A parsimonious scoring and normative calculator for the Parkinson's disease mild cognitive impairment battery

• Published in: Clinical neuropsychologist Vol. 31; no. 6-7; pp. 1231 - 1247
• Main Authors: Bezdicek, Ondrej, Sulc, Zdenek, Nikolai, Tomas, Stepankova, Hana, Kopecek, Miloslav, Jech, Robert, Růžička, Evžen
• Format: Journal Article
• Language: English
• Published: England Routledge 03.10.2017
• Subjects: Adult; Aged; Aged, 80 and over; Clinical inference; Cognitive Dysfunction - diagnosis; Cohort Studies; Female; Humans; Male; Middle Aged; mild cognitive impairment; Neuropsychological Tests - standards; Parkinson Disease - psychology; Parkinson's disease; Psychometrics - methods; Clinical inference; mild cognitive impairment; Parkinson’s disease
• ISSN: 1385-4046; 1744-4144
• DOI: 10.1080/13854046.2017.1293161

Objective: The aim of the present study was to provide a regression-based calculator that takes premorbid functioning into account to detect subtle cognitive decline, as is often present in pre-dementia states, especially mild cognitive impairment in Parkinson's disease (PD-MCI). Method: We used demographic adjustments based on sex, age, and education of 699 normative participants that fulfilled exclusion criteria for ascertaining the diagnostic accuracy of the Movement Disorders Society PD-MCI battery at Level II. We examined the clinical validity of the battery on 36 PD patients. Results: An estimated z-score was calculated for any raw score based on different models that adjust for the demographic predictors of gender, age, and education, either concurrently, individually or without covariates. We provide a useful online z-score, SD, and percentile calculator that yields estimates of cognitive impairment based on normative sample for each of the ten neuropsychological tests and enables actuarial decision-making regarding its level and profile (number of domains impaired). We document the clinical utility and applicability of the calculator on a patient with PD-MCI and show the discriminative validity of all measures in the battery by comparing PD-MCI and PD without cognitive impairment with the highest area under the curve (.94) for Tower of London at −2 SD threshold. Conclusions: Our normative calculator introduces a practical web-based psychometric tool for the evaluation of PD-MCI status in clinical settings. We show the detection potential of each of ten measures included in the battery and delineate the diagnostic precision of the PD-MCI battery.