Journal of Alzheimer's disease : JAD · 2020
A Latent Transition Analysis Model to Assess Change in Cognitive States over Three Occasions: Results from the Rush Memory and Aging Project.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Zammit Andrea R, Bennett David A, Hall Charles B, Lipton Richard B, Katz Mindy J, Muniz-Terrera Graciela
Аннотация
BACKGROUND: Conceptualizing cognitive aging as a step-sequential process is useful in identifying particular stages of cognitive function and impairment.
OBJECTIVE: We applied latent transition analysis (LTA) to determine 1) whether the underlying structure of cognitive profiles found at every measurement occasion are uniform across three waves of assessment, 2) whether class-instability is predictive of distal outcomes, and 3) whether class-reversions from impaired to non-impaired using latent modelling is lower than when using clinical criteria of mild cognitive impairment (MCI).
METHODS: A mover-stayer LTA model with dementia as a distal outcome was specified to model transitions of ten neuropsychological measures over three annual waves in the Rush Memory and Aging Project (n = 1,661). The predictive validity of the mover-stayer status for incident Alzheimer's disease (AD) was then assessed.
RESULTS: We identified a five-class model across the three time-points: Mixed-Domain Impairment, Memory-Specific Impairment, Frontal Impairment, Average, and Superior Cognition. None of the individuals in the Impairment classes reverted to the Average or Superior classes. Conventional MCI classification identified 26.4% and 14.1% at Times 1 and 2 as false-positive cases. "Movers" had 87% increased risk of developing dementia compared to those classified as "Stayers".
CONCLUSION: Our findings support the use of latent variable modelling that incorporates comprehensive neuropsychological assessment to identify and classify cognitive impairment.
OBJECTIVE: We applied latent transition analysis (LTA) to determine 1) whether the underlying structure of cognitive profiles found at every measurement occasion are uniform across three waves of assessment, 2) whether class-instability is predictive of distal outcomes, and 3) whether class-reversions from impaired to non-impaired using latent modelling is lower than when using clinical criteria of mild cognitive impairment (MCI).
METHODS: A mover-stayer LTA model with dementia as a distal outcome was specified to model transitions of ten neuropsychological measures over three annual waves in the Rush Memory and Aging Project (n = 1,661). The predictive validity of the mover-stayer status for incident Alzheimer's disease (AD) was then assessed.
RESULTS: We identified a five-class model across the three time-points: Mixed-Domain Impairment, Memory-Specific Impairment, Frontal Impairment, Average, and Superior Cognition. None of the individuals in the Impairment classes reverted to the Average or Superior classes. Conventional MCI classification identified 26.4% and 14.1% at Times 1 and 2 as false-positive cases. "Movers" had 87% increased risk of developing dementia compared to those classified as "Stayers".
CONCLUSION: Our findings support the use of latent variable modelling that incorporates comprehensive neuropsychological assessment to identify and classify cognitive impairment.