Sensitivity and specificity of the Montreal cognitive assessment using U.S. National alzheimer coordinating centre uniform data set: a retrospective analysis of 16,309 participants.

Background: Neurodegenerative diseases (NDDs), like Alzheimer's disease, are characterized by progressive cognitive decline, with limited effective treatments available. Several screening tools are available for diagnosing various types of dementia, including the Montreal Cognitive Assessment (MoCA), the Mini-Mental State Examination (MMSE), and the Dementia Rating Scale (DRS).

Objective: This study aims to evaluate the sensitivity and specificity of MoCA to determine its suitability as a screening tool.

Methods: This study analyzed data from participants aged 55 and older, recruited from U.S. Alzheimer's Disease Research Centers (ADRCs), using a National Alzheimer Coordinating Center Uniformed Data Set (NACC-UDS). Participants were classified based on patient records into demented and non-demented groups, with the non-demented group further categorized into those with normal cognition and cognitive impairment (CI). This analysis examines the correlation between these classifications and MoCA scores.

Results: This study utilized an initial dataset of 188,700 participant records from NACC. After applying inclusion criteria, 16,309 participants were included. The participants had complete diagnostic information, clinician-conducted cognitive assessments, and MoCA scores. The participants were categorized into three groups: 7,624 with no cognitive impairment (NoCI), 4,893 with CI, and 3,792 with dementia. This study focused on MoCA scores, revealing significant differences among diagnostic groups. ROC analysis demonstrated the MoCA's strong diagnostic capability, with AUC values significantly above 0.5 (P <.001). Sensitivity and specificity were calculated in at the literature-recommended cutoff scores of 26 and 21, while the optimal cutoff scores were identified as (< 24) for detecting MCI and (< 21) for dementia based on the Youden index in reference to individuals with no cognitive impairment. Although PPV was generally low, the high NPV across comparisons underscores the MoCA's effectiveness in ruling out cognitive impairment.

Conclusion: The study confirms MoCA as an effective tool for detecting dementia, showing 83% sensitivity and 82% specificity at a cutoff value of 21. With a high NPV of 94%, MoCA is particularly reliable for ruling out dementia. Its ability to detect MCI is moderate, with a sensitivity of 77.3% at cutoff of 24 among normal population.