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Updated: Jun 18, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Validation of the telephone interview for cognitive status-modified in subjects with normal cognition, mild cognitive
David S Knopman1, Rosebud O Roberts, Yonas E Geda
1Department of Neurology, College of Medicine, Mayo Clinic, Rochester, MN 55905, USA. knopman@mayo.edu
Background:
The telephone assessment of cognitive functions may reduce the cost and burden of epidemiological studies.
Methods:
We validated the Telephone Interview for Cognitive Status-modified (TICS-m) using an extensive in-person assessment as the standard for comparison. Clinical diagnoses of normal cognition, mild cognitive impairment (MCI), or dementia were established by consensus of physician, nurse, and neuropsychological assessments.
Results:
The extensive in-person assessment classified 83 persons with normal cognition, 42 persons with MCI, and 42 persons with dementia. There was considerable overlap in TICS-m scores among the three groups. Receiver operating characteristic curves identified < or = 31 as the optimal cutoff score to separate subjects with MCI from subjects with normal cognition (sensitivity = 71.4%; subjects with dementia excluded), and < or = 27 to separate subjects with dementia from subjects with MCI (sensitivity = 69.0%; subjects with normal cognition excluded). The TICS-m performed well when subjects with MCI were pooled either with subjects with dementia (sensitivity = 83.3%) or with subjects with normal cognition (sensitivity = 83.3%).
Conclusions:
Although the TICS-m performed well when using a dichotomous classification of cognitive status, it performed only fairly in separating MCI from either normal cognition or dementia. The TICS-m should not be used as a free-standing tool to identify subjects with MCI, and it should be used with caution as a tool to detect dementia.
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