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.

Ribino, P., Paragliola, G., Napoli, C., Mannone, M., Chicco, D., Gasparini, F. (2024). Clustering of longitudinal Clinical Dementia Rating data to identify predictors of Alzheimer's disease progression. In 15th International Conference on Emerging Ubiquitous Systems and Pervasive Networks / 14th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare EUSPN/ICTH 2024 (pp.326-333) [10.1016/j.procs.2024.11.117].

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

Chicco D.;Gasparini F.
2024

Abstract

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.
paper
Alzheimer's disease; Clinical Dementia Rating; Cognitive Decline; Longitudinal Clustering; Statistical Analysis;
English
15th International Conference on Emerging Ubiquitous Systems and Pervasive Networks / 14th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, EUSPN/ICTH 2024 - 28 October 2024 through 30 October 2024
2024
15th International Conference on Emerging Ubiquitous Systems and Pervasive Networks / 14th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare EUSPN/ICTH 2024
2024
251
326
333
open
Ribino, P., Paragliola, G., Napoli, C., Mannone, M., Chicco, D., Gasparini, F. (2024). Clustering of longitudinal Clinical Dementia Rating data to identify predictors of Alzheimer's disease progression. In 15th International Conference on Emerging Ubiquitous Systems and Pervasive Networks / 14th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare EUSPN/ICTH 2024 (pp.326-333) [10.1016/j.procs.2024.11.117].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/536822
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