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Disentangling the PIGD classification for the prediction of cognitive impairment in de novo Parkinson's disease.

Authors :
Urso D
Leta V
Batzu L
Yousaf T
Farrell C
van Wamelen DJ
Ray Chaudhuri K
Source :
Journal of neurology [J Neurol] 2022 Mar; Vol. 269 (3), pp. 1566-1573. Date of Electronic Publication: 2021 Aug 02.
Publication Year :
2022

Abstract

Background: Postural Instability and Gait difficulties (PIGD) subtype has been associated with worse cognitive performance in Parkinson's disease (PD).<br />Objective: To investigate whether PIGD subtype classification or PIGD-related clinical features predict the development of cognitive decline in de novo PD patients.<br />Methods: Data from 422 PD patients with de novo PD were obtained from the PPMI database. At follow-up (up to 6 years), patients were categorized as having cognitive impairment or not. Multivariate Cox survival analysis was carried out including motor subtype and individual MDS-UPDRS items defining PIGD phenotype as predictors. Previously validated clinical predictors of cognitive impairment were included in the model as covariates. Occurrence of cognitive impairment at follow-up was used as the time-to-event and Kaplan-Meier curve was generated.<br />Results: At baseline, 76 patients were classified as PIGD, 299 tremor-dominant and 47 as indeterminate. Development of cognitive impairment was not associated with PIGD subtype (p = 0.252). When individual MDS-UPDRS items were interrogated in the model, postural instability proved to be an independent predictor of cognitive impairment (HR = 2.045; 95%CI: 1.068-3.918; p = 0.031), while gait difficulties were not associated with cognitive decline (p = 0.870).<br />Conclusions: Our findings suggest that postural instability, as assessed by MDS-UPDRS III, may serve as a possible indicator of the risk of developing cognitive impairment in de novo PD patients rather than the PIGD phenotype.<br /> (© 2021. The Author(s).)

Details

Language :
English
ISSN :
1432-1459
Volume :
269
Issue :
3
Database :
MEDLINE
Journal :
Journal of neurology
Publication Type :
Academic Journal
Accession number :
34338858
Full Text :
https://doi.org/10.1007/s00415-021-10730-3