Accuracy of Machine Learning Using the Montreal Cognitive Assessment for the Diagnosis of Cognitive Impairment in Parkinson's Disease.

ABSTRACT:

Objective

The Montreal Cognitive Assessment (MoCA) is recommended for assessing general cognition in Parkinson's disease (PD). Several cutoffs of MoCA scores for diagnosing PD with cognitive impairment (PD-CI) have been proposed, with varying sensitivity and specificity. This study investigated the utility of machine learning algorithms using MoCA cognitive domain scores for improving diagnostic performance for PD-CI.

Methods

In total, 2,069 MoCA results were obtained from 397 patients with PD enrolled in the Parkinson's Progression Markers Initiative database with a diagnosis of cognitive status based on comprehensive neuropsychological assessments. Using the same number of MoCA results randomly sampled from patients with PD with normal cognition or PD-CI, discriminant vali

SUBMITTER: Jeon J 

PROVIDER: S-EPMC9171310 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature