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Resumen de Trajectories of relative performance with 2 measures of global cognitive function

Mark A. Espeland, Jiu-Chiaun Chen, Julie Weitlauf, Kathleen M. Hayden, Stephen R. Rapp, Susan M. Resnick, Lorena García, Brad Cannell, Laura D. Baker, Bonnie C. Sachs, Hilary A. Tindle, Robert Wallace, Ramón Casanova, Women's Health Initiative

  • Objectives To examine whether trajectories of global cognitive function over time in studies that change assessment protocols may be modeled based on an individual's performance relative to others in the study cohort.

    Design Extended follow‐up of a cohort originally enrolled in a clinical trial of postmenopausal hormone therapy.

    Setting The Women's Health Initiative Memory Study switched from an in‐person interview with the Modified Mini‐Mental State Examination to a telephone‐based interview with the modified Telephone Interview for Cognitive Status to assess global cognitive function over long‐term follow‐up.

    Participants Women aged 75 to 92 (N=2,561).

    Measurements Annual cognitive assessments from participants, ranked according to age‐, race‐ and ethnicity‐adjusted performance levels, were used to identify distinct trajectories. Participants assigned to the resulting trajectories were compared for selected risk factor profiles.

    Results Our approach grouped participants into five trajectories according to relative cognitive performance over time. These groups differed significantly according to 3 known risk factors for cognitive decline—education level, apolipoprotein E‐ϵ4 genotype, and type 2 diabetes mellitus—and a biomarker based on brain structure that has been linked to cognitive decline and Alzheimer's disease. Participants with consistently low relative levels of cognitive function over time and those whose relative performance over time declined to these levels tended to have poorer risk factor profiles.

    Conclusion Longitudinal measures of an individual's relative performance on different assessment protocols for global cognitive function can be used to identify trajectories of change over time that appear to have internal validity with respect to known risk factors.


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