Objective: To establish psychometric properties of the Montreal Cognitive Assessment (MoCA) with respect to detecting mild cognitive impairment in Parkinson's disease (PD-MCI). Introduction: MCI is considered a transitional stage between normal cognitive functioning and dementia.
The MoCA has recently been recommended as one of the standard tools for the diagnosis of PD-MCI. However, its detection potential in the Czech population has not been demonstrated.
Methods: A sample of 80 patients with PD was administered the MoCA and a neuropsychological battery with criteria operationalized for MCI-deficits. Thirty nine of these patients (PD-MCI sample) were age and education-matched to a control sample (CS).
ROC analysis was used to ascertain classification statistics (discriminative validity) of the MoCA as a diagnostic instrument. Results: The MoCA total score was significantly different between PD-MCI and CS (p = 0.006).
Delayed recall was the most differentiating MoCA subscore (p < 0.001). The 28/29 scores were identified as an optimal screening MoCA cut-off to discriminate PD-MCI from CS was (sensitivity = 0.90, specificity = 0.32; positive and negative predictive value = 0.57 and 0.76, respectively).
We constructed a regression equation based on a large control sample of the Czech population (n = 268) to estimate the MoCA's age and education-specific performance more accurately. Conclusion: Despite the group differences between PD-MCI and CS, our results show that MoCA has an unsatisfactory detection potential for an individual diagnosis of PD-MCI.
A comprehensive neuropsychological battery is thus recommendable. Key words: validity - mild cognitive impairment - diagnostic criteria - Parkinson's disease - Montreal Cognitive Assessment The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.
The Editorial Board declares that the manu-script met the ICMJE "uniform requirements" for biomedical papers.