Evidence map›Paper›PMID 42554250›Full record

ReviewAlzheimer's & dementia : the journal of the Alzheimer's Association2026

Early identification of vascular cognitive impairment from a multimodal perspective: a combined diagnosis from targeted cognitive assessments, imaging biomarkers, and molecular fluid biomarkers to ecological behavioral characteristics.

Wenqi Song, Xiaoqun Liu, Tianrui Yu, Yuanyuan Xiang, Peijie Fu, Moxin Wu, Xiaoping Yin, Xiaorong Zhang, Zhiying Chen

Abstract readReview
In one paragraph

Review in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Wenqi SongDepartment of Neurology, Affiliated Hospital of Jiujiang University, Jiujiang, Jiangxi, China.ORCID https://orcid.org/0009-0008-9198-7598
Xiaoqun LiuJiujiang Clinical Precision Medicine Research Center, Jiujiang, Jiangxi, China.
Tianrui YuDepartment of Neurology, Affiliated Hospital of Jiujiang University, Jiujiang, Jiangxi, China.
Yuanyuan XiangJiujiang Clinical Precision Medicine Research Center, Jiujiang, Jiangxi, China.
Peijie FuDepartment of Neurology, Affiliated Hospital of Jiujiang University, Jiujiang, Jiangxi, China.
Moxin WuDepartment of Medical Laboratory, Affiliated Hospital of Jiujiang University, Jiujiang, Jiangxi, China.
Xiaoping YinDepartment of Neurology, Affiliated Hospital of Jiujiang University, Jiujiang, Jiangxi, China.
Xiaorong ZhangJiujiang Clinical Precision Medicine Research Center, Jiujiang, Jiangxi, China.
Zhiying ChenDepartment of Neurology, Affiliated Hospital of Jiujiang University, Jiujiang, Jiangxi, China.

Funding

Jiangxi Provincial Administration of Traditional Chinese Medicine science and technology plan project 2022A322Jiangxi Provincial Health Commission Science and Technology Plan project 202311506National Natural Science Foundation of China 81960221National Natural Science Foundation of China 82260249Research and Reform Project on Education and Teaching in Ordinary Colleges JXJG-24-17-2Research and Reform Project on Education and Teaching in Ordinary Colleges JXJG-24-17-20Research and Reform Project on Education and Teaching in Ordinary Colleges JXYJG-2024-140Youth Foundation of Natural Science Foundation of Jiangxi Province 20224BAB216045
6 · The paper itself

Abstract

Vascular cognitive impairment (VCI), the second leading cause of dementia, is characterized by heterogeneous pathophysiology and a potentially reversible early phase, underscoring the need for timely identification. This review synthesizes advances across four complementary domains - targeted cognitive assessments, imaging biomarkers, molecular fluid biomarkers, and ecological behavioral characteristics - conceptualized as the TIME framework. Emerging markers, including the peak width of skeletonized mean diffusivity (PSMD), oxygen extraction fraction, brain-derived extracellular vesicles, and digital gait metrics, enable the detection of microvascular injury before overt cognitive decline. Given the limitations of single modalities, we advocate for multimodal integration via machine learning to capture the disease continuum from vascular insult to clinical impairment. Establishing a standardized, pathophysiologically anchored classification system, analogous to the AT(N) framework in Alzheimer's disease, is essential to advance precision risk stratification and early intervention in VCI.

Indexed as

BiomarkersCognitive DysfunctionDementia, VascularEarly DiagnosisHumansMachine LearningNeuroimagingNeuropsychological TestsBiomarkersbiomarkersearly identificationmachine learningmultimodal diagnosisneuroimagingvascular cognitive impairment

Identifiers

PMID42554250
PMCPMC13439749

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.