ArticleGeroScience2020
A multivariate model of time to conversion from mild cognitive impairment to Alzheimer's disease.
Article in GeroScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Longitudinal multi-modal data prediction model for mild cognitive impairment by deep survival analysis.BMC medical informatics and decision making · 2026Article
- Advancements in deep learning for early diagnosis of Alzheimer's disease using multimodal neuroimaging: challenges and future directions.Frontiers in neuroinformatics · 2025Review
- Peak alpha frequency as an objective biomarker for cognitive assessment in post-stroke cognitive impairment.Frontiers in aging neuroscience · 2025Article
- High-power transient 12-30 Hz beta event features as early biomarkers of Alzheimer's disease conversion: An MEG study.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Sex differences in the progression to Alzheimer's disease: a combination of functional and structural markers.GeroScience · 2024Article
- Modified RCTU Score: A Semi-Quantitative, Visual Tool for Predicting Alzheimer's Conversion from aMCI.Brain sciences · 2024Article
- Episodic memory dysfunction and hypersynchrony in brain functional networks in cognitively intact subjects and MCI: a study of 379 individuals.GeroScience · 2023Article
- Sex differences in brain functional connectivity of hippocampus in mild cognitive impairment.Frontiers in aging neuroscience · 2022Article
- Gamma band functional connectivity reduction in patients with amnestic mild cognitive impairment and epileptiform activity.Brain communications · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present study was aimed at determining which combination of demographic, genetic, cognitive, neurophysiological, and neuroanatomical factors may predict differences in time to progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). To this end, a sample of 121 MCIs was followed up during a 5-year period. According to their clinical outcome, MCIs were divided into two subgroups: (i) the "progressive" MCI group (n = 46; mean time to progression 17 ± 9.73 months) and (ii) the "stable" MCI group (n = 75; mean time of follow-up 31.37 ± 14.58 months). Kaplan-Meier survival analyses were applied to explore each variable's relationship with the progression to AD. Once potential predictors were detected, Cox regression analyses were utilized to calculate a parsimonious model to estimate differences in time to progression. The final model included three variables (in order of relevance): left parahippocampal volume (corrected by intracranial volume, LP_ ICV), delayed recall (DR), and left inferior occipital lobe individual alpha peak frequency (LIOL_IAPF). Those MCIs with LP_ICV volume, DR score, and LIOL_IAPF value lower than the defined cutoff had 6 times, 5.5 times, and 3 times higher risk of progression to AD, respectively. Besides, when the categories of the three variables were "unfavorable" (i.e., values below the cutoff), 100% of cases progressed to AD at the end of follow-up. Our results highlighted the relevance of neurophysiological markers as predictors of conversion (LIOL_IAPF) and the importance of multivariate models that combine markers of different nature to predict time to progression from MCI to dementia.
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