Clustering of longitudinal Clinical Dementia Rating data to identify predictors of Alzheimer's disease progression.

Autor: Ribino, Patrizia, Paragliola, Giovanni, Napoli, Claudia Di, Mannone, Maria, Chicco, Davide, Gasparini, Francesca
Předmět:
Zdroj: Procedia Computer Science; 2024, Vol. 251, p326-333, 8p
Abstrakt: Clinical Dementia Rating (CDR) is a common tool to assess cognitive and functional abilities in the context of Alzheimer's disease (AD). It is a structured interview that encompasses evaluation across six specific domains. However, AD's initial stages may not lead to a uniform cognitive decline across all cognitive domains. The main aim of this study is to evaluate the prognostic utility of individual CDR domains in predicting the progression of AD dementia over a five-year longitudinal period among an elderly cohort. Initially, a longitudinal-cluster analysis was conducted using five-point longitudinal data to categorize subjects into clusters based on the progression of CDR domains during the follow-up. Then, a statistical analysis was performed on the identified clusters to ascertain whether, at the baseline, patients exhibiting stability have different profiles about CDR domains compared to patients who converted to an AD during the whole follow-up period. Results show that the risk of AD progression was mainly related to problems with Orientation and Judgment at the baseline. [ABSTRACT FROM AUTHOR]
Databáze: Supplemental Index