Montreal Cognitive Assessment: Normative Data for Cognitively Healthy Swedish 80- to 94-Year-Olds

On the Clinimetrics of the Montreal Cognitive Assessment: Cutoff Analysis in Patients with Mild Cognitive Impairment due to Alzheimer's Disease

Background

In the era of disease-modifying therapies, empowering the clinical neuropsychologist's toolkit for timely identification of mild cognitive impairment (MCI) is crucial.

Objective

Here we examine the clinimetric properties of the Montreal Cognitive Assessment (MoCA) for the early diagnosis of MCI due to Alzheimer's disease (MCI-AD).

Methods

Data from 48 patients with MCI-AD and 47 healthy controls were retrospectively analyzed. Raw MoCA scores were corrected according to the conventional Nasreddine's 1-point correction and demographic adjustments derived from three normative studies. Optimal cutoffs were determined while previously established cutoffs were diagnostically reevaluated.

Results

The original Nasreddine's cutoff of 26 and normative cutoffs (non-parametric outer tolerance limit on the 5th percentile of demographically-adjusted score distributions) were overly imbalanced in terms of Sensitivity (Se) and Specificity (Sp). The optimal cutoff for Nasreddine's adjustment showed adequate clinimetric properties (≤23.50, Se = 0.75, Sp = 0.70). However, the optimal cutoff for Santangelo's adjustment (≤22.85, Se = 0.65, Sp = 0.87) proved to be the most effective for both screening and diagnostic purposes according to Larner's metrics. The results of post-probability analyses revealed that an individual testing positive using Santangelo's adjustment combined with a cutoff of 22.85 would have 84% post-test probability of receiving a diagnosis of MCI-AD (LR+ = 5.06).

Conclusions

We found a common (mal)practice of bypassing the applicability of normative cutoffs in diagnosis-oriented clinical practice. In this study, we identified optimal cutoffs for MoCA to be allocated in secondary care settings for supporting MCI-AD diagnosis. Methodological and psychometric issues are discussed.

The Montreal cognitive assessment: normative data from a large, population-based sample of Chinese healthy adults and validation for detecting vascular cognitive impairment

Background

The Montreal Cognitive Assessment (MoCA) is a valuable tool for detecting cognitive impairment, widely used in many countries. However, there is still a lack of large sample normative data and whose cut-off values for detecting cognitive impairment is considerable controversy.

Methods

The assessment conducted in this study utilizes the MoCA scale, specifically employing the Mandarin-8.1 version. This study recruited a total of 3,097 healthy adults aged over 20 years. We performed multiple linear regression analysis, incorporating age, gender, and education level as predictor variables, to examine their associations with the MoCA total score and subdomain scores. Subsequently, we established normative values stratified by age and education level. Finally, we included 242 patients with vascular cognitive impairment (VCI) and 137 controls with normal cognition, and determined the optimal cut-off value of VCI through ROC curves.

Results

The participants in this study exhibit a balanced gender distribution, with an average age of 54.46 years (SD = 14.38) and an average education period of 9.49 years (SD = 4.61). The study population demonstrates an average MoCA score of 23.25 points (SD = 4.82). The multiple linear regression analysis indicates that MoCA total score is influenced by age and education level, collectively accounting for 46.8% of the total variance. Higher age and lower education level are correlated with lower MoCA total scores. A score of 22 is the optimal cut-off value for diagnosing vascular cognitive impairment (VCI).

Conclusion

This study offered normative MoCA values specific to the Chinese adults. Furthermore, this study indicated that a score of 26 may not represent the most optimal cut-off value for VCI. And for detecting VCI, a score of 22 may be a better cut-off value.

Comparing Montreal Cognitive Assessment Performance in Parkinson's Disease Patients: Age- and Education-Adjusted Cutoffs vs. Machine Learning

OBJECTIVE

The Montreal Cognitive Assessment (MoCA) is recommended for general cognitive evaluation in Parkinson's disease (PD) patients. However, age- and education-adjusted cutoffs specifically for PD have not been developed or systematically validated across PD cohorts with diverse education levels.

METHODS

In this retrospective analysis, we utilized data from 1,293 Korean patients with PD whose cognitive diagnoses were determined through comprehensive neuropsychological assessments. Age- and education-adjusted cutoffs were formulated based on 1,202 patients with PD. To identify the optimal machine learning model, clinical parameters and MoCA domain scores from 416 patients with PD were used. Comparative analyses between machine learning.

METHODS

and different cutoff criteria were conducted on an additional 91 consecutive patients with PD.

RESULTS

The cutoffs for cognitive impairment decrease with increasing age within the same education level. Similarly, lower education levels within the same age group correspond to lower cutoffs. For individuals aged 60-80 years, cutoffs were set as follows: 25 or 24 years for those with more than 12 years of education, 23 or 22 years for 10-12 years, and 21 or 20 years for 7-9 years. Comparisons between age- and education-adjusted cutoffs and the machine learning method showed comparable accuracies. The cutoff method resulted in a higher sensitivity (0.8627), whereas machine learning yielded higher specificity (0.8250).

CONCLUSION

Both the age- and education-adjusted cutoff.

METHODS

and machine learning.

METHODS

demonstrated high effectiveness in detecting cognitive impairment in PD patients. This study highlights the necessity of tailored cutoffs and suggests the potential of machine learning to improve cognitive assessment in PD patients.

Cognitive impairment in adults under compulsory psychiatric care: association with psychotic symptoms and high-dose antipsychotics

BACKGROUND

There is limited evidence on the association between cognitive function, psychotic symptoms and doses of antipsychotics in adults under compulsory psychiatric care.

AIMS

We assessed (a) the degree of cognitive impairment in adults involuntarily hospitalised for compulsory psychiatric care and (b) correlation of Montreal Cognitive Assessment (MoCA) score with psychotic symptoms, polypharmacy and prescription of high-dose antipsychotics.

METHOD

This was a nationwide, cross-sectional study, conducted at the only referral state hospital for compulsory psychiatric care in Cyprus (December 2016-February 2018). Τhe MoCA was applied for the assessment of cognitive functioning. The Positive and Negative Syndrome Scale (PANSS) was applied for the assessment of psychotic symptoms.

RESULTS

The sample comprised 187 men and 116 women. The mean MoCA score was 22.09 (reported scale range (RSR): 3-30); the mean PANSS general symptoms subscale score was 49.60 (RSR = 41-162). The participants who reported positive psychiatric history (mean 21.71, s.d. 5.37), non-adherence to pharmacotherapy (mean 21.32, s.d. 5.56) and prescription of high-dose antipsychotics (with medication prescribed as needed: mean 21.31, s.d. 5.70; without medication prescribed as needed: mean 20.71, s.d. 5.78) had lower mean MoCA scores compared with those who reported negative psychiatric history (mean 23.42, s.d. 4.51; P = 0.017), adherence to pharmacotherapy (mean 23.10, s.d. 6.61; P = 0.003) and no prescription of high-dose antipsychotics (with medication prescribed as needed: mean 22.56, s.d. 4.90; without medication prescribed as needed: mean 22.60 s.d. 4.94; P = 0.045-0.005), respectively. Mean MoCA score was mildly and inversely associated with total PANSS score (r = -0.15, P = 0.03), PANSS general (r = -0.18, P = 0.002) and PANSS negative (r = -0.16, P = 0.005) symptoms subscales, respectively.

CONCLUSIONS

Our findings support the evaluation of cognitive functioning in adults under compulsory psychiatric care via the MoCA tool, with focus on those prescribed high-dose antipsychotics, with positive mental health history and non-adherence to pharmacotherapy.

Regression-Based Normative Data for the Montreal Cognitive Assessment (MoCA) and Its Memory Index Score (MoCA-MIS) for Individuals Aged 18–91

(1) Background: There is a need for a brief assessment of cognitive function, both in patient care and scientific research, for which the Montreal Cognitive Assessment (MoCA) is a psychometrically reliable and valid tool. However, fine-grained normative data allowing for adjustment for age, education, and/or sex are lacking, especially for its Memory Index Score (MIS). (2) Methods: A total of 820 healthy individuals aged 18–91 (366 men) completed the Dutch MoCA (version 7.1), of whom 182 also completed the cued recall and recognition memory subtests enabling calculation of the MIS. Regression-based normative data were computed for the MoCA Total Score and MIS, following the data-handling procedure of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI). (3) Results: Age, education level, and sex were significant predictors of the MoCA Total Score (Conditional R² = 0.4, Marginal R² = 0.12, restricted maximum likelihood (REML) criterion at convergence: 3470.1) and MIS (Marginal R² = 0.14, REML criterion at convergence: 682.8). Percentile distributions are presented that allow for age, education and sex adjustment for the MoCA Total Score and the MIS. (4) Conclusions: We present normative data covering the full adult life span that can be used for the screening for overall cognitive deficits and memory impairment, not only in older people with or people at risk of neurodegenerative disease, but also in younger individuals with acquired brain injury, neurological disease, or non-neurological medical conditions.