ArticleFrontiers in psychology2021
Cognitive Decline in Parkinson's Disease: A Subgroup of Extreme Decliners Revealed by a Data-Driven Analysis of Longitudinal Progression.
Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Role of Machine Learning in Cognitive Impairment in Parkinson Disease: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Systematic review of data-driven cognitive subtypes in Parkinson disease.European journal of neurology · 2022Pooled it
- Molecular neuroimaging of Parkinson's disease: association of motor and non-motor symptoms with synaptic density, dopaminergic and serotonergic systems.Neuroimage. Reports · 2026Article
- Predicting Cognition and Affective Changes in Newly Diagnosed Parkinson's Disease Through Longitudinal Data-Driven Clustering.Journal of geriatric psychiatry and neurology · 2026Article
- Cognitive profiles at presentation and subsequent cognitive decline and quality of life in Parkinson's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- A predictive model for longitudinal cognitive subtypes in Parkinson's disease.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Article
- Article
- Prediction of Cognitive Decline in Parkinson's Disease Using Clinical and DAT SPECT Imaging Features, and Hybrid Machine Learning Systems.Diagnostics (Basel, Switzerland) · 2023Article
- Profiling people with Parkinson's disease at risk of cognitive decline: Insights from PPMI and ICICLE-PD data.Alzheimer's & dementia (Amsterdam, Netherlands)Article
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Authors and funding
4 authors.
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Abstract
Cognitive impairment is an important symptom of Parkinson's disease (PD) and predicting future cognitive decline is crucial for clinical practice. Here, we aim to identify latent sub-groups of longitudinal trajectories of cognitive change in PD patients, and explore predictors of differences in cognitive change. Longitudinal cognitive performance data from 349 newly diagnosed PD patients and 145 healthy controls from the Parkinson Progression Marker Initiative were modeled using a multivariate latent class linear mixed model. Resultant latent classes were compared on a number of baseline demographics and clinical variables, as well as cerebrospinal fluid (CSF) biomarkers and striatal dopamine transporter (DAT) density markers of neuropathology. Trajectories of cognitive change in PD were best described by two latent classes. A large subgroup (90%), which showed a subtle impairment in cognitive performance compared to controls but remained stable over the course of the study, and a small subgroup (10%) which rapidly declined in all cognitive performance measures. Rapid decliners did not differ significantly from the larger group in terms of disease duration, severity, or motor symptoms at baseline. However, rapid decliners had lower CSF amyloidß42 levels, a higher prevalence of sleep disorder and pronounced loss of caudate DAT density at baseline. These data suggest the existence of a distinct minority sub-type of PD in which rapid cognitive change in PD can occur uncoupled from motor symptoms or disease severity, likely reflecting early pathological change that extends from motor areas of the striatum into associative compartments and cortex.
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