Evidence map›Paper›PMID 30772684›Full record

ArticleNeuroImage. Clinical2019

Structural brain network measures are superior to vascular burden scores in predicting early cognitive impairment in post stroke patients with small vessel disease.

Jing Du, Yao Wang, Nan Zhi, Jieli Geng, Wenwei Cao, Ling Yu, Jianhua Mi, Yan Zhou, Qun Xu, Wei Wen and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

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  13. Global changes in diffusion tensor imaging during acute ischemic stroke and post-stroke cognitive performance.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2022
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  20. Inner Hemispheric and Interhemispheric Connectivity Balance in the Human Brain.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021
    Article
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

11 authors.

Jing DuDepartment of Neurology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Renji-UNSW CHeBA Neurocognitive Center, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Yao WangDepartment of Radiology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Nan ZhiDepartment of Neurology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Renji-UNSW CHeBA Neurocognitive Center, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Jieli GengDepartment of Neurology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Renji-UNSW CHeBA Neurocognitive Center, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Wenwei CaoDepartment of Neurology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Renji-UNSW CHeBA Neurocognitive Center, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Ling YuDepartment of Neurology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Renji-UNSW CHeBA Neurocognitive Center, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Jianhua MiDepartment of Neurology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Renji-UNSW CHeBA Neurocognitive Center, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Yan ZhouDepartment of Radiology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. Electronic address: clare1475@hotmail.com.
Qun XuRenji-UNSW CHeBA Neurocognitive Center, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Department of Health Manage Center, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. Electronic address: xuqun@renji.com.
Wei WenCentre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, Australia.
Perminder SachdevCentre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesIn this cross-sectional study, we aimed to explore the mechanisms of early cognitive impairment in a post stroke non-dementia cerebral small vessel disease (SVD) cohort by comparing the SVD score with the structural brain network measures.

method127 SVD patients were recruited consecutively from a stroke clinic, comprising 76 individuals with mild cognitive impairment (MCI) and 51 with no cognitive impairment (NCI). Detailed neuropsychological assessments and multimodal MRI were performed. SVD scores were calculated on a standard scale, and structural brain network measures were analyzed by diffusion tensor imaging (DTI). Between-group differences were analyzed, and logistic regression was applied to determine the predictive value of SVD and network measures for cognitive status. Mediation analysis with structural equation modeling (SEM) was used to better understand the interactions of SVD burden, brain networks and cognitive deficits.

resultsGroup difference was found on all global brain network measures. After adjustment for age, gender, education and depression, significant correlations were found between global brain network measures and diverse neuropsychological tests, including TMT-B (r = -0.209, p < .05), DSST (r = 0.206, p < .05), AVLT short term free recall (r = 0.233, p < .05), AVLT long term free recall (r = 0.264, p < .05) and Rey-O copy (r = 0.272, p < .05). SVD score showed no group difference and was not correlated with cognition tests. Network global efficiency (E

conclusionsBrain network measures, but not the SVD score, are significantly correlated with cognition in post-stroke SVD patients. Mediation analysis showed that the cerebral vascular lesions produce cognitive dysfunction by interfering with the structural brain network in SVD patients. The brain network measures may be regarded as direct and independent surrogate markers of cognitive impairment in SVD.

Indexed as

AgedAged, 80 and overBrainCerebral Small Vessel DiseasesCognitive DysfunctionCross-Sectional StudiesDiffusion Tensor ImagingFemaleHumansImage Interpretation, Computer-AssistedMaleMiddle AgedNerve NetStrokeBrain networksCerebral small vessel diseaseCognitive impairmentSVD score

Identifiers

PMID30772684
PMCPMC6378318

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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.