Diagnostics (Dec 2021)

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

DOI
https://doi.org/10.3390/diagnostics12010055
Journal volume & issue
Vol. 12, no. 1
p. 55

Abstract

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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.

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