Present and future of parkinson’s disease in Spain: Parkinson-2030 delphi project

Parkinson’s disease (PD) is a chronic progressive and irreversible disease and the second most common neurodegenerative disease worldwide. In Spain, it affects around 120.000–150.000 individuals, and its prevalence is estimated to increase in the future. PD has a great impact on patients’ and caregivers’ lives and also entails a substantial socioeconomic burden. The aim of the present study was to examine the current situation and the 10-year PD forecast for Spain in order to optimize and design future management strategies. This study was performed using the modified Delphi method to try to obtain a consensus among a panel of movement disorders experts. According to the panel, future PD management will improve diagnostic capacity and follow-up, it will include multidisciplinary teams, and innovative treatments will be developed. The expansion of new technologies and studies on biomarkers will have an impact on future PD management, leading to more accurate diagnoses, prognoses, and individualized therapies. However, the socio-economic impact of the disease will continue to be significant by 2030, especially for patients in advanced stages. This study highlighted the unmet needs in diagnosis and treatment and how crucial it is to establish recommendations for future diagnostic and therapeutic management of PD.This project was funded by Zambon S.A.U

Dispositivos experimentales permanentes de la Unidad de Gestión Forestal Sostenible para el estudio de modelos de crecimiento forestal en Galicia

Se presentan los dispositivos experimentales permanentes instalados y mantenidos por la Unidad de Gestión Forestal Sostenible (Universidad de Santiago de Compostela) para la elaboración de modelos de crecimiento forestal, que constan de redes de parcelas permanentes con dos inventarios para Pinus radiata (151 parcelas) y Pinus sylvestris (91 parcelas), y con uno único para Quercus robur (172 parcelas), Betula alba (125 parcelas) y Pseudotsuga menziesii (92 parcelas). También se han instalado ensayos de claras, uno en masas de Pinus sylvestris y de Pinus pinaster, y dos en repoblaciones de Pinus radiata, en los que se ha establecido la posición exacta de cada pie dentro de las parcelas mediante una estación total topográfica. Finalmente se discute la necesidad, ventajas e inconvenientes de mantener dichos dispositivos experimentales como permanentes, así como el número adecuado de parcelas, la periodicidad óptima entre mediciones y el sistema de señalización de los árboles

Continuous intestinal infusion of levodopa-carbidopa in patients with advanced Parkinson's disease in Spain: Subanalysis by autonomous community

[ES] Objetivos: Comparar las características de los pacientes con enfermedad de Parkinson avanzada en tratamiento con infusión intestinal continua de levodopa-carbidopa (IICLC) y los datos de efectividad y seguridad de IICLC entre diferentes comunidades autónomas (CC. AA.). Métodos: Estudio longitudinal observacional y retrospectivo. Se incluyeron 177 pacientes de 11 CC. AA. que iniciaron tratamiento con IICLC entre enero de 2006 y diciembre de 2011. Se compararon las características clínicas y demográficas, las variables de efectividad (cambios en el tiempo OFF, ON con y sin discinesias discapacitantes, cambios en la escala de Hoehn y Yahr y puntuación de la Unified Parkinson's Disease Rating Scale, síntomas no motores e Impresión Clínica Global) y seguridad (acontecimientos adversos), y la tasa de suspensión de IICLC. Resultados: Se hallaron diferencias significativas entre las CC. AA. en diversas variables basales: duración de la enfermedad hasta el inicio de IICLC, tiempo OFF (34,9-59,7%) y ON (con o sin discinesias; 2,6-48,0%), Hoehn y Yahr en ON, Unified Parkinson's Disease Rating Scale-III en ON y OFF, presencia de ≥ 4 síntomas motores y dosis de IICLC. En el seguimiento (> 24 meses en 9 de 11 CC. AA.) hubo diferencias significativas en el porcentaje de tiempo OFF, tiempo ON sin discinesias discapacitantes, frecuencia de acontecimientos adversos e Impresión Clínica Global. La tasa de suspensión fue de entre 20-40% en todas las CC. AA., excepto en 2 (78 y 80%). Conclusiones: Este estudio muestra una amplia variabilidad en la selección de los pacientes y en la efectividad y seguridad de IICLC entre las diferentes CC. AA. Podrían influir las características basales de los pacientes, la disponibilidad de un equipo multidisciplinar y la experiencia clínica.[EN] Objectives: To compare the characteristics of patients undergoing treatment with continuous intestinal infusion of levodopa-carbidopa (CIILC) for advanced Parkinson's disease and the data on the effectiveness and safety of CIILC in the different autonomous communities (AC) of Spain. Methods: A retrospective, longitudinal, observational study was carried out into 177 patients from 11 CAs who underwent CIILC between January 2006 and December 2011. We analysed data on patients’ clinical and demographic characteristics, variables related to effectiveness (changes in off time/on time with or without disabling dyskinesia; changes in Hoehn and Yahr scale and Unified Parkinson's Disease Rating Scale scores; non-motor symptoms; and Clinical Global Impression scale scores) and safety (adverse events), and the rate of CIILC discontinuation. Results: Significant differences were observed between CAs for several baseline variables: duration of disease progression prior to CIILC onset, off time (34.9-59.7%) and on time (2.6-48.0%; with or without disabling dyskinesia), Hoehn and Yahr score during on time, Unified Parkinson's Disease Rating Scale-III score during both on and off time, presence of ≥ 4 motor symptoms, and CIILC dose. Significant differences were observed during follow-up (> 24 months in 9 of the 11 CAs studied) for the percentage of off time and on time without disabling dyskinesia, adverse events frequency, and Clinical Global Impression scores. The rate of CIILC discontinuation was between 20-40% in 9 CAs (78 and 80% in remaining 2 CAs). Conclusions: This study reveals a marked variability between CAs in terms of patient selection and CIILC safety and effectiveness. These results may have been influenced by patients’ baseline characteristics, the availability of multidisciplinary teams, and clinical experience.AbbVie Spain, S. L. U. financió este estudio, fue responsable del diseño y coordinó la recogida de datos

Impact of Disease Duration in Effectiveness of Treatment with Levodopa-Carbidopa Intestinal Gel and Factors Leading to Discontinuation

[Background] Levodopa-carbidopa intestinal gel (LCIG) is effective in the treatment of advanced Parkinson’s disease (PD). However, the patients’ profile that might benefit from treatment with LCIG has not been characterized.[Objective]This retrospective study explored the influence of disease duration (DD) on the effectiveness of LCIG and identified factors associated with treatment discontinuation in a cohort of advanced PD patients.[Methods] Patients initiating LCIG therapy between Jan-2006 and Dec-2011 in 18 Spanish centers were included. Effectiveness in treating motor symptoms (MSs), non-motor symptoms (NMSs), and adverse events (AEs) occurrence was compared in DD≥10 or <10 years and LCIG continuation/discontinuation groups. Factors associated with LCIG discontinuation were evaluated using univariate and multivariate analyses.[Results] Overall, 177 PD patients were included (52.5% male; mean age 70.6±8.4 years; mean LCIG duration 35.6±18.6 months). Patients with DD≥10 years (n = 125) experienced less reduction in “off” time (–29%) than those with DD <10 years (–38%; n = 51; p = 0.021), and reported more severe AEs (32.8% vs. 17.6%; p = 0.043). DD did not significantly influence changes in NMSs or discontinuation rates. Fifty-four patients discontinued LCIG therapy, factors associated with discontinuation were higher percentages of waking day in the “off” state (OR, 1.028; 95% CI, 1.002–1.055; p = 0.0360) and in the “on” state with troublesome dyskinesia (OR, 1.032; 95% CI, 1.002–1.064; p = 0.0376) at baseline.[Conclusions] Advanced PD patients with DD <10 years might benefit more from treatment with LCIG than patients with a longer DD. Although MSs severity at baseline was statistically associated with LCIG discontinuation, the probability was very low with little clinical significance

Novel strategies based on sensory electrical stimulation to manage tremor in Parkinson¿s disease. A pilot study

Objective: Tremor can be a disabling motor symptom in patients with Parkinson¿s disease (PD) and in some patients is refractory to medication. Here we present a pilot study on the potential of peripheral electrical stimulation to reduce pathological tremor in two PD patients. Background: Recently, electrical stimulation of afferent pathways has been explored as a potential approach for tremor reduction [1] [2]. We have recently demonstrated the potential of selective and adaptive timely stimulation (SATS) in essential tremor patients, with some of these patients sustaining tremor reduction 24h after stimulation trials [3]. Method: Two PD patients with rest and postural tremor (one female and one male, 50 and 59 years old) were recruited from Gregorio Marañón Hospital (Madrid, Spain). All procedures were approved by the hospital ethics committee. Surface electromyography (sEMG) electrodes were placed over flexor carpi radialis and extensor carpi radialis of the side most affected by tremor. Surface stimulation electrodes were placed over the radial and the median nerves. An embedded control unit including an electrical stimulator and an EMG amplifier was used to record sEMG signals at 2 kHz and provide biphasic stimulation of 100 Hz and 400 µs of pulse width. Four inertial measurement units were placed in the chest, lateral side of the arm, forearm, and dorsal side of the hand to quantify changes in tremor amplitude. Each patient was asked to maintain the arms in a position that would elicit the greatest tremor amplitude. Several SATS out-of-phase (i.e., stimulation of the antagonist muscle to the one presenting tremor) trials were performed on each patient (30 seconds of stimulation; 7 and 6 trials for patients 1 and 2, respectively). Clinical evaluation was performed before and immediately after the stimulation. Results: Both patients experienced a significant tremor reduction in all joints after stimulation trials (see [figure1] and [figure2]). For patient 1, the reduction was greater in the shoulder joint. Patient 2 showed considerable tremor reduction in all joints. Moreover, both patients improved in the clinical assessment. Conclusion: These preliminary results suggest that SATS via peripheral electrical stimulation may induce an acute reduction of the postural component of PD tremor. This work was supported by the EU Horizon 2020 research and innovation programme (Project EXTEND, Grant 779982).This work was supported by the EU Horizon 2020 research and innovation programme (Project EXTEND, Grant 779982)

Study of the automatic detection of Parkison's Disease based on speaker recognition technologies and allophonic distillation

The use of new tools to detect Parkinson´s Disease (PD) from speech articulatory movements can have a considerable impact in the diagnosis of patients. In this study, a novel approach involving speaker recognition techniques with allophonic distillation is proposed and tested separately in four parkinsonian speech databases (205 patients and 186 controls in total). The results of applying this new scheme in the databases provides up to 94% of accuracy in the automatic detection of PD and improvements up to 9% respect to baseline techniques. Results not only point towards the importance of the segmentation of the speech for the differentiation of parkinsonian and control speakers but confirm previous findings about the relevance of plosives and fricatives in the detection of parkinsonian dysarthria

Classification of Kinematic and Electromyographic Signals Associated with Pathological Tremor Using Machine and Deep Learning

Peripheral Electrical Stimulation (PES) of afferent pathways has received increased interest as a solution to reduce pathological tremors with minimal side effects. Closed-loop PES systems might present some advantages in reducing tremors, but further developments are required in order to reliably detect pathological tremors to accurately enable the stimulation only if a tremor is present. This study explores different machine learning (K-Nearest Neighbors, Random Forest and Support Vector Machines) and deep learning (Long Short-Term Memory neural networks) models in order to provide a binary (Tremor; No Tremor) classification of kinematic (angle displacement) and electromyography (EMG) signals recorded from patients diagnosed with essential tremors and healthy subjects. Three types of signal sequences without any feature extraction were used as inputs for the classifiers: kinematics (wrist flexion–extension angle), raw EMG and EMG envelopes from wrist flexor and extensor muscles. All the models showed high classification scores (Tremor vs. No Tremor) for the different input data modalities, ranging from 0.8 to 0.99 for the f1 score. The LSTM models achieved 0.98 f1 scores for the classification of raw EMG signals, showing high potential to detect tremors without any processed features or preliminary information. These models may be explored in real-time closed-loop PES strategies to detect tremors and enable stimulation with minimal signal processing steps

First-in-human demonstration of floating EMG sensors and stimulators wirelessly powered and operated by volume conduction

Background: Recently we reported the design and evaluation of floating semi-implantable devices that receive power from and bidirectionally communicate with an external system using coupling by volume conduction. The approach, of which the semi-implantable devices are proof-of-concept prototypes, may overcome some limitations presented by existing neuroprostheses, especially those related to implant size and deployment, as the implants avoid bulky components and can be developed as threadlike devices. Here, it is reported the first-in-human acute demonstration of these devices for electromyography (EMG) sensing and electrical stimulation. Methods: A proof-of-concept device, consisting of implantable thin-film electrodes and a nonimplantable miniature electronic circuit connected to them, was deployed in the upper or lower limb of six healthy participants. Two external electrodes were strapped around the limb and were connected to the external system which delivered high frequency current bursts. Within these bursts, 13 commands were modulated to communicate with the implant. Results: Four devices were deployed in the biceps brachii and the gastrocnemius medialis muscles, and the external system was able to power and communicate with them. Limitations regarding insertion and communication speed are reported. Sensing and stimulation parameters were configured from the external system. In one participant, electrical stimulation and EMG acquisition assays were performed, demonstrating the feasibility of the approach to power and communicate with the floating device. Conclusions: This is the first-in-human demonstration of EMG sensors and electrical stimulators powered and operated by volume conduction. These proof-of-concept devices can be miniaturized using current microelectronic technologies, enabling fully implantable networked neuroprosthetics.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 779982 (Project EXTEND - Bidirectional Hyper-Connected Neural System). CR has been also partially funded by CSIC Interdisciplinary Thematic Platform (PTI+) NEURO-AGINGl+ (PTI-NEURO-AGING+). FOB thanks the financial support from the Spanish MCIN/AEI/https://doi.org/10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR” under Grant agreement IJC2020-044467-I. AI gratefully acknowledges the financial support by ICREA under the ICREA Academia programme

Classification of kinematic and electromyographic signals associated with pathological tremor using machine and deep learning

2023 Descuento MDPIPeripheral Electrical Stimulation (PES) of afferent pathways has received increased interest as a solution to reduce pathological tremors with minimal side effects. Closed-loop PES systems might present some advantages in reducing tremors, but further developments are required in order to reliably detect pathological tremors to accurately enable the stimulation only if a tremor is present. This study explores different machine learning (K-Nearest Neighbors, Random Forest and Support Vector Machines) and deep learning (Long Short-Term Memory neural networks) models in order to provide a binary (Tremor; No Tremor) classification of kinematic (angle displacement) and electromyography (EMG) signals recorded from patients diagnosed with essential tremors and healthy subjects. Three types of signal sequences without any feature extraction were used as inputs for the classifiers: kinematics (wrist flexion-extension angle), raw EMG and EMG envelopes from wrist flexor and extensor muscles. All the models showed high classification scores (Tremor vs. No Tremor) for the different input data modalities, ranging from 0.8 to 0.99 for the f(1) score. The LSTM models achieved 0.98 f(1) scores for the classification of raw EMG signals, showing high potential to detect tremors without any processed features or preliminary information. These models may be explored in real-time closed-loop PES strategies to detect tremors and enable stimulation with minimal signal processing steps.European CommissionMinisterio de Ciencia e Innovación (España)Depto. de MedicinaFac. de MedicinaTRUEpubDescuento UC