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Updated: Jan 27, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Global & Community Health: Brief in-hospital cognitive screening anticipates complex admissions and may detect
David Bissig1, Charles S DeCarli2
1From the Department of Neurology (D.B.), Oregon Health & Science University, Portland; and Department of Neurology (C.S.D.), University of California-Davis. bissig@ohsu.edu.
Objective:
With the long-term goal of improving community health by screening for dementia, we tested the utility of integrating the Six-Item Screener (SIS) into our emergency department neurology consultations.
Methods:
In this cross-sectional observational study, we measured SIS performance within 24 hours of hospital arrival in 100 consecutive English-speaking patients aged ≥45 years. Performance was compared to patient age, previously charted cognitive impairment, and proxies for in-hospital complexity: whether or not a patient was admitted to the hospital and the number of medical studies ordered.
Results:
Those with poor SIS performance were older (p = 0.02) and more likely to have previously charted cognitive impairment (p < 0.01; sensitivity 86%, specificity 77%). Poor performers were more likely to be admitted to the hospital (p = 0.04; odds ratio 3.6) and were subjected to more tests once admitted (p < 0.01), relationships that persisted after accounting for age and history of cognitive impairment.
Conclusions:
Poor performance on the SIS was associated with previously charted cognitive impairment, justifying future study of its ability to detect unrecognized dementia cases. Until then, its ability to inexpensively anticipate medically complex hospital admissions motivates broader emergency department use of the SIS.
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