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Updated: Oct 14, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Dementia screening in psychiatric consultation for elderly patients in a general hospital]
F M Reischies1, A Diefenbacher
1Psychiatrische Klinik und Poliklinik, Freien Universität Berlin. reischie@zedat.fu-berlin.de
Background:
Elderly patients on medical-surgical wards in general hospitals often suffer from cognitive dysfunction that hampers medical treatment of somatic diseases. Symptoms of cognitive dysfunction may not be recognized adequately by non-psychiatric physicians.
Patients And Method:
We studied the usefulness of a short screening instrument for cognitive dysfunctions (short mini mental state test) in a consecutive sample of 222 psychiatric consultation liaison patients older than 60 years of age. Normative data for the screening test from an epidemiological sample, the Berlin Aging Study, are given and compared with the consultation sample.
Results:
Mild to moderate deficits in cognitive functions were found in 32% of patients, severe deficits indicating dementia- or delirium syndromes were found in 17.7%. Applying the cut off 4/5, 88.9% correct classifications of dementia patients were obtained. The item analysis demonstrates significant differences with respect to the age-matched population sample for the orientation items, the 2nd and subsequent subtractions of the serial seven task and, to a lesser degree, the memory items.
Conclusion:
A standardized assessment of the 15 items of the SMMS represents a practical, reliable and valid screening for relevant cognitive deficits, which may also serve as documentation of the time course especially in acute organic-psychiatric syndromes.
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