MNCD: A New Tool for Classifying Parkinson’s Disease in Daily Clinical Practice
Diego Santos García,
María Álvarez Sauco,
Matilde Calopa,
Fátima Carrillo,
Francisco Escamilla Sevilla,
Eric Freire,
Rocío García Ramos,
Jaime Kulisevsky,
Juan Carlos Gómez Esteban,
Inés Legarda,
María Rosario Isabel Luquín,
Juan Carlos Martínez Castrillo,
Pablo Martínez-Martin,
Irene Martínez-Torres,
Pablo Mir,
Ángel Sesar Ignacio
Affiliations
Diego Santos García
Unidad de Trastornos de Movimiento, Servicio de Neurología, CHUAC, Complejo Hospitalario Universitario de A Coruña, 15009 A Coruña, Spain
María Álvarez Sauco
Departamento de Neurología, Hospital General Universitario de Elche, 03203 Elche, Spain
Matilde Calopa
Unidad de Trastornos del Movimiento, Servicio de Neurología, Hospital Universitari de Bellvitge, 08907 Barcelona, Spain
Fátima Carrillo
Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío, 41013 Sevilla, Spain
Francisco Escamilla Sevilla
Unidad de Trastornos del Movimiento, Servicio de Neurología, Hospital Universitario Virgen de las Nieves, Instituto de Investigación Biosanitaria (ibs.Granada), 18013 Granada, Spain
Eric Freire
Departamento de Neurología, Hospital General Universitario de Elche, 03203 Elche, Spain
Rocío García Ramos
Instituto de Investigación Sanitaria San Carlos (IdISCC), Hospital Clínico San Carlos, 28040 Madrid, Spain
Jaime Kulisevsky
Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas CIBERNED, 28031 Madrid, Spain
Juan Carlos Gómez Esteban
Servicio de Neurología, Hospital Cruces, 48903 Bilbao, Spain
Inés Legarda
Hospital Universitario Son Espases, 07120 Palma, Spain
María Rosario Isabel Luquín
Departamento de Neurología, Clínica Universidad de Navarra, Instituto de Investigación Sanitaria de Navarra, 31008 Pamplona, Spain
Juan Carlos Martínez Castrillo
Servicio de Neurología, Hospital Ramón y Cajal, 28034 Madrid, Spain
Pablo Martínez-Martin
Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas CIBERNED, 28031 Madrid, Spain
Irene Martínez-Torres
Unidad de Trastornos del Movimiento, Servicio de Neurología, Hospital Universitario y Politècnico La Fe, 46026 Valencia, Spain
Pablo Mir
Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío, 41013 Sevilla, Spain
Ángel Sesar Ignacio
Unidad de Trastornos del Movimiento, Servicio de Neurología, CHUS (Complejo Hospitalario Universitario de Santiago de Compostela), 15706 A Coruña, Spain
Background and objective: Parkinson’s disease (PD) is a clinically heterogeneous disorder in which the symptoms and prognosis can be very different among patients. We propose a new simple classification to identify key symptoms and staging in PD. Patients and Methods: Sixteen movement disorders specialists from Spain participated in this project. The classification was consensually approved after a discussion and review process from June to October 2021. The TNM classification and the National Institutes of Health Stroke Scale (NIHSS) were considered as models in the design. Results: The classification was named MNCD and included 4 major axes: (1) motor symptoms; (2) non-motor symptoms; (3) cognition; (4) dependency for activities of daily living (ADL). Motor axis included 4 sub-axes: (1) motor fluctuations; (2) dyskinesia; (3) axial symptoms; (4) tremor. Four other sub-axes were included in the non-motor axis: (1) neuropsychiatric symptoms; (2) autonomic dysfunction; (3) sleep disturbances and fatigue; (4) pain and sensory disorders. According to the MNCD, 5 stages were considered, from stage 1 (no disabling motor or non-motor symptoms with normal cognition and independency for ADL) to 5 (dementia and dependency for basic ADL). Conclusions: A new simple classification of PD is proposed. The MNCD classification includes 4 major axes and 5 stages to identify key symptoms and monitor the evolution of the disease in patients with PD. It is necessary to apply this proof of concept in a properly designed study.