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Updated: Jun 30, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Validity of Montreal Cognitive Assessment to Detect Cognitive Impairment in Individuals with Type 2 Diabetes
Anu Gupta1, Alpesh Goyal2, Roopa Rajan1
1Department of Neurology, All India Institute of Medical Sciences, New Delhi, 110029, India.
Introduction:
Guidelines recommend screening older people (> 60-65 years) with type 2 diabetes (T2D) for cognitive impairment, as it has implications in the management of diabetes. The Montreal Cognitive Assessment (MoCA) is a sensitive test for the detection of mild cognitive impairment (MCI) in the general population, but its validity in T2D has not been established.
Methods:
We administered MoCA to patients with T2D (age ≥ 60 years) and controls (no T2D), along with a culturally validated neuropsychological battery and functional activity questionnaire. MCI was defined as performance in one or more cognitive domains ≥ 1.0 SD below the control group (on two tests representing a cognitive domain), with preserved functional activities. The discriminant validity of MoCA for the diagnosis of MCI at different cut-offs was ascertained.
Results:
We enrolled 267 patients with T2D and 120 controls; 39% of the participants with T2D met the diagnostic criteria for MCI on detailed neuropsychological testing. At the recommended cut-off on MoCA (< 26), the sensitivity (94.2%) was high, but the specificity was quite low (29.5%). The cut-off score of < 23 showed an optimal trade-off between sensitivity (69.2%), specificity (71.8%), and diagnostic accuracy (70.8%). The cut-off of < 21 exhibited the highest diagnostic accuracy (74.9%) with an excellent specificity (91.4%), a good positive and negative predictive value (78.5% and 73.7%, respectively).
Conclusions:
The recommended screening cut-off point on MoCA of < 26 has a suboptimal specificity and may increase the referral burden in memory clinics. A lower cut-off of < 21 on MoCA maximizes the diagnostic accuracy. Interactive Visual Abstract available for this article.
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