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Refining the Parkinson's Disease Risk Estimator for Decline In Cognition Tool (PREDICT).

Tara C Carlisle1,2, Lauren B Gunn-Sandell3, William L Lippitt3

  • 1Department of Neurology, Behavioral Neurology Section, University of Colorado School of Medicine, Aurora, Colorado.

Cognitive and Behavioral Neurology : Official Journal of the Society for Behavioral and Cognitive Neurology
|March 25, 2026
PubMed
Summary

Excessive daytime sleepiness and moderate-severe motor symptoms are key predictors of cognitive decline in Parkinson's disease (PD). These factors, along with education level, can help estimate future cognitive impairment risk in PD patients.

Keywords:
Parkinson’s diseasecognitive declinedementiaeducational statusrisk factorssleep

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Area of Science:

  • Neurology
  • Cognitive Science
  • Biostatistics

Background:

  • Cognitive decline is a common complication in Parkinson's disease (PD).
  • Current clinical tools for predicting cognitive decline risk in PD are limited.
  • There is a need for accessible methods to identify individuals at high risk for cognitive impairment in PD.

Purpose of the Study:

  • To refine a predictive tool for cognitive decline in Parkinson's disease.
  • To identify potentially modifiable risk factors associated with cognitive decline in PD.
  • To develop and validate the Parkinson's Disease Risk Estimator for Decline In Cognition Tool (PREDICT).

Main Methods:

  • Utilized neuropsychological scores from the Parkinson's Progression Markers Initiative (PPMI) de novo PD cohort.
  • Calculated a composite cognitive score (CCS) and identified cognitive decline (PD-Decline) based on a ≥0.5 SD decrease in CCS.
  • Employed conditional linear mixed modeling to handle dropouts and logistic regression to identify risk factors for PD-Decline, developing the PREDICT scoring system.

Main Results:

  • Excessive daytime sleepiness (OR=2.8), moderate-severe motor symptoms (OR=2.6), and fewer years of education (OR=2.2) were significantly associated with increased odds of PD-Decline.
  • The PREDICT scoring system ranged from 0 to 3.5.
  • The developed PREDICT tool demonstrated average bootstrap sensitivity of 59.9% and specificity of 43.5%.

Conclusions:

  • Excessive daytime sleepiness and moderate-to-severe motor symptoms are significant predictors of cognitive decline in Parkinson's disease.
  • These identified factors represent potentially modifiable targets for intervention.
  • The PREDICT tool shows promise for personalized risk assessment and potential risk reduction strategies in PD management.