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MNCD: A New Tool for Classifying Parkinson's Disease in Daily Clinical Practice.
- Source :
-
Diagnostics (Basel, Switzerland) [Diagnostics (Basel)] 2021 Dec 28; Vol. 12 (1). Date of Electronic Publication: 2021 Dec 28. - Publication Year :
- 2021
-
Abstract
- 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.
Details
- Language :
- English
- ISSN :
- 2075-4418
- Volume :
- 12
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Diagnostics (Basel, Switzerland)
- Publication Type :
- Academic Journal
- Accession number :
- 35054222
- Full Text :
- https://doi.org/10.3390/diagnostics12010055