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Updated: Aug 11, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Cognitive impairment and depression predict mortality in medically ill older adults
C L Arfken1, P A Lichtenberg, M E Tancer
1Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, Michigan, USA. carfken@med.wayne.edu
Background:
Depression and cognitive impairment are common in medically ill older adults. Few studies, however, have investigated the roles of both in predicting mortality for medically ill older adults.
Methods:
We used a cohort of consecutive patients aged 60 or older admitted to a rehabilitation hospital (N = 667) of whom 455 completed a standardized protocol measuring cognition (Dementia Rating Scale), depression (Geriatric Depression Scale), and disabilities (Functional Independence Measure). Burden of medical illnesses was measured with the Charlson Index. Vital status was assessed one year later.
Results:
Those subjects who did not complete the screening were more likely to die (24% vs 17%; p = .02) during the one-year follow-up. Of those who completed the screening, male sex (odds ratio [OR] = 1.84), depression (mild OR = 1.64; moderate OR = 2.49), and more severe cognitive impairment (OR = 2.13) predicted mortality independent of age, medical illnesses, or disabilities. No interaction of cognitive impairment and depression was detected. In those subjects cognitively intact, moderate depression (OR = 4.95) and male sex (OR = 3.42) were independent risk factors for dying. In those subjects without depression, male sex (OR = 2.24) and elevated Charlson Index (OR = 1.42) predicted mortality.
Conclusions:
Depression and cognitive impairment are independent predictors of one-year mortality in this subgroup of medically ill older adults.
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