Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
Neuropsychiatric symptoms in preclinical and clinically manifest dementia: clusters and their health determinants.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Guazzarini Anna Giulia, Galaris Evangelos, Boccardi Virginia, Mancinetti Francesca, Ruggiero Carmelinda, Muehlboeck J-Sebastian, Mecocci Patrizia, Westman Eric, Marseglia Anna
Аннотация
INTRODUCTION: Neuropsychiatric symptoms (NPSs) are common in dementia, but their patterns in preclinical stages remain unclear. This study identified NPS clusters and associated health factors in a geriatric clinical population.
METHODS: We analyzed 1234 participants from the Italian GERIatric COgnitive evaluation memory clinic cohort with Neuropsychiatric Inventory data. Clusters were derived using machine learning (K-means, Elbow method) separately for dementia and dementia-free groups. Associations were assessed via multinomial logistic regression.
RESULTS: In the overall cohort, four NPS clusters emerged: minimal NPS, depression-anxiety-apathy, depression-anxiety, and delusions-agitation-irritability. Cluster profiles differed between the dementia and dementia-free groups. Specific clinical and metabolic factors - lipid abnormalities, glycemic control, thyroid dysfunction, and underweight status - were differentially associated with NPS clusters.
DISCUSSION: Distinct NPS patterns exist across the dementia continuum. These clusters differ in demographic, cognitive, functional, and metabolic profiles, suggesting NPS may precede cognitive decline and represent syndromic entities with diagnostic relevance. Multidimensional, personalized approaches are needed.
METHODS: We analyzed 1234 participants from the Italian GERIatric COgnitive evaluation memory clinic cohort with Neuropsychiatric Inventory data. Clusters were derived using machine learning (K-means, Elbow method) separately for dementia and dementia-free groups. Associations were assessed via multinomial logistic regression.
RESULTS: In the overall cohort, four NPS clusters emerged: minimal NPS, depression-anxiety-apathy, depression-anxiety, and delusions-agitation-irritability. Cluster profiles differed between the dementia and dementia-free groups. Specific clinical and metabolic factors - lipid abnormalities, glycemic control, thyroid dysfunction, and underweight status - were differentially associated with NPS clusters.
DISCUSSION: Distinct NPS patterns exist across the dementia continuum. These clusters differ in demographic, cognitive, functional, and metabolic profiles, suggesting NPS may precede cognitive decline and represent syndromic entities with diagnostic relevance. Multidimensional, personalized approaches are needed.