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385 results on '"Gómez Esteban, Juan Carlos"'

4. Predicting Parkinson’s Disease Progression: Analyzing Prodromal Stages Through Machine Learning

Author

Martinez-Eguiluz, Maitane, Muguerza, Javier, Arbelaitz, Olatz, Gurrutxaga, Ibai, Gomez-Esteban, Juan Carlos, Murueta-Goyena, Ane, Gabilondo, Iñigo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Alonso-Betanzos, Amparo, editor, Guijarro-Berdiñas, Bertha, editor, Bolón-Canedo, Verónica, editor, Hernández-Pereira, Elena, editor, Fontenla-Romero, Oscar, editor, Camacho, David, editor, Rabuñal, Juan Ramón, editor, Ojeda-Aciego, Manuel, editor, Medina, Jesús, editor, Riquelme, José C., editor, and Troncoso, Alicia, editor

Published
2024
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6. Artificial intelligence for identification of candidates for device-aided therapy in Parkinson's disease: DELIST-PD study

Author

Freire-Álvarez, Eric, Ramírez, Inés Legarda, García-Ramos, Rocio, Carrillo, Fátima, Santos-García, Diego, Gómez-Esteban, Juan Carlos, Martínez-Castrillo, Juan Carlos, Martínez-Torres, Irene, Madrid-Navarro, Carlos J., Pérez-Navarro, María José, Valero-García, Fuensanta, Vives-Pastor, Bárbara, Muñoz-Delgado, Laura, Tijero, Beatriz, Martínez, Carlos Morata, Valls, José M., Aler, Ricardo, Galván, Inés M., and Escamilla-Sevilla, Francisco

Published
2025
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8. Rapid iPSC inclusionopathy models shed light on formation, consequence, and molecular subtype of α-synuclein inclusions

Author

Lam, Isabel, Ndayisaba, Alain, Lewis, Amanda J., Fu, YuHong, Sagredo, Giselle T., Kuzkina, Anastasia, Zaccagnini, Ludovica, Celikag, Meral, Sandoe, Jackson, Sanz, Ricardo L., Vahdatshoar, Aazam, Martin, Timothy D., Morshed, Nader, Ichihashi, Toru, Tripathi, Arati, Ramalingam, Nagendran, Oettgen-Suazo, Charlotte, Bartels, Theresa, Boussouf, Manel, Schäbinger, Max, Hallacli, Erinc, Jiang, Xin, Verma, Amrita, Tea, Challana, Wang, Zichen, Hakozaki, Hiroyuki, Yu, Xiao, Hyles, Kelly, Park, Chansaem, Wang, Xinyuan, Theunissen, Thorold W., Wang, Haoyi, Jaenisch, Rudolf, Lindquist, Susan, Stevens, Beth, Stefanova, Nadia, Wenning, Gregor, van de Berg, Wilma D.J., Luk, Kelvin C., Sanchez-Pernaute, Rosario, Gómez-Esteban, Juan Carlos, Felsky, Daniel, Kiyota, Yasujiro, Sahni, Nidhi, Yi, S. Stephen, Chung, Chee Yeun, Stahlberg, Henning, Ferrer, Isidro, Schöneberg, Johannes, Elledge, Stephen J., Dettmer, Ulf, Halliday, Glenda M., Bartels, Tim, and Khurana, Vikram

Published
2024
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17. Prognostic factors for falls in Parkinson’s disease: a systematic review

Author

Neurociencias, Neurozientziak, Murueta-Goyena Larrañaga, Ane, Muiño, Oier, Gómez Esteban, Juan Carlos, Neurociencias, Neurozientziak, Murueta-Goyena Larrañaga, Ane, Muiño, Oier, and Gómez Esteban, Juan Carlos

Abstract

Background Falls represent a critical concern in Parkinson’s disease (PD), contributing to increased morbidity and reduced quality of life. Purpose We conducted a systematic review to assess the prognostic factors associated with falls in PD, aiming to provide a comprehensive overview of relevant demographic and clinical parameters, and aid neurologists in identifying subsets of PD patients most susceptible to falls and associated injuries. Methods PubMed and Web of Science databases were searched for prospective studies assessing factors associated with falls in ambulatory PD patients across different settings, from inception to August 2023. Data extraction was conducted using CHARMS-PF checklist and risk of bias was assessed with QUIPS tool. PRISMA guidelines were followed. Results The initial search yielded 155 references. Thirty-four studies, involving a total of 3454 PD patients, were included in the final analysis. The mean pooled age was 67.6 years, and 45.1% were women. PD patients presented mild motor impair- ment (UPDRS III score 27.8) with mean pooled disease duration of 5.7 years. Gait and balance disorders and history of prior falls emerged as the most consistent predictors of falls across studies. Disease duration, disease severity, dysautonomic symptoms, freezing of gait, frontal cognitive functions, and PD medication dosages yielded inconsistent findings. Conversely, dyskinesias, age, sex, and depression were unrelated to future falls in PD. Logistic regression models were most commonly employed to identify factors significantly associated with falls in PD. Substantial heterogeneity prevailed in the inclusion of confounding factors. Conclusion The evidence suggests that previous history of falls, gait disorders, and poor balance are robust prognostic markers for falls in PD.

Published
2024

22. Plasma Neurofilament Light Chain: A Potential Biomarker for Neurological Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Author

Azcue, Naiara, Tijero-Merino, Beatriz, Acera, Marian, Pérez-Garay, Raquel, Fernández-Valle, Tamara, Ayo-Mentxakatorre, Naia, Ruiz-López, Marta, Lafuente, Jose Vicente, Gómez Esteban, Juan Carlos, and Del Pino, Rocio

Subjects
CHRONIC fatigue syndrome, AUTONOMIC nervous system, COGNITIVE testing, VISUAL memory, NEUROPSYCHOLOGICAL tests
Abstract

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex disorder characterized by heterogeneous symptoms, which lack specific biomarkers for its diagnosis. This study aimed to investigate plasma neurofilament light chain (NfL) levels as a potential biomarker for ME/CFS and explore associations with cognitive, autonomic, and neuropathic symptoms. Here, 67 ME/CFS patients and 43 healthy controls (HCs) underwent comprehensive assessments, including neuropsychological evaluation, autonomic nervous system (ANS) testing, and plasma NfL level analysis. ME/CFS patients exhibited significantly higher plasma NfL levels compared to HC (F = 4.30, p < 0.05). Correlations were observed between NfL levels and cognitive impairment, particularly in visuospatial perception (r = −0.42; p ≤ 0.001), verbal memory (r = −0.35, p ≤ 0.005), and visual memory (r = −0.26; p < 0.05) in ME/CFS. Additionally, higher NfL levels were associated with worsened autonomic dysfunction in these patients, specifically in parasympathetic function (F = 9.48, p ≤ 0.003). In ME/CFS patients, NfL levels explained up to 17.2% of the results in cognitive tests. Unlike ME/CFS, in HC, NfL levels did not predict cognitive performance. Elevated plasma NfL levels in ME/CFS patients reflect neuroaxonal damage, contributing to cognitive dysfunction and autonomic impairment. These findings support the potential role of NfL as a biomarker for neurological dysfunction in ME/CFS. Further research is warranted to elucidate underlying mechanisms and clinical implications. [ABSTRACT FROM AUTHOR]

Published
2024
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23. Virtual Coaching for Home Rehabilitation – Evidence of an Empirical Study.

Author

SCHLIETER, Hannes, GAND, Kai, WEIMANN, Thure Georg, CAPRINO, Massimo, CORBO, Massimo, SEREGNI, Agnese, TROPEA, Peppino, PINO, Rocio DEL, GÓMEZ ESTEBAN, Juan Carlos, GABILONDO, Iñigo, LACRARU, Andreea, and BUSNATU, Stefan

Abstract

Older individuals often face disabilities or diseases that lower their quality of life (QoL). While inpatient rehabilitation can initially enhance QoL, there is often a lack of continuation at home. Virtual coaches (VCs) as specific embodied conversational agents promise appropriate support for home rehabilitation. They emerge as complementary digital aids to ensure care continuity. This paper presents the results of implementing a full-featured VC for older patients' home rehabilitation in a multi-stage study, summarizing the main results regarding QoL outcomes and user experience tests. The study confirms the intervention as an engaging means for rehabilitation (mostly above user experience thresholds) and improvements of QoL (>10% between experimental and control groups). [ABSTRACT FROM AUTHOR]

Published
2024
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27. Dysautonomia and small fiber neuropathy in post-COVID condition and Chronic Fatigue Syndrome

Author

Azcue, Naiara, primary, Pino, Rocio Del, additional, Acera, Marian, additional, Valle, Tamara Fernandez, additional, Mentxakatorre, Naia Ayo, additional, Concha, Tomás Pérez, additional, Murueta-Goyena, Ane, additional, Lafuente, Jose Vicente, additional, Prada-Iñurrategui, Álvaro, additional, de Munain, Adolfo López, additional, Ruiz-Irastorza, Guillermo, additional, Martín-Iglesias, Daniel, additional, Ribacoba, Laureano, additional, Gabilondo, Iñigo, additional, Gómez-Esteban, Juan Carlos, additional, and Tijero-Merino, Beatriz, additional

Published
2023
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28. Building Bridges through Science

Author

Lissek, Thomas, Adams, Michelle, Adelman, John, Ahissar, Ehud, Akaaboune, Mohammed, Akil, Huda, al’Absi, Mustafa, Arain, Fazal, Arango-Lasprilla, Juan Carlos, Atasoy, Deniz, Avila, Jesus, Badawi, Ashraf, Bading, Hilmar, Baig, Abdul Mannan, Baleriola, Jimena, Belmonte, Carlos, Bertocchi, Ilaria, Betz, Heinrich, Blakemore, Colin, Blanke, Olaf, Boehm-Sturm, Philipp, Bonhoeffer, Tobias, Bonifazi, Paolo, Brose, Nils, Campolongo, Patrizia, Celikel, Tansu, Chang, Cathy C., Chang, Ta-Yuan, Citri, Ami, Cline, Hollis T., Cortes, Jesus M., Cullen, Kathleen, Dean, Kellie, Delgado-Garcia, José M., Desroches, Mathieu, Disterhoft, John F., Dowling, John E., Draguhn, Andreas, El-Khamisy, Sherif F., El Manira, Abdeljabbar, Enam, S. Ather, Encinas, Juan M., Erramuzpe, Asier, Esteban, José A., Fariñas, Isabel, Fischer, Edmond, Fukunaga, Izumi, Gabilondo, Iñigo, Ganten, Detlev, Gidon, Albert, Gomez-Esteban, Juan Carlos, Greengard, Paul, Grinevich, Valery, Gruart, Agnés, Guillemin, Roger, Hariri, Ahmad R., Hassan, Bassem, Häusser, Michael, Hayashi, Yasunori, Hussain, Natasha K., Jabbar, Adnan Abdul, Jaber, Mohamed, Jahn, Reinhardt, Janahi, Essam Mohammed, Kabbaj, Mohamed, Kettenmann, Helmut, Kindt, Merel, Knafo, Shira, Köhr, Georg, Komai, Shoji, Krugers, Harm, Kuhn, Bernd, Ghazal, Nouria Lakhdar, Larkum, Matthew E., London, Mickey, Lutz, Beat, Matute, Carlos, Martinez-Millan, Luis, Maroun, Mouna, McGaugh, James, Moustafa, Ahmed A., Nasim, Anwar, Nave, Klaus-Armin, Neher, Erwin, Nikolich, Karoly, Outeiro, Tiago, Palmer, Lucy M., Penagarikano, Olga, Perez-Otano, Isabel, Pfaff, Donald W., Poucet, Bruno, Rahman, Atta-ur, Ramos-Cabrer, Pedro, Rashidy-Pour, Ali, Roberts, Richard J., Rodrigues, Serafim, Sanes, Joshua R., Schaefer, Andreas T., Segal, Menahem, Segev, Idan, Shafqat, Saad, Siddiqui, Nikhat Ahmed, Soreq, Hermona, Soriano-García, Eduardo, Spanagel, Rainer, Sprengel, Rolf, Stuart, Greg, Südhof, Thomas C., Tønnesen, Jan, Treviño, Mario, Uthman, Basim M., Venter, J. Craig, Verkhratsky, Alexei, Weiss, Craig, Wiesel, Torsten N., Yaksi, Emre, Yizhar, Ofer, Young, Larry J., Young, Paul, Zawia, Nasser H., Zugaza, José L., and Hasan, Mazahir T.

Published
2017
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32. Diagnostic classification of Parkinson’s disease based on non-motor manifestations and machine learning strategies

Author

Arquitectura y Tecnología de Computadores, Neurociencias, Konputagailuen Arkitektura eta Teknologia, Neurozientziak, Martínez Eguiluz, Maitane, Arbelaiz Gallego, Olatz, Gurrutxaga Goikoetxea, Ibai, Muguerza Rivero, Javier Francisco, Perona Balda, Iñigo, Murueta-Goyena Larrañaga, Ane, Acera Gil, María Ángeles, Del Pino Sáez, Rocío, Tijero Merino, Beatriz, Gómez Esteban, Juan Carlos, Gabilondo Cuellar, Iñigo, Arquitectura y Tecnología de Computadores, Neurociencias, Konputagailuen Arkitektura eta Teknologia, Neurozientziak, Martínez Eguiluz, Maitane, Arbelaiz Gallego, Olatz, Gurrutxaga Goikoetxea, Ibai, Muguerza Rivero, Javier Francisco, Perona Balda, Iñigo, Murueta-Goyena Larrañaga, Ane, Acera Gil, María Ángeles, Del Pino Sáez, Rocío, Tijero Merino, Beatriz, Gómez Esteban, Juan Carlos, and Gabilondo Cuellar, Iñigo

Abstract

Non-motor manifestations of Parkinson’s disease (PD) appear early and have a significant impact on the quality of life of patients, but few studies have evaluated their predictive potential with machine learning algorithms. We evaluated 9 algorithms for discriminating PD patients from controls using a wide collection of non-motor clinical PD features from two databases: Biocruces (96 subjects) and PPMI (687 subjects). In addition, we evaluated whether the combination of both databases could improve the individual results. For each database 2 versions with different granularity were created and a feature selection process was performed. We observed that most of the algorithms were able to detect PD patients with high accuracy (>80%). Support Vector Machine and Multi-Layer Perceptron obtained the best performance, with an accuracy of 86.3% and 84.7%, respectively. Likewise, feature selection led to a significant reduction in the number of variables and to better performance. Besides, the enrichment of Biocruces database with data from PPMI moderately benefited the performance of the classification algorithms, especially the recall and to a lesser extent the accuracy, while the precision worsened slightly. The use of interpretable rules obtained by the RIPPER algorithm showed that simply using two variables (autonomic manifestations and olfactory dysfunction), it was possible to achieve an accuracy of 84.4%. Our study demonstrates that the analysis of non-motor parameters of PD through machine learning techniques can detect PD patients with high accuracy and recall, and allows us to select the most discriminative non-motor variables to create potential tools for PD screening.

Published
2023

33. Staging Parkinson’s Disease According to the MNCD (Motor/Non-motor/Cognition/Dependency) Classification Correlates with Disease Severity and Quality of Life

Author

Fundación Degen, Alpha Bioresearch, Ministerio de Economía y Competitividad (España), Instituto de Salud Carlos III, Santos-García, Diego, Deus Fonticoba, T. de, Cores Bartolomé, Carlos, Feal Painceiras, María J., Íñiguez-Alvarado, María Cristina, García Díaz, Iago, Jesús Maestre, Silvia, Buongiorno, Maria Teresa, Planellas, Lluís, Cosgaya, Marina, García Caldentey, Juan, Caballol, Nuria, Legarda, Inés, Hernández-Vara, Jorge, Cabo, Iria, López-Manzanares, Lydia, González-Aramburu, Isabel, Ávila-Rivera, María A., Gómez Mayordomo, Víctor, Nogueira, Víctor, Puente, Víctor, Dotor, Julio, Borrué, Carmen, Solano Vila, Berta, Álvarez-Sauco, María, Vela, Lydia, Escalante, Sonia, Cubo, Esther, Carrillo Padilla, Francisco, Martínez-Castrillo, J. C., Sánchez Alonso, Pilar, Alonso Losada, María G., López-Ariztegui, Nuria, Gastón, Itziar, Kulisevsky, Jaime, Menéndez-González, Manuel, Seijo, Manuel, Ruiz Martínez, Javier, Valero, Caridad, Kurtis, Mónica, González Ardura, Jessica, Alonso Redondo, Rubén, Ordás, Carlos, López-Díaz, Luis M., McAfee, Darrian, Calopa, Matildeoo, Carrillo, Fátima, Escamilla-Sevilla, Francisco, Freire, Eric, Gómez Esteban, Juan Carlos, García-Ramos, Rocío, Luquín, María Rosario Isabel, Martínez Torres, Irene, Sesar Ignacio, Ángel, Martínez-Martín, Pablo, Mir, Pablo, COPPADIS Study Group, Fundación Degen, Alpha Bioresearch, Ministerio de Economía y Competitividad (España), Instituto de Salud Carlos III, Santos-García, Diego, Deus Fonticoba, T. de, Cores Bartolomé, Carlos, Feal Painceiras, María J., Íñiguez-Alvarado, María Cristina, García Díaz, Iago, Jesús Maestre, Silvia, Buongiorno, Maria Teresa, Planellas, Lluís, Cosgaya, Marina, García Caldentey, Juan, Caballol, Nuria, Legarda, Inés, Hernández-Vara, Jorge, Cabo, Iria, López-Manzanares, Lydia, González-Aramburu, Isabel, Ávila-Rivera, María A., Gómez Mayordomo, Víctor, Nogueira, Víctor, Puente, Víctor, Dotor, Julio, Borrué, Carmen, Solano Vila, Berta, Álvarez-Sauco, María, Vela, Lydia, Escalante, Sonia, Cubo, Esther, Carrillo Padilla, Francisco, Martínez-Castrillo, J. C., Sánchez Alonso, Pilar, Alonso Losada, María G., López-Ariztegui, Nuria, Gastón, Itziar, Kulisevsky, Jaime, Menéndez-González, Manuel, Seijo, Manuel, Ruiz Martínez, Javier, Valero, Caridad, Kurtis, Mónica, González Ardura, Jessica, Alonso Redondo, Rubén, Ordás, Carlos, López-Díaz, Luis M., McAfee, Darrian, Calopa, Matildeoo, Carrillo, Fátima, Escamilla-Sevilla, Francisco, Freire, Eric, Gómez Esteban, Juan Carlos, García-Ramos, Rocío, Luquín, María Rosario Isabel, Martínez Torres, Irene, Sesar Ignacio, Ángel, Martínez-Martín, Pablo, Mir, Pablo, and COPPADIS Study Group

Abstract

Background: Recently, a novel simple classification called MNCD, based on 4 axes (Motor; Non-motor; Cognition; Dependency) and 5 stages, has been proposed to classify Parkinson's disease (PD)., Objective: Our aim was to apply the MNCD classification in a cohort of PD patients for the first time and also to analyze the correlation with quality of life (QoL) and disease severity., Methods: Data from the baseline visit of PD patients recruited from 35 centers in Spain from the COPPADIS cohort fromJanuary 2016 to November 2017 were used to apply the MNCD classification. Three instruments were used to assess QoL:1) the 39-item Parkinson's disease Questionnaire [PDQ-39]); PQ-10; the EUROHIS-QOL 8-item index (EUROHIS-QOL8)., Results: Four hundred and thirty-nine PD patients (62.05±7.84 years old; 59% males) were included. MNCD stage was:stage 1, 8.4% (N = 37); stage 2, 62% (N = 272); stage 3, 28.2% (N = 124); stage 4-5, 1.4% (N = 6). A more advancedMNCD stage was associated with a higher score on the PDQ39SI (p < 0.0001) and a lower score on the PQ-10 (p< 0.0001) and EUROHIS-QOL8 (p< 0.0001). In many other aspects of the disease, such as disease duration, levodopa equivalent daily dose, motor symptoms, non-motor symptoms, and autonomy for activities of daily living, an association between the stage and severity was observed, with data indicating a progressive worsening related to disease progression throughout the proposed stages., Conclusion: Staging PD according to the MNCD classification correlated with QoL and disease severity. The MNCD could be a proper tool to monitor the progression of PD.

Published
2023

34. Brain Degeneration in Synucleinopathies Based on Analysis of Cognition and Other Nonmotor Features: A Multimodal Imaging Study

Author

Lucas-Jiménez, Olaia, primary, Ibarretxe-Bilbao, Naroa, additional, Diez, Ibai, additional, Peña, Javier, additional, Tijero, Beatriz, additional, Galdós, Marta, additional, Murueta-Goyena, Ane, additional, Del Pino, Rocío, additional, Acera, Marian, additional, Gómez-Esteban, Juan Carlos, additional, Gabilondo, Iñigo, additional, and Ojeda, Natalia, additional

Published
2023
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37. SYNAPSES. Estudio observacional europeo para evaluar la seguridad y la efectividad de la safinamida en la práctica clínica habitual: análisis post hoc de la población española del estudio

Author

Kulisevsky Bojarski, Jaume, primary, Esquivel, Alberto, additional, Freire Álvarez, Eric, additional, Gómez Esteban, Juan Carlos, additional, Legarda Ramírez, Inés, additional, Avilés, Arantxa, additional, and Mata Álvarez-Santullano, Marina, additional

Published
2023
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40. Correction to: Multimodal visual system analysis as a biomarker of visual hallucinations in Parkinson’s disease

Author

Diez-Cirarda, Maria, primary, Cabrera-Zubizarreta, Alberto, additional, Murueta-Goyena, Ane, additional, Strafella, Antonio P., additional, Del Pino, Rocio, additional, Acera, Marian, additional, Lucas-Jiménez, Olaia, additional, Ibarretxe-Bilbao, Naroa, additional, Tijero, Beatriz, additional, Gómez-Esteban, Juan Carlos, additional, and Gabilondo, Iñigo, additional

Published
2022
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43. Rapid iPSC inclusionopathy models shed light on formation, consequence and molecular subtype of α-synuclein inclusions

Author

Lam, Isabel, primary, Ndayisaba, Alain, additional, Lewis, Amanda J., additional, Fu, YuHong, additional, Sagredo, Giselle T., additional, Zaccagnini, Ludovica, additional, Sandoe, Jackson, additional, Sanz, Ricardo L., additional, Vahdatshoar, Aazam, additional, Martin, Timothy D., additional, Morshed, Nader, additional, Ichihashi, Toru, additional, Tripathi, Arati, additional, Ramalingam, Nagendran, additional, Oettgen-Suazo, Charlotte, additional, Bartels, Theresa, additional, Schäbinger, Max, additional, Hallacli, Erinc, additional, Jiang, Xin, additional, Verma, Amrita, additional, Tea, Challana, additional, Wang, Zichen, additional, Hakozaki, Hiroyuki, additional, Yu, Xiao, additional, Hyles, Kelly, additional, Park, Chansaem, additional, Theunissen, Thorold W., additional, Wang, Haoyi, additional, Jaenisch, Rudolf, additional, Lindquist, Susan, additional, Stevens, Beth, additional, Stefanova, Nadia, additional, Wenning, Gregor, additional, Luk, Kelvin C., additional, Pernaute, Rosario Sanchez, additional, Gómez-Esteban, Juan Carlos, additional, Felsky, Daniel, additional, Kiyota, Yasujiro, additional, Sahni, Nidhi, additional, Yi, S. Stephen, additional, Chung, Chee-Yeun, additional, Stahlberg, Henning, additional, Ferrer, Isidro, additional, Schöneberg, Johannes, additional, Elledge, Stephen J., additional, Dettmer, Ulf, additional, Halliday, Glenda M., additional, Bartels, Tim, additional, and Khurana, Vikram, additional

Published
2022
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44. Multimodal visual system analysis as a biomarker of visual hallucinations in Parkinson’s disease

Author

Diez-Cirarda, Maria, primary, Cabrera-Zubizarreta, Alberto, additional, Murueta-Goyena, Ane, additional, Strafella, Antonio P., additional, Del Pino, Rocio, additional, Acera, Marian, additional, Lucas-Jiménez, Olaia, additional, Ibarretxe-Bilbao, Naroa, additional, Tijero, Beatriz, additional, Gómez-Esteban, Juan Carlos, additional, and Gabilondo, Iñigo, additional

Published
2022
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46. Virtual coach and telerehabilitation for Parkinson´s disease patients: vCare system

Author

Del Pino, Rocio, de Echevarría, Amaia Ortiz, Díez-Cirarda, Maria, Ustarroz-Aguirre, Iker, Caprino, Massimo, Liu, Jin, Gand, Kai, Schlieter, Hannes, Gabilondo, Iñigo, and Gómez-Esteban, Juan Carlos

Abstract

Aim: The vCare system is a virtual coach that involves physical and cognitive telerehabilitation and a daily life monitoring system. This pilot study aims to evaluate the vCare pilot test for Parkinson’s disease (PD) patients and to analyze the usability and the satisfaction level of patients and their quality of life (QoL). Subject and methods: Twenty PD patients were randomized, 10 patients into the vCare group focused on personalized home telerehabilitation [motor and cognitive rehabilitation (4 days/week for 4 months)], while the control group (10 patients) continued the clinical standard at the clinic. A pre-post clinical evaluation and a cost-utility study were performed. Results: Repeated measures ANOVA showed significant improvement in the PD vCare group compared to the control group (p&lt;.05). Specifically, the PD vCare group showed significant improvement in cognition (p=.016), and QoL dimensions of mobility (p=.008), self-care (p=.008), daily activities (p=.010) and pain/discomfort (p=.004) at post-treatment. vCare PD patients showed high adherence to the vCare system (90.5-100%). Costs per patient in the control group were higher (€5,108.26) than in the vCare group (€2,243.07). Conclusion: The PD vCare group significantly increase their QoL, cognition, motor symptoms, and daily life activities compared to the control group. Patients showed high adherence to the vCare coach, the care plan, rehabilitation, and devices. The vCare system seems to be an optimal and cost-effective tool for telerehabilitation in PD.

Published
2024
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49. H35 Cognitive and neuropsychiatric differences between asymptomatic and symptomatic carriers of Huntington´s disease

Author

Turuelo, Miriam, primary, Acera, Mariéa Aéngeles, additional, Fernaéndez-Valle, Tamara, additional, Somme, Johanne, additional, Ruiéz-Martiénez, Javier, additional, Pardina-Vilella, Lara, additional, Gabilondo, Andrea, additional, Tijero, Beatriz, additional, Ruiéz-Loépez, Marta, additional, Carmona, Mar, additional, Croitoru, Ioana, additional, Ayo, Naia, additional, Murueta-Goyena, Ane, additional, Gabilondo, Iñigo, additional, Gómez-Esteban, Juan Carlos, additional, and Del Pino, Rocio, additional

Published
2022
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