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Updated: Mar 30, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Trajectories of Neuropsychiatric Symptoms and Cognitive Decline in Mild Cognitive Impairment
Nicholas D David1, Feng Lin2, Anton P Porsteinsson1
1University of Rochester School of Medicine and Dentistry, Rochester, NY.
Objective:
To characterize the course of neuropsychiatric symptoms (NPS) in adults with mild cognitive impairment (MCI), and to examine baseline individual-level predictors and associated cognitive and functional outcomes.
Design:
A 2-year prospective cohort study.
Setting:
Multicenter clinical settings.
Participants:
Five hundred sixty individuals with MCI at baseline.
Measurements:
NPS severity (measured using Neuropsychiatric Inventory Questionnaire) and cognitive and functional outcomes were assessed at baseline and every 6 months thereafter. Potential individual-level predictors were collected at baseline.
Results:
Three latent classes of NPS courses were identified using growth mixture modeling: a stable class in which a low NPS burden remained relatively unchanged over time (N = 503, 89.8%); a worsened class in which an initially moderate NPS burden increased (N = 39, 7.0%); and an improved class in which an initially high NPS burden decreased (N = 18, 3.2%). There were no associations between class membership and baseline individual characteristics. Members of the worsened class were 1.74 times more likely to be diagnosed with incident Alzheimer disease (AD) than members of the stable class (95% confidence interval: 1.07-2.84). The worsened class also showed significantly more rapid declines in cognitive and functional outcomes than the stable class. Class membership did not predict rate of brain atrophy.
Conclusions:
Patients with MCI may experience different trajectories of NPS over time. Patients with worsening NPS may be at greater risk of developing AD and severe cognitive and functional impairment.
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