•Recovery of walking function is one of the main goals of patients after stroke.•RAGT may be considered a valuable tool in improving gait abnormalities.•The earlier the gait training starts, the ...better the motor recovery.
Studies about electromechanical-assisted devices proved the validity and effectiveness of these tools in gait rehabilitation, especially if used in association with conventional physiotherapy in stroke patients.
The aim of this study was to compare the effects of different robotic devices in improving post-stroke gait abnormalities.
A computerized literature research of articles was conducted in the databases MEDLINE, PEDro, COCHRANE, besides a search for the same items in the Library System of the University of Parma (Italy). We selected 13 randomized controlled trials, and the results were divided into sub-acute stroke patients and chronic stroke patients. We selected studies including at least one of the following test: 10-Meter Walking Test, 6-Minute Walk Test, Timed-Up-and-Go, 5-Meter Walk Test, and Functional Ambulation Categories.
Stroke patients who received physiotherapy treatment in combination with robotic devices, such as Lokomat or Gait Trainer, were more likely to reach better results, compared to patients who receive conventional gait training alone. Moreover, electromechanical-assisted gait training in association with Functional Electrical Stimulations produced more benefits than the only robotic treatment (−0.80 −1.14; −0.46, p > .05).
The evaluation of the results confirm that the use of robotics can positively affect the outcome of a gait rehabilitation in patients with stroke. The effects of different devices seems to be similar on the most commonly outcome evaluated by this review.
Objective
The study aim was to investigate the prevalence of behavioral symptoms and burnout in healthcare workers in an intensive neurological rehabilitation unit in Messina, Italy, during the first ...COVID-19 lockdown in Italy.
Methods
Forty-seven healthcare workers (including neurologists, physiatrists, nurses and rehabilitation therapists) were enrolled in this cross-sectional study from February 2020 to June 2020. Participants were administered the following psychometric tests to investigate burnout and related symptoms: the Maslach Burnout Inventory, which measures emotional exhaustion, depersonalization and reduced personal accomplishment; the Zung Self-Rating Depression Scale (SDS); the Pre-Sleep Arousal Scale (PSAS); the Dyadic Adjustment Scale; and the Buss–Perry Aggression Questionnaire (BPAQ).
Results
We found several correlations between test scores and burnout subdimensions. Emotional exhaustion was correlated with SDS (r = 0.67), PSAS-Cognitive (r = 0.67) and PSAS-Somatic (r = 0.70) scores, and moderately correlated with all BPAQ dimensions (r = 0.42). Depersonalization was moderately correlated with SDS (r = 0.54), PSAS-Cognitive (r = 0.53) and PSAS-Somatic (r = 0.50) scores.
Conclusion
During the first COVID-19 lockdown in Italy, healthcare workers were more exposed to physical and mental exhaustion and burnout. Research evaluating organizational and system-level interventions to promote psychological well-being at work for healthcare workers are needed.
Alzheimer's Disease (AD) is a neurodegenaritive disorder characterized by a progressive dementia, for which actually no cure is known. An early detection of patients affected by AD can be obtained by ...analyzing their electroencephalography (EEG) signals, which show a reduction of the complexity, a perturbation of the synchrony, and a slowing down of the rhythms.
In this work, we apply a procedure that exploits feature extraction and classification techniques to EEG signals, whose aim is to distinguish patient affected by AD from the ones affected by Mild Cognitive Impairment (MCI) and healthy control (HC) samples. Specifically, we perform a time-frequency analysis by applying both the Fourier and Wavelet Transforms on 109 samples belonging to AD, MCI, and HC classes. The classification procedure is designed with the following steps: (i) preprocessing of EEG signals; (ii) feature extraction by means of the Discrete Fourier and Wavelet Transforms; and (iii) classification with tree-based supervised methods.
By applying our procedure, we are able to extract reliable human-interpretable classification models that allow to automatically assign the patients into their belonging class. In particular, by exploiting a Wavelet feature extraction we achieve 83%, 92%, and 79% of accuracy when dealing with HC vs AD, HC vs MCI, and MCI vs AD classification problems, respectively.
Finally, by comparing the classification performances with both feature extraction methods, we find out that Wavelets analysis outperforms Fourier. Hence, we suggest it in combination with supervised methods for automatic patients classification based on their EEG signals for aiding the medical diagnosis of dementia.
Electroencephalography (EEG) signal analysis is a fast, inexpensive, and accessible technique to detect the early stages of dementia, such as Mild Cognitive Impairment (MCI) and Alzheimer’s disease ...(AD). In the last years, EEG signal analysis has become an important topic of research to extract suitable biomarkers to determine the subject’s cognitive impairment. In this work, we propose a novel simple and efficient method able to extract features with a finite response filter (FIR) in the double time domain in order to discriminate among patients affected by AD, MCI, and healthy controls (HC). Notably, we compute the power intensity for each high- and low-frequency band, using their absolute differences to distinguish among the three classes of subjects by means of different supervised machine learning methods. We use EEG recordings from a cohort of 105 subjects (48 AD, 37 MCI, and 20 HC) referred for dementia to the IRCCS Centro Neurolesi “Bonino-Pulejo” of Messina, Italy. The findings show that this method reaches 97%, 95%, and 83% accuracy when considering binary classifications (HC vs. AD, HC vs. MCI, and MCI vs. AD) and an accuracy of 75% when dealing with the three classes (HC vs. AD vs. MCI). These results improve upon those obtained in previous studies and demonstrate the validity of our approach. Finally, the efficiency of the proposed method might allow its future development on embedded devices for low-cost real-time diagnosis.
•Stroke represents the leading cause of disability in the industrialized world.•Post-stroke impairment interferes with the QoL of the patient and caregiver.•Robot-assisted hand training allow to ...perform practical tasks with a VR setting.•Hand robotic plus VR-based training may amplify the functional outcome achievement.
Robot-assisted hand training adopting end-effector devices results in an additional reduction of motor impairment in comparison to usual care alone in different stages of stroke recovery. These devices often allow the patient to perform practical, attentive, and visual-spatial tasks in a semi-virtual reality (VR) setting. We aimed to investigate whether the hand end-effector robotic device AmadeoTM could improve cognitive performance, beyond the motor deficit, as compared to the same amount of occupational treatment focused on the hand. Forty-eight patients (aged 54.3 ± 10.5 years, 62.5% female) affected by either ischemic or hemorrhagic stroke in the chronic phase were enrolled in the study. The experimental group (EG) underwent AmadeoTM robotic training, while the control group (CG) performed occupational therapy involving the upper limb. Patients were assessed at the beginning and at the end of the rehabilitation protocol using a specific neuropsychological battery, as well as motor function tests. The EG showed greater improvements in different cognitive domains, including attentive abilities and executive functions, as well as in hand motor function, as compared to CG. Our study showed that task-oriented VR-based robotic rehabilitation enhanced not only motor function in the paretic arm but also global and specific cognitive abilities in post-stroke patients. We may argue that the hand robotic plus VR-based training may provide patients with an integration of cognitive and motor skill rehabilitation, thus amplifying the functional outcome achievement.
Objective
To compare selective serotonin reuptake inhibitors (SSRIs) and nootropic drugs in the reduction of anxiety and depressive symptoms in post-stroke patients.
Methods
This retrospective cohort ...study included patients diagnosed with post-stroke depression that were treated with either SSRIs or nootropic drugs (i.e. citicoline or choline alphoscerate). Depression and anxiety were assessed using the Hamilton Rating Scales. Statistical associations between the use of nootropic drugs and mood disorder improvements were determined by measuring assessment scores at 6-months.
Results
A total of 44 post-stroke patients with depression (aged 45–75 years) were enrolled in the study: 20 were treated with SSRIs and 24 received nootropic drugs. From baseline to follow-up, the SSRI group showed a large effect size with regard depression (success rate difference SRD 0.57; 95% confidence interval CI 0.21, 0.79) and anxiety (SRD 0.49; 95% CI 0.14, 0.74), whereas the nootropic group showed a small effect size for depression (SRD 0.16; 95% CI –0.17, 0.46) and a small effect size for anxiety (SRD 0.36; 95% CI –0.03, 0.62).
Conclusion
The administration of nootropic drugs could be a valid therapeutic strategy to manage post-stroke patients suffering from mild–moderate anxiety or anxious-depressive syndrome, but this requires further research.
Objective
Population screening can facilitate early diagnosis of dementia and improve disease management. This study examined the effects of a screening campaign for neurodegenerative disorders on ...the early diagnosis of dementia using 2-year follow-up data.
Methods
A 5-day screening campaign was conducted that comprised neurological, neuropsychological and other specialist examinations. Identification of alterations during the neurological examination was followed-up by further diagnostic examinations to confirm the neurological impairment.
Results
Neurological alterations were observed in 39% of the screened subjects, who were mostly diagnosed with mild cognitive impairment and referred to a dementia and cognitive disorders centre. Suspicion of neurological impairment was a risk factor for inclusion in a specific neurological ambulatory follow-up and a condition for exemption from payment for medical examinations.
Conclusions
Neurodegenerative screening initiatives should include subjects selected by general practitioners. It would be useful to create a network including primary care physicians and cognitive disorder centres. Telemedicine tools (e.g., teleconsulting) could also be used to facilitate early diagnosis.
Objective
Emergency psychological interventions are needed in patients with COVID-19. During the pandemic, psychological counseling services have been provided using online platforms to address ...adverse psychological impacts and symptoms in patients and the general population. We investigated the effects of telepsychotherapy on emotional well-being and psychological distress in patients affected by COVID-19.
Methods
Forty-five Sicilian patients who had contracted COVID-19 joined “Telecovid Sicilia” from March to June 2020. Participants completed self-assessment questionnaires and psychological testing to measure levels of anxiety, presence of depressive symptoms, and altered circadian rhythm with consequent sleep disorders and psychological distress. Individual telepsychotherapy services were provided for 1 hour, twice a week, for 16 sessions in total.
Results
We enrolled 45 patients (42.2% women). We found significant changes between baseline and the end of follow-up in all outcome measures, especially depression (χ2 (1) = 30.1; effect size ES = 0.82), anxiety (χ2 (1) = 37.4; ES = 0.91), and paranoid ideation (χ2 (1) = 5.6; ES = 0.35). The proportion of participants with sleep disorders decreased to 84.1% after intervention (χ2 (1) = 58.6; ES = 1.14).
Conclusion
A telepsychotherapeutic approach showed promising effects on psychological symptoms, with significantly reduced patient anxiety and depression.
Several studies reported olfactory dysfunction in patients with multiple sclerosis. The estimate of the incidence of olfactory deficits in multiple sclerosis is uncertain; this may arise from ...different testing methods that may be influenced by patients' response bias and clinical, demographic and cognitive features.
To evaluate objectively the olfactory function using Olfactory Event Related Potentials.
We tested the olfactory function of 30 patients with relapsing remitting multiple sclerosis (mean age of 36.03±6.96 years) and of 30 age, sex and smoking-habit matched healthy controls by using olfactory potentials. A selective and controlled stimulation of the olfactory system to elicit the olfactory event related potentials was achieved by a computer-controlled olfactometer linked directly with electroencephalograph. Relationships between olfactory potential results and patients' clinical characteristics, such as gender, disability status score, disease-modifying therapy, and disease duration, were evaluated.
Seven of 30 patients did not show olfactory event related potentials. Sixteen of remaining 23 patients had a mean value of amplitude significantly lower than control group (p<0.01). The presence/absence of olfactory event related potentials was associated with dichotomous expanded disability status scale (p = 0.0433), as well as inversely correlated with the disease duration (r = -0.3641, p = 0.0479).
Unbiased olfactory dysfunction of different severity found in multiple sclerosis patients suggests an organic impairment which could be related to neuroinflammatory and/or neurodegenerative processes of olfactory networks, supporting the recent findings on neurophysiopathology of disease.
Objective
We conducted a narrative review to investigate whether antidepressant therapy, including the use of selective serotonin reuptake inhibitors (SSRIs) or serotonin-norepinephrine reuptake ...inhibitors (SNRIs) or the use of supportive drugs (i.e., citicoline or choline alfoscerate) as a substitute for antidepressant therapy, reduces depression in patients with cerebrovascular diseases.
Methods
A systematic search of the PubMed and Web of Science databases was performed, including review articles and other studies to identify additional citations. Only 4 of 1566 publications met the inclusion/exclusion criteria and were selected.
Results
Studies showed that post-stroke depression (PSD) could be treated with antidepressant therapy, as well as supportive drugs such as citicoline or choline alfoscerate, which may have antidepressant effects.
Conclusions
The findings support the efficacy of citicoline as a treatment for depression. Studies aimed to discover the characteristics of these psychostimulants in relation to PSD treatment should be performed.
PDF
