2026-08-29T14:25:12Zhttps://repisalud.isciii.es/rest/oai/request

oai:repisalud.isciii.es:20.500.12105/145242025-04-01T12:15:35Zcom_20.500.12105_2052com_20.500.12105_2051col_20.500.12105_19608

00925njm 22002777a 4500 dc Mu, Jesse author Chaudhuri, Kallol Ray author Bielza, Concha author Pedro-Cuesta, Jesus de author Larrañaga, Pedro author Martínez-Martín, Pablo author 2017-09-20 Parkinson's disease is now considered a complex, multi-peptide, central, and peripheral nervous system disorder with considerable clinical heterogeneity. Non-motor symptoms play a key role in the trajectory of Parkinson's disease, from prodromal premotor to end stages. To understand the clinical heterogeneity of Parkinson's disease, this study used cluster analysis to search for subtypes from a large, multi-center, international, and well-characterized cohort of Parkinson's disease patients across all motor stages, using a combination of cardinal motor features (bradykinesia, rigidity, tremor, axial signs) and, for the first time, specific validated rater-based non-motor symptom scales. Two independent international cohort studies were used: (a) the validation study of the Non-Motor Symptoms Scale (n = 411) and (b) baseline data from the global Non-Motor International Longitudinal Study (n = 540). k-means cluster analyses were performed on the non-motor and motor domains (domains clustering) and the 30 individual non-motor symptoms alone (symptoms clustering), and hierarchical agglomerative clustering was performed to group symptoms together. Four clusters are identified from the domains clustering supporting previous studies: mild, non-motor dominant, motor-dominant, and severe. In addition, six new smaller clusters are identified from the symptoms clustering, each characterized by clinically-relevant non-motor symptoms. The clusters identified in this study present statistical confirmation of the increasingly important role of non-motor symptoms (NMS) in Parkinson's disease heterogeneity and take steps toward subtype-specific treatment packages. Front Aging Neurosci. 2017 Sep 20;9:301. 10.3389/fnagi.2017.00301 1663-4365 Frontiers in Aging Neuroscience 28979203 http://hdl.handle.net/20.500.12105/14524 Parkinson's disease Cluster analysis Motor symptoms Non-motor symptoms Subtypes Parkinson's Disease Subtypes Identified from Cluster Analysis of Motor and Non-motor Symptoms