Davide Ferrazzoli

Background/Objectives: Parkinson’s disease (PD) is a complex neurodegenerative disorder responsible for both motor and non-motor disturbances impairing motor behavior. This complexity necessitates integrated, multidisciplinary, and comprehensive models of care. A new and interesting complementary approach is represented by “Dance Well”, i.e., an artistic, multisensory dance intervention based on art and music. This pilot study aims to evaluate the efficacy, feasibility, and safety of a 4-week Dance Well (DW) program in PD patients in early–medium disease stages. Methods: Twenty-four PD patients (H&Y ≤ 3; MoCA score ≥ 13.8) were enrolled and randomly allocated into two groups, both with a twice-per-week frequency and lasting 4 weeks: one group underwent the DW program, while the other underwent conventional physiotherapy (CPT). Demographic, biometric, and clinical data were collected. To study the treatment effect, motor (Unified PD Rating Scale-III, Timed Up and Go Test, Berg Balance Scale, 6-Minute Walk Test, and Falls Efficacy Scale), cognitive (Corsi Supra Span Test, Trail Making Test A and B-A), and emotional–motivational (Beck Depression Inventory, State-Trait Anxiety Inventory, Apathy Evaluation Scale) outcome measures were assessed, before and after the rehabilitation program. To study treatment compliance and safety, the number of dropouts and any adverse events (such as injuries and falls) were recorded. Results: All outcome measures improved in both groups. The percentage of improvement in outcome measures assessing attention and motivation was greater in the DW group. No dropouts, falls, or injuries occurred. Conclusions: In the early–medium stages of PD, DW could be considered a feasible and safe complementary treatment, useful in improving motor, cognitive, and emotional–motivational symptoms.

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.

The assessment of cognitive deficits is pivotal for diagnosis and management in patients with parkinsonisms. Low levels of correspondence are observed between evaluations assessed with screening cognitive tests in comparison with those assessed with in-depth neuropsychological batteries. A new tool, we named CoMDA (Cognition in Movement Disorders Assessment), was composed by merging Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Frontal Assessment Battery (FAB). In total, 500 patients (400 with Parkinson’s disease, 41 with vascular parkinsonism, 31 with progressive supranuclear palsy, and 28 with multiple system atrophy) underwent CoMDA (level 1–L1) and in-depth neuropsychological battery (level 2–L2). Machine learning was developed to classify the CoMDA score and obtain an accurate prediction of the cognitive profile along three different classes: normal cognition (NC), mild cognitive impairment (MCI), and impaired cognition (IC). The classification accuracy of CoMDA, assessed by ROC analysis, was compared with MMSE, MoCA, and FAB. The area under the curve (AUC) of CoMDA was significantly higher than that of MMSE, MoCA and FAB (p < 0.0001,p = 0.028 andp = 0.0007, respectively). Among 15 different algorithmic methods, the Quadratic Discriminant Analysis algorithm (CoMDA-ML) showed higher overall-metrics performance levels in predictive performance. Considering L2 as a 3-level continuous feature, CoMDA-ML produces accurate and generalizable classifications: micro-average ROC curve, AUC = 0.81; and AUC = 0.85 for NC, 0.67 for MCI, and 0.83 for IC. CoMDA and COMDA-ML are reliable and time-sparing tools, accurate in classifying cognitive profile in parkinsonisms.This study has been registered on ClinicalTrials.gov (NCT04858893).

Background and purpose: Fatigue and cognitive difficulties are reported as the most frequently persistent symptoms in patients after mild SARS‐CoV‐2 infection. An extensive neurophysiological and neuropsychological assessment of such patients was performed focusing on motor cortex physiology and executive cognitive functions.Methods: Sixty‐seven patients complaining of fatigue and/or cognitive difficulties after resolution of mild SARS‐CoV‐2 infection were enrolled together with 22 healthy controls (HCs). Persistent clinical symptoms were investigated by means of a 16‐item questionnaire. Fatigue, exertion, cognitive difficulties, mood and ‘well‐being’ were evaluated through self‐administered tools. Utilizing transcranial magnetic stimulation of the primary motor cortex (M1) resting motor threshold, motor evoked potential amplitude, cortical silent period duration, short‐interval intracortical inhibition, intracortical facilitation, long‐interval intracortical inhibition and short‐latency afferent inhibition were evaluated. Global cognition and executive functions were assessed with screening tests. Attention was measured with computerized tasks.Results: Post COVID‐19 patients reported a mean of 4.9 persistent symptoms, high levels of fatigue, exertion, cognitive difficulties, low levels of well‐being and reduced mental well‐being. Compared to HCs, patients presented higher resting motor thresholds, lower motor evoked potential amplitudes and longer cortical silent periods, concurring with reduced M1 excitability. Long‐interval intracortical inhibition and short‐latency afferent inhibition were also impaired, indicating altered GABA_B‐ergic and cholinergic neurotransmission. Short‐interval intracortical inhibition and intracortical facilitation were not affected. Patients also showed poorer global cognition and executive functions compared to HCs and a clear impairment in sustained and executive attention.Conclusions: Patients with fatigue and cognitive difficulties following mild COVID‐19 present altered excitability and neurotransmission within M1 and deficits in executive functions and attention.