Background:The Montreal Cognitive Assessment (MoCA) is used to evaluate multiple cognitive domains in elderly individuals. However, it is influenced by demographic characteristics that have yet to be adequately considered.Objective:The aim of our study was to investigate the effects of age, education, and sex on the MoCA total score and to provide demographically adjusted normative values for a German-speaking population.Methods:Subjects were recruited from a registry of healthy volunteers. Cognitive health was defined using the Mini-Mental State Examination (score ≥27/30 points) and the Consortium to Establish a Registry for Alzheimer’s Disease-Neuropsychological Assessment Battery (total score ≥85.9 points). Participants were assessed with the German version of the MoCA. Normative values were developed based on regression analysis. Covariates were chosen using the Predicted Residual Sums of Squares approach.Results:The final sample consisted of 283 participants (155 women, 128 men; mean (SD) age = 73.8 (5.2) years; education = 13.6 (2.9) years). Thirty-one percent of participants scored below the original cut-off (<26/30 points). The MoCA total score was best predicted by a regression model with age, education, and sex as covariates. Older age, lower education, and male sex were associated with a lower MoCA total score (p < 0.001).Conclusion:We developed a formula to provide demographically adjusted standard scores for the MoCA in a German-speaking population. A comparison with other MoCA normative studies revealed considerable differences with respect to selection of volunteers and methods used to establish normative data.

Background: The Montreal Cognitive Assessment (MoCA) has good sensitivity for mild cognitive impairment, but specificity is low when the original cutoff (25/26) is used. We aim to revise the cutoff on the German MoCA for its use in clinical routine. Methods: Data were analyzed from 496 Memory Clinic outpatients (447 individuals with a neurocognitive disorder; 49 with cognitive normal findings) and from 283 normal controls. Cutoffs were identified based on (a) Youden's index and (b) the 10th percentile of the control group. Results: A cutoff of 23/24 on the MoCA had better correct classification rates than the MMSE and the original MoCA cutoff. Compared to the original MoCA cutoff , the cutoff of 23/24 points had higher specificity (92% vs 63%), but lower sensitivity (65% vs 86%). Introducing two separate cutoffs increased diagnostic accuracies with 92% specificity (23/24 points) and 91% sensitivity (26/27 points). Scores between these two cutoffs require further examinations. Conclusions: Using two separate cutoffs for the MoCA combined with scores in an indecisive area enhances the accuracy of cognitive screening.

Background Evaluating the discrepancies between patient‐reported measures and clinician examination has implications for formulating individual treatment regimens. Objective This study investigated the association between health outcomes and level of self‐reported motor‐related function impairment relative to clinician‐examined motor signs. Methods Recently diagnosed PD patients were evaluated using the Parkinson's Progression Marker Initiative (PPMI, N = 420) and the PASADENA phase II clinical trial (N = 316). We calculated the average normalized difference between each participant's part II and III MDS‐UPDRS (Movement Disorder Society Unified Parkinson's Disease Rating Scale) scores. Individuals with score differences <25th or >75th percentiles were labeled as low‐ and high‐self‐reporters, respectively (those between ranges were labeled intermediate‐self‐reporters). We compared a wide range of clinical/biomarker readouts among these three groups, using Kruskal–Wallis nonparametric and Pearson's χ2 tests. Spearman's correlations were tested for associations between MDS‐UPDRS subscales. Results In both cohorts, high‐self‐reporters reported the largest impairment/symptom experience for most motor and nonmotor patient‐reported variables. By contrast, these high‐self‐reporters were similar to or less impaired on clinician‐examined and biomarker measures. Patient‐reported nonmotor symptoms on MDS‐UPDRS part IB showed the strongest positive correlation with self‐reported motor‐related impairment (PPMI rs = 0.54, PASADENA rs = 0.52). This correlation was numerically stronger than the part II and clinician‐examined MDS‐UPDRS part III correlation (PPMI rs = 0.38, PASADENA rs = 0.28). Conclusion Self‐reported motor‐related impairments reflect not only motor signs/symptoms but also other self‐reported nonmotor measures. This may indicate (1) a direct impact of nonmotor symptoms on motor‐related functioning and/or (2) the existence of general response tendencies in how patients self‐rate symptoms. Our findings suggest further investigation into the suitability of MDS‐UPDRS II to assess motor‐related impairments. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society