ArticleFrontiers in neurology2023
Predictive factors for Alzheimer's disease progression: a comprehensive retrospective analysis of 3,553 cases with 211 months follow-up.
Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 7 citations in OpenAlex.
- Genetic Associations with Temporal Modeling of Alzheimer's Disease Progression Supports a Novel Paradigm for Disease Risk.medRxiv : the preprint server for health sciences · 2026Article
- Epidemiologic and clinical features of Alzheimer's disease: a hospital study based on the memory clinic in Abidjan, Côte D'ivoire, Sub-Saharan Africa.BMC neurology · 2026Article
- Interpretable Machine Learning for Risk Stratification of Hippocampal Atrophy in Alzheimer's Disease Using CSF Erythrocyte Load and Clinical Data.Biomedicines · 2025Article
- Primary age-related tauopathy.Acta neuropathologica · 2025Review
- AutoRADP: An Interpretable Deep Learning Framework to Predict Rapid Progression for Alzheimer's Disease and Related Dementias Using Electronic Health Records.medRxiv : the preprint server for health sciences · 2025Article
- Fazekas scale magnetic resonance imaging assessment in Alzheimer's disease and primary age-related tauopathy.Neuroradiology · 2024Article
- Mild Cognitive Impairment Progression and Alzheimer's Disease Risk: A Comprehensive Analysis of 3553 Cases over 203 Months.Journal of clinical medicine · 2024Article
- Temporal atrophy together with verbal encoding impairment is highly predictive for cognitive decline in typical Alzheimer's dementia - a retrospective follow-up study.Frontiers in psychiatry · 2024Article
- Factors affecting progression of non-Alzheimer dementia: a retrospective analysis with long-term follow-up.Frontiers in neurology · 2023Article
- Early intervention and adding effective doses of EGb761 likeFrontiers in neurology · 2023Article
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Authors and funding
4 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Background: There is conflicting data regarding the predictors of Alzheimer's Disease (AD), the most common form of dementia. The main objective of the study is to evaluate potential predictors of AD progression using a comprehensive follow-up dataset that includes functional/cognitive assessments, clinical and neuropsychiatric evaluations, and neuroimaging biomarkers such as hippocampal atrophy or white matter intensities (WMIs). Method: A total of 161 AD cases were recruited from a dementia database consisting of individuals who consulted the Dementia Outpatient Clinic of the Neurology Department at Mersin University Medical Faculty between 2000 and 2022, under the supervision of the same senior author have at least 3 full evaluation follow-up visit including functional, clinical, biochemical, neuropsychological, and radiological screening. Data were exported and analyzed by experts accordingly. Results: Mean follow-up duration of study sample was 71.66 ± 41.98, min 15 to max 211 months. The results showed a fast and slow progressive subgroup of our AD cases with a high sensitivity (Entropy = 0.836), with a close relationship with several cofactors and the level of disability upon admittance. Hippocampal atrophy and WMIs grading via Fazekas were found to be underestimated predictors of AD progression, and functional capacity upon admittance was also among the main stakeholders. Conclusion: The study highlights the importance of evaluating multiple potential predictors for AD progression, including functional capacity upon admittance, hippocampal atrophy, and WMIs grading via Fazekas. Our findings provide insight into the complexity of AD progression and may contribute to the development of effective strategies for managing and treating AD.
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