Living with Parkinson's disease in Portugal: Findings from PRISM study.

BACKGROUND: Parkinson's disease (PD) ranks second in global neurodegenerative disorders. The "Parkinson's Real-world Impact assesSMent (PRISM)" study addressed the disease burden and treatment of European PD patients. Yet, the burden on Portuguese PD patients remains unexplored. Here, we outline the demographics, clinical features, and impact of PD in the Portuguese PRISM cohort. METHODS: Descriptive analysis of the PRISM Portuguese cohort (80 patients) was performed, emphasizing socio-demographic data, anti-PD medication usage, PD impact on patients' lives and healthcare resources utilization. RESULTS: The predominant comorbidities in the Portuguese PD cohort (55 % male; mean age 66.2 years; mean disease duration 8.8 years) included depression (26.3 %) and anxiety (26.3 %). Levodopa was the initial prescribed anti-PD medication for 88 % of patients. Among Portuguese PDP, dopamine agonists (DA), monoamine oxidase-B (MAO-B) inhibitors, and catechol-O-methyltransferase (COMT) inhibitors were used by 50 %, 44.4 %, and 18.3 %, respectively. Portuguese PDP experienced impaired quality of life (PDQ-39 score: 31.3 ± 16.8), various non-motor symptoms, namely sadness/blues (65.4 %), urinary urgency (63.5 %), high/low sex interest (57.7 %), while 56 % reported at least one impulse control behavior. Additionally, 30.8 % retired early due to PD and 31.8 % reduced hours in daily activities. Mental health appointments were attended by 31 %, primarily in psychiatry (19 %) and psychology (6 %), and psychotherapy. CONCLUSION: This study uncovers the burden of PD among Portuguese patients, revealing current treatment methods, impact on daily life and healthcare resources employed in Portugal. It emphasizes the need for personalized clinical strategies at national and international levels to improve long-term health outcomes and quality of life of PD patients.

Monipar: movement data collection tool to monitor motor symptoms in Parkinson's disease using smartwatches and smartphones.

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder commonly characterized by motor impairments. The development of mobile health (m-health) technologies, such as wearable and smart devices, presents an opportunity for the implementation of clinical tools that can support tasks such as early diagnosis and objective quantification of symptoms. Objective: This study evaluates a framework to monitor motor symptoms of PD patients based on the performance of standardized exercises such as those performed during clinic evaluation. To implement this framework, an m-health tool named Monipar was developed that uses off-the-shelf smart devices. Methods: An experimental protocol was conducted with the participation of 21 early-stage PD patients and 7 healthy controls who used Monipar installed in off-the-shelf smartwatches and smartphones. Movement data collected using the built-in acceleration sensors were used to extract relevant digital indicators (features). These indicators were then compared with clinical evaluations performed using the MDS-UPDRS scale. Results: The results showed moderate to strong (significant) correlations between the clinical evaluations (MDS-UPDRS scale) and features extracted from the movement data used to assess resting tremor (i.e., the standard deviation of the time series: r = 0.772, p < 0.001) and data from the pronation and supination movements (i.e., power in the band of 1-4 Hz: r = -0.662, p < 0.001). Conclusion: These results suggest that the proposed framework could be used as a complementary tool for the evaluation of motor symptoms in early-stage PD patients, providing a feasible and cost-effective solution for remote and ambulatory monitoring of specific motor symptoms such as resting tremor or bradykinesia.

Trial of Deferiprone in Parkinson's Disease.

BACKGROUND: Iron content is increased in the substantia nigra of persons with Parkinson's disease and may contribute to the pathophysiology of the disorder. Early research suggests that the iron chelator deferiprone can reduce nigrostriatal iron content in persons with Parkinson's disease, but its effects on disease progression are unclear. METHODS: We conducted a multicenter, phase 2, randomized, double-blind trial involving participants with newly diagnosed Parkinson's disease who had never received levodopa. Participants were assigned (in a 1:1 ratio) to receive oral deferiprone at a dose of 15 mg per kilogram of body weight twice daily or matched placebo for 36 weeks. Dopaminergic therapy was withheld unless deemed necessary for symptom control. The primary outcome was the change in the total score on the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS; range, 0 to 260, with higher scores indicating more severe impairment) at 36 weeks. Secondary and exploratory clinical outcomes at up to 40 weeks included measures of motor and nonmotor disability. Brain iron content measured with the use of magnetic resonance imaging was also an exploratory outcome. RESULTS: A total of 372 participants were enrolled; 186 were assigned to receive deferiprone and 186 to receive placebo. Progression of symptoms led to the initiation of dopaminergic therapy in 22.0% of the participants in the deferiprone group and 2.7% of those in the placebo group. The mean MDS-UPDRS total score at baseline was 34.3 in the deferiprone group and 33.2 in the placebo group and increased (worsened) by 15.6 points and 6.3 points, respectively (difference, 9.3 points; 95% confidence interval, 6.3 to 12.2; P<0.001). Nigrostriatal iron content decreased more in the deferiprone group than in the placebo group. The main serious adverse events with deferiprone were agranulocytosis in 2 participants and neutropenia in 3 participants. CONCLUSIONS: In participants with early Parkinson's disease who had never received levodopa and in whom treatment with dopaminergic medications was not planned, deferiprone was associated with worse scores in measures of parkinsonism than those with placebo over a period of 36 weeks. (Funded by the European Union Horizon 2020 program; FAIRPARK-II ClinicalTrials.gov number, NCT02655315.).

Quantitative gait analysis value as a predictor of shunt surgery effectiveness in normal pressure hydrocephalus: A technical note.

INTRODUCTION: Shunt surgery (SS) remains the most effective treatment for idiopathic Normal pressure hydrocephalus (iNPH), but the selection of the patients with the greatest potential benefit remains elusive. OBJECTIVE: Identify gait features predictive of best response to SS in iNPH. METHODS: Eight patients with iNPH were assessed at baseline, after Cerebrospinal fluid tap-test (CSF-TT) and SS, with clinical scales (Clinical/Patient Global Clinical Impression, EuroQol-5D, Clinical Dementia Rating Scale(CDR), MoCA test, Hoehn-Yahr Scale) and gait analysis with inertial sensors. RESULTS: The 8 included iNPH patients had a mean age of 73 years(59-81), moderate cognitive (CDR-1.5 (0.5-2); MoCA-9.5 (3-21)) and motor impairment (Hoehn-Yahr-2.75(2-3)). After SS, patients had a significant improvement in cognition (MoCA, p = 0.001) and quality of life. At baseline, patients with lower improvement (no change/ minimally improved) (n = 2), in comparison to patient with higher improvement (much/very much improved) (n = 6), already had higher cognitive impairment (MoCa-3(3-3) vs. 11(7-21)). Patients with lower improvement had a lower % of change in gait performance at LP (mean 10.2 %) and were absent of additional benefit after SS(mean -0.8 %). In contrast, gait performance in patients with higher improvement consistently got better from baseline to LP (mean 23.1 %) and from baseline to SS (mean 82.9 %). A significant negative correlation was observed between CDR score and several gait variables: speed (rpb=-0.92,p = 0.009); stride length (rpb=-0.92,p = 0.009); lift-off angle (rpb=-0.96,p = 0.003); and maximum heel (rpb=-0.81,p = 0.049). CONCLUSION: The magnitude of gait improvement after CSF-TT, quantified by gait analysis, can be used as an integral variable in the multimodal clinical approach to the prediction of improvement after SS.

Embodiment Comfort Levels During Motor Imagery Training Combined With Immersive Virtual Reality in a Spinal Cord Injury Patient.

Brain-machine interfaces combining visual, auditory, and tactile feedback have been previously used to generate embodiment experiences during spinal cord injury (SCI) rehabilitation. It is not known if adding temperature to these modalities can result in discomfort with embodiment experiences. Here, comfort levels with the embodiment experiences were investigated in an intervention that required a chronic pain SCI patient to generate lower limb motor imagery commands in an immersive environment combining visual (virtual reality -VR), auditory, tactile, and thermal feedback. Assessments were made pre-/ post-, throughout the intervention (Weeks 0-5), and at 7 weeks follow up. Overall, high levels of embodiment in the adapted three-domain scale of embodiment were found throughout the sessions. No significant adverse effects of VR were reported. Although sessions induced only a modest reduction in pain levels, an overall reduction occurred in all pain scales (Faces, Intensity, and Verbal) at follow up. A high degree of comfort in the comfort scale for the thermal-tactile sleeve, in both the thermal and tactile feedback components of the sleeve was reported. This study supports the feasibility of combining multimodal stimulation involving visual (VR), auditory, tactile, and thermal feedback to generate embodiment experiences in neurorehabilitation programs.

Discrimination of idiopathic Parkinson's disease and vascular parkinsonism based on gait time series and the levodopa effect.

Idiopathic Parkinson's disease (IPD) and vascular parkinsonism (VaP) present highly overlapping phenotypes, making it challenging to distinguish between these two parkinsonian syndromes. Recent evidence suggests that gait assessment and response to levodopa medication may assist in the objective evaluation of clinical differences. In this paper, we propose a new approach for gait pattern differentiation that uses convolutional neural networks (CNNs) based on gait time series with and without the influence of levodopa medication. Wearable sensors positioned on both feet were used to acquire gait data from 14 VaP patients, 15 IPD patients, and 34 healthy subjects. An individual's gait features are affected by physical characteristics, including age, height, weight, sex, and walking speed or stride length. Therefore, to reduce bias due to intersubject variations, a multiple regression normalization approach was used to obtain gait data. Recursive feature elimination using the linear support vector machine, lasso, and random forest were applied to infer the optimal feature subset that led to the best results. CNNs were implemented by means of various hyperparameters and feature subsets. The best CNN classifiers achieved accuracies of 79.33%±6.46, 82.33%±10.62, and 86.00%±7.12 without (off state), with (on state), and with the simultaneous consideration of the effect of levodopa medication (off/on state), respectively. The response to levodopa medication improved classification performance. Based on gait time series and response to medication, the proposed approach differentiates between IPD and VaP gait patterns and reveals a high accuracy rate, which might prove useful when distinguishing other diseases related to movement disorders.

Fabry Disease and the Heart: A Comprehensive Review.

Fabry disease (FD) is an X-linked lysosomal storage disorder caused by mutations of the GLA gene that result in a deficiency of the enzymatic activity of α-galactosidase A and consequent accumulation of glycosphingolipids in body fluids and lysosomes of the cells throughout the body. GB3 accumulation occurs in virtually all cardiac cells (cardiomyocytes, conduction system cells, fibroblasts, and endothelial and smooth muscle vascular cells), ultimately leading to ventricular hypertrophy and fibrosis, heart failure, valve disease, angina, dysrhythmias, cardiac conduction abnormalities, and sudden death. Despite available therapies and supportive treatment, cardiac involvement carries a major prognostic impact, representing the main cause of death in FD. In the last years, knowledge has substantially evolved on the pathophysiological mechanisms leading to cardiac damage, the natural history of cardiac manifestations, the late-onset phenotypes with predominant cardiac involvement, the early markers of cardiac damage, the role of multimodality cardiac imaging on the diagnosis, management and follow-up of Fabry patients, and the cardiac efficacy of available therapies. Herein, we provide a comprehensive and integrated review on the cardiac involvement of FD, at the pathophysiological, anatomopathological, laboratory, imaging, and clinical levels, as well as on the diagnosis and management of cardiac manifestations, their supportive treatment, and the cardiac efficacy of specific therapies, such as enzyme replacement therapy and migalastat.

Automatic Resting Tremor Assessment in Parkinson's Disease Using Smartwatches and Multitask Convolutional Neural Networks.

Resting tremor in Parkinson's disease (PD) is one of the most distinctive motor symptoms. Appropriate symptom monitoring can help to improve management and medical treatments and improve the patients' quality of life. Currently, tremor is evaluated by physical examinations during clinical appointments; however, this method could be subjective and does not represent the full spectrum of the symptom in the patients' daily lives. In recent years, sensor-based systems have been used to obtain objective information about the disease. However, most of these systems require the use of multiple devices, which makes it difficult to use them in an ambulatory setting. This paper presents a novel approach to evaluate the amplitude and constancy of resting tremor using triaxial accelerometers from consumer smartwatches and multitask classification models. These approaches are used to develop a system for an automated and accurate symptom assessment without interfering with the patients' daily lives. Results show a high agreement between the amplitude and constancy measurements obtained from the smartwatch in comparison with those obtained in a clinical assessment. This indicates that consumer smartwatches in combination with multitask convolutional neural networks are suitable for providing accurate and relevant information about tremor in patients in the early stages of the disease, which can contribute to the improvement of PD clinical evaluation, early detection of the disease, and continuous monitoring.

Fabry Disease Therapy: State-of-the-Art and Current Challenges.

Fabry disease (FD) is a lysosomal storage disorder caused by mutations of the GLA gene that lead to a deficiency of the enzymatic activity of α-galactosidase A. Available therapies for FD include enzyme replacement therapy (ERT) (agalsidase alfa and agalsidase beta) and the chaperone migalastat. Despite the large body of literature published about ERT over the years, many issues remain unresolved, such as the optimal dose, the best timing to start therapy, and the clinical impact of anti-drug antibodies. Migalastat was recently approved for FD patients with amenable GLA mutations; however, recent studies have raised concerns that "in vitro" amenability may not always reflect "in vivo" amenability, and some findings on real-life studies have contrasted with the results of the pivotal clinical trials. Moreover, both FD specific therapies present limitations, and the attempt to correct the enzymatic deficiency, either by enzyme exogenous administration or enzyme stabilization with a chaperone, has not shown to be able to fully revert FD pathology and clinical manifestations. Therefore, several new therapies are under research, including new forms of ERT, substrate reduction therapy, mRNA therapy, and gene therapy. In this review, we provide an overview of the state-of-the-art on the currently approved and emerging new therapies for adult patients with FD.

Natural history of the late-onset phenotype of Fabry disease due to the p.F113L mutation.

BACKGROUND: The common GLA gene mutation p.F113L causes late-onset phenotype of Fabry disease (FD) with predominant cardiac manifestations. A founder effect of FD due to this mutation was found in the Portuguese region of Guimarães. Our study aims to deepen the knowledge on the natural history of this late-onset variant. METHODS: 203 consecutive adult Fabry patients with p.F113L mutation (79 males; mean age 46 ± 18 years), from this region, were submitted at baseline to a predefined diagnostic protocol. The occurrence of FD manifestations was analyzed in each decade of age in both genders. RESULTS: In males, left ventricular hypertrophy (40.2%) and late gadolinium enhancement (21.4%) arose over 30 years; heart failure (HF) (21.9%), ventricular tachycardia (8.9%) and conduction disorders over 40 years; and bifascicular (13.1%) and complete atrioventricular blocks (5.9%) beyond 50 years of age. Cardiac manifestations occurred more commonly and 1-2 decades earlier in males; their frequency increased with age. Septum and posterior wall thickness, LV mass, QRS interval duration and pro-BNP levels increased with age in both genders. Mean survival free from HF (64 ± 1 vs. 76 ± 2 years) and pacemaker (71 ± 2 vs. 86 ± 1 years) was higher in females (p < .001). Albuminuria A2/A3 (33.7%), brain white matter lesions (50.3%) and sensorineural deafness (44.7%) arose before 30 years of age in both genders, increasing with age. Renal failure and stroke were rare. Lysosomal inclusions were demonstrated in podocytes of patients with proteinuria. CONCLUSION: This study improves the knowledge on natural history of late-onset variants of FD, carrying major impact on clinical decisions and guidelines.