A qualitative approach to extract diagnostic patterns of cognitive impairment in Parkinson's disease.

Abstract

Parkinson's disease (PD) is the second-most diagnosed age-related neurodegenerative disorder globally. PD pathology causes dysregulation of motor movement and for many, mild cognitive impairment (PD-MCI). The most recommended global screening exam to detect PD-MCI is the Montreal Cognitive Assessment© (MoCA). Traditionally, the MoCA is scored according to guidelines and compared against a standardized cutoff, but clinical professionals additionally draw upon their observations of the patient's performance to determine the score. To better understand how clinicians use the MoCA in real-world clinical settings, we employed the qualitative descriptive approach to identify performance patterns professionals utilize to assess the cognitive health of a person with PD. We curated retrospective data from nine people with PD-MCI to PD-Dementia. Each patient had one completed MoCA exam and one neuropsychological report containing health data. The assessments were organized into three groups of three and used in semi-structured interviews with six clinical professionals to gather at minimum two clinical opinions for each. Three coders distilled, based on consensus, three clinically meaningful patterns from the interviews composed of features emphasized as vital by the interviewees for determining a person's cognitive health. The derived features were from a patient's performance on sections of the MoCA exam, sociodemographic and health data from the neuropsychological report, and dependent relationships between the assessments. Our study leveraged the popular MoCA exam to explore its real-world clinical use. Extracting these patterns clinicians recognized provides deeper insights into how they interpret cognitive health creating a blueprint for future efforts to tailor the exam for detecting cognitive impairment in people with PD.