Cognitive trajectories modeling of rare reversion in mild cognitive impairment

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Author: QIN Yao ^1, ^2, ³ HUO Yanji ¹ ZHOU Jing ¹ ZHOU Yan ¹ HAN Hongjuan ⁴ CUI Jing ^1, ²  YU Hongmei ^1, ^2, ³

Affiliation: 1. Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan 030001, China 2. Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, Shanxi Medical University, Taiyuan 030001, China. 3. Ministry of Education Key Laboratory of Coal Environmental Pathogenicity and Prevention, Taiyuan 030001, China 4. Department of Mathematics, School of Basic Medical Sciences, Shanxi Medical University, Taiyuan 030001, China

Keywords: Mild cognitive impairment Reversion Rare events Functional principal component analysis Multi-state model

DOI: 10.12173/j.issn.1005-0698.202503205

Reference: QIN Yao, HUO Yanji, ZHOU Jing, ZHOU Yan, HAN Hongjuan, CUI Jing, YU Hongmei. Cognitive trajectories modeling of rare reversion in mild cognitive impairment[J]. Yaowu Liuxingbingxue Zazhi, 2025, 34(8): 877-886. DOI: 10.12173/j.issn.1005-0698.202503205.[Article in Chinese]  Copied

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Abstract

Objective To construct a dynamic framework for bidirectional transitions of mild cognitive impairment (MCI), quantifying both rare reversion and high-risk progression trajectories in cognitive dynamics.

Methods Patients diagnosed with MCI at baseline from 2005 to 2022 and completed at least two follow-up visits were selected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), and a retrospective cohort was constructed. Demographic information, APOEε4 genotype, and neuropsychological scales data were collected. Longitudinal cognitive assessments were functionally reconstructed using multivariate functional principal component analysis (MFPCA), with functional principal components (FPCs) extracted based on cumulative variance contribution rate (PVE>90%). Functional multi-state Markov models were developed to estimate inter-state transition intensities, year to year transition probabilities, and covariate effects.

Results Among 1,019 MCI patients (4,657 follow-up visits), 93 (9.1%) reverted to normal cognition, while 359 (35.2%) progressed to Alzheimer’s disease (AD). Longitudinal trajectory analysis revealed significant heterogeneity: progressive MCI > stable MCI > reverted MCI in the first functional principal component (MFPC1) scores. The transition intensity for MCI reversion (0.020) was approximately one-fourth of the AD progression risk (0.086), but the post-reversion cognitive re-impairment intensity was 0.138. Reduced MFPC1 (HR=0.993, 95%Cl: 0.991, 0.995) and elevated MFPC2 (HR=1.004, 95%Cl: 1.001, 1.007) were closely associated with MCI reversion.

Conclusion MCI exhibits marked heterogeneity in longitudinal cognitive trajectories. Although reversion is rare, reversed patients remain at high risk of cognitive re-impairment.

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