Predictors of Cognitive Decline in Alzheimer’s Disease: A Longitudinal Bayesian Analysis

<i>Background and Objectives</i>: Alzheimer’s disease (AD) is a progressive neurodegenerative condition that significantly affects cognitive, emotional, and functional abilities in older adults. This study aimed to explore how demographic, clinical, and psychological factors influence th...

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Main Authors: Denisa Claudia Negru, Delia Mirela Tit, Paul Andrei Negru, Gabriela Bungau, Ruxandra Cristina Marin
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Medicina
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Online Access:https://www.mdpi.com/1648-9144/61/5/877
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author Denisa Claudia Negru
Delia Mirela Tit
Paul Andrei Negru
Gabriela Bungau
Ruxandra Cristina Marin
author_facet Denisa Claudia Negru
Delia Mirela Tit
Paul Andrei Negru
Gabriela Bungau
Ruxandra Cristina Marin
author_sort Denisa Claudia Negru
collection DOAJ
description <i>Background and Objectives</i>: Alzheimer’s disease (AD) is a progressive neurodegenerative condition that significantly affects cognitive, emotional, and functional abilities in older adults. This study aimed to explore how demographic, clinical, and psychological factors influence the progression of cognitive decline in patients diagnosed with AD. <i>Materials and Methods:</i> A total of 101 patients were evaluated retrospectively and followed longitudinally at three different time points, using standardized instruments, including the MMSE, Reisberg’s GDS, clock-drawing test, MADRS, and Hamilton depression scale. Statistical methods included non-parametric tests, mixed-effect modeling, and Bayesian analysis. <i>Results:</i> Most patients were older women from rural areas, predominantly in moderate-to-severe stages of AD. Age showed a significant association with cognitive decline (<i>p</i> < 0.05), and depression—particularly in moderate and severe forms—was strongly linked to lower MMSE scores (<i>p</i> < 0.001). Over 70% of the participants had some degree of depression. The clock-drawing test highlighted visuospatial impairments, consistent with everyday functional loss. Although donepezil and memantine combinations appeared to be more frequently prescribed, no treatment showed a statistically significant advantage, and confidence interval overlaps suggest caution in interpreting differences between therapies. Longitudinal models confirmed a progressive and accelerated decline, with inter-individual variability becoming more pronounced in later stages. Although comorbidities, such as hypertension and diabetes, were frequent, they did not show a statistically significant effect on MMSE scores in this cohort. <i>Conclusions:</i> Age and depression appear to play central roles in the pace of cognitive deterioration in AD. Given the limited efficacy of most current therapies, these findings highlight the need for earlier intervention and a more personalized, integrated approach—combining cognitive care, psychiatric support, and comorbidity management—to better meet the needs of patients with AD.
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spelling doaj-art-7cc19e69bb714e7189f770ef7021481e2025-08-20T03:48:02ZengMDPI AGMedicina1010-660X1648-91442025-05-0161587710.3390/medicina61050877Predictors of Cognitive Decline in Alzheimer’s Disease: A Longitudinal Bayesian AnalysisDenisa Claudia Negru0Delia Mirela Tit1Paul Andrei Negru2Gabriela Bungau3Ruxandra Cristina Marin4Doctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, RomaniaDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, RomaniaDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, RomaniaDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, RomaniaDoctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania<i>Background and Objectives</i>: Alzheimer’s disease (AD) is a progressive neurodegenerative condition that significantly affects cognitive, emotional, and functional abilities in older adults. This study aimed to explore how demographic, clinical, and psychological factors influence the progression of cognitive decline in patients diagnosed with AD. <i>Materials and Methods:</i> A total of 101 patients were evaluated retrospectively and followed longitudinally at three different time points, using standardized instruments, including the MMSE, Reisberg’s GDS, clock-drawing test, MADRS, and Hamilton depression scale. Statistical methods included non-parametric tests, mixed-effect modeling, and Bayesian analysis. <i>Results:</i> Most patients were older women from rural areas, predominantly in moderate-to-severe stages of AD. Age showed a significant association with cognitive decline (<i>p</i> < 0.05), and depression—particularly in moderate and severe forms—was strongly linked to lower MMSE scores (<i>p</i> < 0.001). Over 70% of the participants had some degree of depression. The clock-drawing test highlighted visuospatial impairments, consistent with everyday functional loss. Although donepezil and memantine combinations appeared to be more frequently prescribed, no treatment showed a statistically significant advantage, and confidence interval overlaps suggest caution in interpreting differences between therapies. Longitudinal models confirmed a progressive and accelerated decline, with inter-individual variability becoming more pronounced in later stages. Although comorbidities, such as hypertension and diabetes, were frequent, they did not show a statistically significant effect on MMSE scores in this cohort. <i>Conclusions:</i> Age and depression appear to play central roles in the pace of cognitive deterioration in AD. Given the limited efficacy of most current therapies, these findings highlight the need for earlier intervention and a more personalized, integrated approach—combining cognitive care, psychiatric support, and comorbidity management—to better meet the needs of patients with AD.https://www.mdpi.com/1648-9144/61/5/877Alzheimer’s diseaseBayesian analysisReisberg’s GDSclock-drawing testHamilton depression scalememantine
spellingShingle Denisa Claudia Negru
Delia Mirela Tit
Paul Andrei Negru
Gabriela Bungau
Ruxandra Cristina Marin
Predictors of Cognitive Decline in Alzheimer’s Disease: A Longitudinal Bayesian Analysis
Medicina
Alzheimer’s disease
Bayesian analysis
Reisberg’s GDS
clock-drawing test
Hamilton depression scale
memantine
title Predictors of Cognitive Decline in Alzheimer’s Disease: A Longitudinal Bayesian Analysis
title_full Predictors of Cognitive Decline in Alzheimer’s Disease: A Longitudinal Bayesian Analysis
title_fullStr Predictors of Cognitive Decline in Alzheimer’s Disease: A Longitudinal Bayesian Analysis
title_full_unstemmed Predictors of Cognitive Decline in Alzheimer’s Disease: A Longitudinal Bayesian Analysis
title_short Predictors of Cognitive Decline in Alzheimer’s Disease: A Longitudinal Bayesian Analysis
title_sort predictors of cognitive decline in alzheimer s disease a longitudinal bayesian analysis
topic Alzheimer’s disease
Bayesian analysis
Reisberg’s GDS
clock-drawing test
Hamilton depression scale
memantine
url https://www.mdpi.com/1648-9144/61/5/877
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