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Updated: Jul 3, 2026
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The MMSE is not an adequate screening cognitive instrument in studies of late-life depression
Tarek K Rajji1, Dielle Miranda, Benoit H Mulsant
1Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada M6J 1H4.
Background:
The Mini Mental State Examination (MMSE) is frequently used to assess cognition in studies of late-life depression (LLD). However, its sensitivity and specificity in this population are largely unknown. We undertook an analysis of subjects with LLD and hypothesized that: (1) at the traditional cutoff of 24, the MMSE would have low sensitivity in the detection of cognitive impairment; (2) increasing the cutoff score would improve this sensitivity at the expense of a minimal reduction in specificity.
Methods:
We analyzed the MMSE scores of 447 non-demented subjects with LLD using the Dementia Rating Scale (DRS) as the gold standard for cognitive function.
Results:
Using the DRS raw total cutoff of 132 as the "gold standard", the MMSE at a cutoff of 24 has a sensitivity of 8.0% and a specificity of 99.4% in detecting "cognitively impaired" depressed elders. A receiver operating characteristic curve demonstrates that with an MMSE cutoff of 27 instead of 24, its sensitivity more than quadruples and increases to 37.5% while its specificity decreases minimally from 99.4% to 91.3%.
Conclusions:
In our sample almost all of those classified as cognitively impaired by the DRS are mislabelled as "cognitively intact" by the MMSE. By using a higher cutoff score, the sensitivity can be increased with a minimal reduction in specificity. Our findings have significant implications for those who study or treat persons with LLD or other neuropsychiatric disorders.
