benefit from its translation and validation. This clinical study provides a translated, adapted and validated version of the MOBID2, the Italian I-MOBID2. The translation, adaptation and validation of the scale for non-verbal, severe demented patients was conducted according to current guidelines in a cohort of 11 patients over 65 with mini-mental state examination ≤ 12. The I-MOBID2 proves: good face and scale content validity index (0.89); reliable internal consistency (Cronbach's α = 0.751); good to excellent inter-rater (Intraclass correlation coefficient, and test-retest (ICC = 0.902) reliability. The construct validity is high (Rho = 0.748 p < 0.05 for 11 patients, Spearman rank order correlation of the overall pain intensity score with the maximum item score of I-MOBID2 Part 1; rho=0.895 p < 0.01 for 11 patients, for the overall pain intensity score with the maximum item score of I-MOBID2 Part 2) and a good rate of inter-rater and test-retest agreement was demonstrated by Cohen's K = 0.744. The average execution time is of 5.8 min, thus making I-MOBID2 a useful tool suitable also for future development in community setting with administration by caregivers.

Identification of Determinants of Biofeedback Treatment’s Efficacy in Treating Migraine and Oxidative Stress by ARIANNA (ARtificial Intelligent Assistant for Neural Network Analysis)

Migraines are a public health problem that impose severe socioeconomic burdens and causes related disabilities. Among the non-pharmacological therapeutic approaches, behavioral treatments such as biofeedback have proven effective for both adults and children. Oxidative stress is undoubtedly involved in the pathophysiology of migraines. Evidence shows a complex relationship between nitric oxide (NO) and superoxide anions, and their modification could lead to an effective treatment. Conventional analyses may fail in highlighting the complex, nonlinear relationship among factors and outcomes. The aim of the present study was to verify if an artificial neural network (ANN) named ARIANNA could verify if the serum levels of the decomposition products of NO—nitrite and nitrate (NOx)—the superoxide dismutase (SOD) serum levels, and the Migraine Disability Assessment Scores (MIDAS) could constitute prognostic variables predicting biofeedback’s efficacy in migraine treatment. Twenty women affected by chronic migraine were enrolled and underwent an EMG-biofeedback treatment. The results show an accuracy for the ANN of 75% in predicting the post-treatment MIDAS score, highlighting a statistically significant correlation (R = −0.675, p = 0.011) between NOx (nitrite and nitrate) and MIDAS only when the peroxide levels in the serum were within a specific range. In conclusion, the ANN was proven to be an innovative methodology for interpreting the complex biological phenomena and biofeedback treatment in migraines.

Characterizing Fractal Genetic Variation in the Human Genome from the Hapmap Project

Over the last decades, the exuberant development of next-generation sequencing has revolutionized gene discovery. These technologies have boosted the mapping of single nucleotide polymorphisms (SNPs) across the human genome, providing a complex universe of heterogeneity characterizing individuals worldwide. Fractal dimension (FD) measures the degree of geometric irregularity, quantifying how "complex" a self-similar natural phenomenon is. We compared two FD algorithms, box-counting dimension (BCD) and Higuchi's fractal dimension (HFD), to characterize genome-wide patterns of SNPs extracted from the HapMap data set, which includes data from 1184 healthy subjects of eleven populations. In addition, we have used cluster and classification analysis to relate the genetic distances within chromosomes based on FD similarities to the geographical distances among the 11 global populations. We found that HFD outperformed BCD at both grand average clusterization analysis by the cophenetic correlation coefficient, in which the closest value to 1 represents the most accurate clustering solution (0.981 for the HFD and 0.956 for the BCD) and classification (79.0% accuracy, 61.7% sensitivity, and 96.4% specificity for the HFD with respect to 69.1% accuracy, 43.2% sensitivity, and 94.9% specificity for the BCD) of the 11 populations present in the HapMap data set. These results support the evidence that HFD is a reliable measure helpful in representing individual variations within all chromosomes and categorizing individuals and global populations.

Gender Influences Virtual Reality-Based Recovery of Cognitive Functions in Patients with Traumatic Brain Injury: A Secondary Analysis of a Randomized Clinical Trial

The rehabilitation of cognitive deficits in individuals with traumatic brain injury is essential for promoting patients’ recovery and autonomy. Virtual reality (VR) training is a powerful tool for reaching this target, although the effectiveness of this intervention could be interfered with by several factors. In this study, we evaluated if demographical and clinical variables could be related to the recovery of cognitive function in TBI patients after a well-validated VR training. One hundred patients with TBI were enrolled in this study and equally randomized into the Traditional Cognitive Rehabilitation Group (TCRG: n = 50) or Virtual Reality Training Group (VRTG: n = 50). The VRTG underwent a VRT with BTs-N, whereas the TCRG received standard cognitive treatment. All the patients were evaluated by a complete neuropsychological battery before (T0) and after the end of the training (T1). We found that the VR-related improvement in mood, as well as cognitive flexibility, and selective attention were influenced by gender. Indeed, females who underwent VR training were those showing better cognitive recovery. This study highlights the importance of evaluating gender effects in planning cognitive rehabilitation programs. The inclusion of different repetitions and modalities of VR training should be considered for TBI male patients.

Psychological Interventions for Children with Autism during the COVID-19 Pandemic through a Remote Behavioral Skills Training Program

COVID-19 has impacted negatively on the mental health of children with autism spectrum disorder (ASD), as well as on their parents. Remote health services are a sustainable approach to behavior management interventions and to giving caregivers emotional support in several clinical domains. During the COVID-19 pandemic, we investigated the feasibility of a web-based behavioral skills training (BST) program for 16 parents and their children with ASD at home. The BST parent training package was tailored to each different specific behavioral disorder that characterizes children with ASD. After training, we found a significant reduction in the frequency of all the targeted behavioral disorders, as well as an improvement in psychological distress and the perception of the severity of ASD-related symptoms in parents. Our data confirm the efficacy of remote health care systems in the management of behavioral disorders of children with ASD, as well as of their parents during the COVID-19 pandemic.

Stroke Telerehabilitation in Calabria: A Health Technology Assessment

Introduction: Telerehabilitation (TR) is defined as a model of home service for motor and cognitive rehabilitation, ensuring continuity of care over time. TR can replace the traditional face-to-face approach as an alternative method of delivering conventional rehabilitation and applies to situations where the patient is unable to reach rehabilitation facilities or for low-income countries where outcomes are particularly poor. For this reason, in this study, we sought to demonstrate the feasibility and utility of a well-known TR intervention on post-stroke patients living in one of the poorest indebted regions of Italy, where the delivery of rehabilitation services is inconsistent and not uniform.

Materials and Methods: Nineteen patients (13 male/6 female; mean age: 61.1 ± 8.3 years) with a diagnosis of first-ever ischemic (n = 14) or hemorrhagic stroke (n = 5), who had been admitted to the intensive rehabilitation unit (IRU) of the Institute S. Anna (Crotone, Italy), were consecutively enrolled to participate in this study. After the discharge, they continued the motor treatment remotely by means of a home-rehabilitation system. The entire TR intervention was performed (online and offline) using the Virtual Reality Rehabilitation System (VRRS) (Khymeia, Italy). All patients received intensive TR five times a week for 12 consecutive weeks (60 sessions, each session lasting about 1h).

Results: We found a significant motor recovery after TR protocol as measured by the Barthel Index (BI); Fugl-Meyer motor score (FM) and Motricity Index (MI) of the hemiplegic upper limbs.

Conclusions: This was the first demonstration that a well-defined virtual reality TR tool promotes motor and functional recovery in post-stroke patients living in a low-income Italian region, such as Calabria, characterized by a paucity of specialist rehabilitation services.

Iliacus Muscle Hematoma an Uncommon Complication in a Rehabilitation Unit: A Case Report Study

Iliacus muscle hematoma is a very rare condition in rehabilitation wards. A 35-year-old pregnant woman at seven months with cerebellar hematoma with signs of compression underwent a cesarean procedure together with neurosurgical decompression of the posterior cranial fossa procedure. After a period in an intensive unit without any complications, she was admitted to our neurorehabilitation ward and treated with antihypertensive therapy, heparin, and anti-seizure drugs. During a rehabilitation session, after a bed–wheelchair transfer, she was feeling very unwell suffering from severe right leg pain radiating to the mid-face leg. Despite unremarkable physical evidence (skin appearance, temperature, and peripheral arterial pulse in both legs), imaging data (ultrasound, CT, and MRI) confirmed the presence of a right iliac muscle hematoma (IMH). Enoxaparin was immediately stopped, and bed rest was prescribed in an antalgic position with tramadole acetaminophen for pain control. After a few days, the patient felt well and was discharged without any additional symptoms. Our study demonstrates that, when a sudden severe leg pain develops, IMH should be considered in the differential diagnosis. This finding suggests further research and tailored protocols for rehabilitation in patients at high risk for iliacus muscle hematoma.

Diagnostic Developments in Differentiating Unresponsive Wakefulness Syndrome and the Minimally Conscious State

When treating patients with a disorder of consciousness (DOC), it is essential to obtain an accurate diagnosis as soon as possible to generate individualized treatment programs. However, accurately diagnosing patients with DOCs is challenging and prone to errors when differentiating patients in a Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) from those in a Minimally Conscious State (MCS). Upwards of ~40% of patients with a DOC can be misdiagnosed when specifically designed behavioral scales are not employed or improperly administered. To improve diagnostic accuracy for these patients, several important neuroimaging and electrophysiological technologies have been proposed. These include Positron Emission Tomography (PET), functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), and Transcranial Magnetic Stimulation (TMS). Here, we review the different ways in which these techniques can improve diagnostic differentiation between VS/UWS and MCS patients. We do so by referring to studies that were conducted within the last 10 years, which were extracted from the PubMed database. In total, 55 studies met our criteria (clinical diagnoses of VS/UWS from MCS as made by PET, fMRI, EEG and TMS- EEG tools) and were included in this review. By summarizing the promising results achieved in understanding and diagnosing these conditions, we aim to emphasize the need for more such tools to be incorporated in standard clinical practice, as well as the importance of data sharing to incentivize the community to meet these goals.

Rehabilitation outcomes in Huntington disease patients with low body mass index

OBJECTIVES

A catabolic state and a progressive body weight loss are a well-documented hallmark of Huntington Disease (HD). No study is still available on the effectiveness of intensive in-hospital rehabilitation in HD patients with low body mass index (BMI).

METHODS

Twenty HD patients with low BMI value were enrolled in this study. Disease severity was assessed before and after rehabilitation by the Barthel Index, the Total Functional Capacity Scale, and the Physical Performance Test.

RESULTS

BMI-scores correlated with clinical measures before and after rehabilitation. All patients showed an improvement in outcome measures (p<0.001), and an increase in BMI values (p<0.001) after rehabilitation. Effectiveness of rehabilitation correlated with the values of BMI assessed before reheducational programs (p=0.024) and with BMI values observed in each patient in the three months before admission to hospital (p=0.002).

CONCLUSIONS

Findings of the current study show that the effectiveness of the rehabilitation is positively correlated with the BMI values and confirm the efficacy of in-hospital intensive rehabilitation as a valid strategy finalized to improve neuromotor performances and global functional recovery even in HD patients with low BMI and at risk of malnutrition.

Aromatherapy in Stroke Patients: Is it Time to Begin?

Stroke is the second largest cause of death worldwide, causing disease with long-term consequences and considerable healthcare costs. The application of new nursing interventions aimed at reducing distressing behaviors and at increasing patient comfort is an important part of the care and, until now, there are no defined guidelines. Aromatherapy has been demonstrated to be efficient in several other neurological disorders for the treatment of somatic and emotional diseases and to promote patient health. In the management of stroke patients, aromatherapy is still in its infancy. The first evidence coming from animal models demonstrated a consistent and reliable neuroprotective effect in reducing cerebral ischemia–reperfusion injury. In the last few years, some preliminary data being to be collected in humans revealed significant influence in reducing patients’ pain and emotional distress. In this perspective study, we sought to summarize, for the first time, the main findings emerging from this new field of study, discussing the future opportunities to be translated into primary care practice.

Anti-SARS-CoV-2 S-RBD IgG Antibody Responses after COVID-19 mRNA Vaccine in the Chronic Disorder of Consciousness: A Pilot Study

OBJECTIVE

In the last year, a large amount of research has investigated the anti-spike protein receptor-binding domain (S-RBD) antibody responses in patients at high risk of developing severe acute respiratory syndrome because of COVID-19 infection. However, no data are available on the chronic disorder of consciousness (DOC).

METHODS

Here, we evaluated anti-S-RBD IgG levels after vaccination in chronic DOC patients compared with demographically matched healthy controls (HC) by indirect chemiluminescence immunoassay. All individuals completed a two-dose-cycle vaccination with Pfizer mRNA vaccine (BNT162b2), and antibody responses were evaluated at 30 and 180 days after the administration of the second dose of vaccination.

RESULTS

We compared 32 DOC patients with 34 demographically matched healthy controls. Both DOC and HC groups showed a similar antibody response at 30 days, whereas at follow-up (180 days) DOC patients were characterized by lower S-RBD IgG levels with respect to controls. Additional multiple regression analyses including demographical and clinical comorbidities as predictors revealed that age was the only factor associated with the decrease in S-RBD IgG levels at follow-up (180 days). Elderly individuals of both groups were characterized by a reduction in the antibody responses with respect to younger individuals.

CONCLUSIONS

Our results show an efficacy seroconversion in DOC patients in the first period after vaccination, which significantly declines over time with respect to healthy controls.

Autistic Traits and Empathy in Children With Attention Deficit Hyperactivity Disorder, Autism Spectrum Disorder and Co-occurring Attention Deficit Hyperactivity Disorder/Autism Spectrum Disorder

Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorders (ASD) are two of the most represented neurodevelopmental conditions in childhood. The diagnostic shift introduced by the DSM-5, allowing a combined diagnosis of ADHD and ASD, poses different clinical challenges related to diagnostic overshadowing, accuracy of clinical judgment and potential delay in an ASD diagnosis in children presenting with ADHD. Here we tried to disentangle the clinical phenotype and specificity of the two co-occurring conditions in relation to autism traits and empathy, by comparing children with ASD with and without comorbid ADHD with children presenting ADHD only and children with typical development. The child versions of the Autism Quotient (C-AQ) and Empathy Quotient (C-EQ) were administered to a total sample of 198 male children between 6 and 14 years old with age appropriate language skills and normal intelligence. Univariate analysis demonstrated no significant differences in the C-AQ total and subscale scores as well as the C-EQ between children with ASD and children with ASD + ADHD, while children with ADHD alone presented an intermediate phenotype between ASD and TD. Furthermore, a receiver operating characteristic (ROC) analysis was applied to discriminate among the different phenotypes. We found that the C-AQ and C-EQ were accurate at distinguishing with satisfactory reliability between: (a) ASD vs. non- ASD (N-ASD) groups comprising both ADHD and TD children (Area Under the Curve AUC 88% for C-AQ and 81% for C-EQ); (b) ASD and TD (AUC 92% for C-AQ and 95% for C-EQ); (c) ASD and ADHD (AUC 80% for C-AQ and 68% for C-EQ). Our data confirm the reliability of the C-AQ and C-EQ as behavioral markers to differentiate ASD (regardless of comorbid ADHD) from an ADHD condition and TD. Interestingly, in our sample an ADHD condition does not increase the severity of the clinical phenotype in terms of autism traits distribution and empathy, suggesting that the psychological measures detected by the two quantitative instruments are independent of ADHD traits. This evidence will contribute to the translational efforts in developing better tailored treatments and preventive strategies.

Effects of maternal psychological distress and perception of COVID-19 on prenatal attachment in a large sample of Italian pregnant women

BACKGROUND

Evidence concerning the impact of COVID-19-related stress exposure on prenatal attachment in pregnant women is unknown. In this study we sought to assess the effect of psychological distress and risk perception of COVID-19 on prenatal attachment in a Italian sample of pregnant women.

METHODS

1179 pregnant women completed an anonymous online survey and self-report questionnaires measuring socio-demographic and obstetric characteristics, psychological distress (STAI Form Y-1-2 and BDI-II), prenatal attachment (PAI) and risk perception of COVID-19. Data were collected from March 2020 to April 2020 referring to the national lockdown period.

RESULTS

After adjusting for the socio-demographic and obstetric factors in the multivariable analysis, we found out the state anxiety was shown to be a significant predictor (p < 0001) of prenatal attachment. Moreover, the COVID-19-risk perception positively moderate the relationship between trait anxiety and prenatal attachment (p=0008), indicating that when COVID-19-risk perception is high, the effects of trait anxiety on prenatal attachment is attenuated. The synergistic effect between STAI Form Y-1 and COVID-19-risk perception index on PAI is partially mediated by STAI Form Y-2 score.

CONCLUSIONS

Findings from this study showed that state anxiety related to COVID-19 outbreak in pregnant women may affect the prenatal attachment process of the expectant mother negatively. However, an adequate and functional perception of COVID-19 could enhance prenatal attachment. These results underline the importance of monitoring the prenatal attachment process and the mother's mental health during pandemics, to safeguard maternal and infant mental health.

The Route of Motor Recovery in Stroke Patients Driven by Exoskeleton-Robot-Assisted Therapy: A Path-Analysis

Background: Exoskeleton-robot-assisted therapy is known to positively affect the recovery of arm functions in stroke patients. However, there is a lack of evidence regarding which variables might favor a better outcome and how this can be modulated by other factors. Methods: In this within-subject study, we evaluated the efficacy of a robot-assisted rehabilitation system in the recovery of upper limb functions. We performed a path analysis using a structural equation modeling approach in a large sample of 102 stroke patients (age 63.6 ± 13.1 years; 61% men) in the post-acute phase. They underwent 7 weeks of bilateral arm training assisted by an exoskeleton robot combined with a conventional treatment (consisting of simple physical activity together with occupational therapy). The upper extremity section of the Fugl–Meyer (FM-UE) scale at admission was used as a predictor of outcome, whereas age, gender, side of the lesion, days from the event, pain scale, duration of treatment, and number of sessions as mediators. Results: FM-UE at admission was a direct predictor of outcome, as measured by the motricity index of the contralateral upper limb and trunk control test, without any other mediating factors. Age, gender, days from the event, side of lesion, and pain scales were independently associated with outcomes. Conclusions: To the best of our knowledge, this is the first study assessing the relationship between clinical variables and outcomes induced by robot-assisted rehabilitation with a path-analysis model. We define a new route for motor recovery of stroke patients driven by exoskeleton-robot-assisted therapy, highlighting the role of FM-UE at admission as a useful predictor of outcome, although other variables need to be considered in the time-course of disease.