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Updated: Aug 8, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Management of multimorbidity in the midst of cognitive decline through clinical decision-support software
Mark C Zelek1, John Q Walker1, Marwan N Sabbagh2
1uMETHOD Health Raleigh North Carolina USA.
Introduction:
Multimorbidity - the coexistence of multiple chronic conditions - is common among older adults with cognitive impairment but is rarely addressed in an integrated manner.
Methods:
We analyzed 17,915 adults aged 55 to 84 years (8997 receiving uMETHOD clinical decision-support care plans and 8918 from the National Health and Nutrition Examination Survey). The mean age was 69.0 years (SD 7.65; 95% CI: 68.86 to 69.1). Multimorbidity was quantified from diagnoses, labs, medications, vitals, and platform-inferred conditions. Associations with cognitive impairment were modeled using age- and sex-adjusted logistic regression.
Results:
Cognitive impairment was reported in 25.91% of participants (97.5% with ≥2 conditions); each additional condition was associated with higher odds (odds ratio: 1.069; 95% CI: 1.061 to 1.077; p < 0.0001). Prominent clusters included vascular-metabolic disorders and micronutrient deficiencies.
Discussion:
Cognitive vulnerability rises stepwise with disease burden. Precision, multimorbidity-aware decision support that integrates multidomain data can align cognitive and systemic care in real-world practice.
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