Adaptation and Validation of Addenbrooke's Cognitive Examination-III in Bengali for Screening MCI and Dementia
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Updated: Sep 6, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Bidisha Bhattacharyya1, Ruchira Mukherjee1, Adreesh Mukherjee1
1Department of Neurology, Bangur Institute of Neurosciences, Institute of Post Graduate Medical Education & Research, Kolkata, India.
Objective:
Bengali, the 6th most spoken language globally with 268 million speakers, demands a culturally appropriate tool for screening any cognitive compromise in this population. Addenbrooke Cognitive Examination-III (ACE-III) is a standardized tool used for screening and/or diagnostic purpose worldwide. The aim of the present study was to adapt and validate ACE-III into Bengali language.
Methods:
The ACE-III UK Version A (2012) was adapted with linguistically and culturally appropriate items and validated on Bengali speakers. The participants consisted of 40 dementia and 22 Mild Cognitive Impairment (MCI) patients and 120 healthy-controls. Reliability and validity were examined. Discriminant function analysis was done. Sensitivity and specificity were evaluated and optimum cut-offs were established for MCI and dementia.
Results:
Both sensitivity and specificity of ACE-III-Bengali of identifying dementia was 1; sensitivity for MCI ranged from 0.83 to 1, specificity from 0.76 to 1. Discriminant function analysis showed a significant difference in all domains of ACE-III-Bengali between healthy individuals and persons with neurocognitive impairment. Separate optimum ACE-III-Bengali cut-off scores were established according to level of education. For low education (
Conclusion:
The ACE-III-Bengali is found to have high diagnostic accuracy in identifying dementia and MCI in the Bengali population.
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