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Updated: Apr 18, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Mixed membership trajectory models of cognitive impairment in the multicenter AIDS cohort study
Samantha A Molsberry1, Fabrizio Lecci, Lawrence Kingsley
1aDepartment of Psychiatry, University of Pittsburgh bDepartment of Statistics, Carnegie Mellon University, Pittsburgh cInfectious Diseases and Microbiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania dDepartment of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland eAIDS Healthcare Foundation, Los Angeles fDepartment of Neurology, University of California Los Angeles, California gDepartment of Psychiatry, Rush University School of Medicine, Chicago, Illinois hDepartment of Psychiatry, University of California Los Angeles, California iDepartment of Psychiatry jDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland kDepartment of Radiology Northwestern University, Evanston, Illinois lDepartment of Neurology mDepartment of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Objective:
The longitudinal trajectories that individuals may take from a state of normal cognition to HIV-associated dementia are unknown. We applied a novel statistical methodology to identify trajectories to cognitive impairment, and factors that affected the 'closeness' of an individual to one of the canonical trajectories.
Design:
The Multicenter AIDS Cohort Study (MACS) is a four-site longitudinal study of the natural and treated history of HIV disease among gay and bisexual men.
Methods:
Using data from 3892 men (both HIV-infected and HIV-uninfected) enrolled in the neuropsychology substudy of the MACS, a Mixed Membership Trajectory Model (MMTM) was applied to capture the pathways from normal cognitive function to mild impairment to severe impairment. MMTMs allow the data to identify canonical pathways and to model the effects of risk factors on an individual's 'closeness' to these trajectories.
Results:
First, we identified three distinct trajectories to cognitive impairment: 'normal aging' (low probability of mild impairment until age 60); 'premature aging' (mild impairment starting at age 45-50); and 'unhealthy' (mild impairment in 20s and 30s) profiles. Second, clinically defined AIDS, and not simply HIV disease, was associated with closeness to the premature aging trajectory, and, third, hepatitis-C infection, depression, race, recruitment cohort and confounding conditions all affected individual's closeness to these trajectories.
Conclusion:
These results provide new insight into the natural history of cognitive dysfunction in HIV disease and provide evidence for a potential difference in the pathophysiology of the development of cognitive impairment based on trajectories to impairment.
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