Evidence map›Paper›PMID 31955350›Full record

ArticleNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2020

Decreased visible deep medullary veins is a novel imaging marker for cerebral small vessel disease.

Xiaodong Chen, Lei Wei, Jihui Wang, Yilong Shan, Wei Cai, Xuejiao Men, Sanxin Liu, Zhuang Kang, Zhengqi Lu, Vincent C T Mok and 1 more

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In one paragraph

Article in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
1.7field-weighted citation impact, top 12% of its field
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

34 citing papers in PubMed, 40 citations in OpenAlex.

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  15. Advancements in investigating the role of cerebral small vein loss in Alzheimer's disease-related pathological changes.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024
    Review
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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 at 2 institutions in 2 countries.

Xiaodong Chen *Department of Neurology, The Third Affiliated Hospital of Sun Yat-sen University, Tianhe Road No. 600, Guangzhou, 510630, Guangdong, China.
Lei Wei *Department of Neurology, The Third Affiliated Hospital of Sun Yat-sen University, Tianhe Road No. 600, Guangzhou, 510630, Guangdong, China.
Jihui Wang *Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Yilong ShanDepartment of Rehabilitation Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Wei CaiDepartment of Clinical Immunology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Xuejiao MenDepartment of Neurology, The Third Affiliated Hospital of Sun Yat-sen University, Tianhe Road No. 600, Guangzhou, 510630, Guangdong, China.
Sanxin LiuDepartment of Neurology, The Third Affiliated Hospital of Sun Yat-sen University, Tianhe Road No. 600, Guangzhou, 510630, Guangdong, China.
Zhuang KangDepartment of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China.
Zhengqi LuDepartment of Neurology, The Third Affiliated Hospital of Sun Yat-sen University, Tianhe Road No. 600, Guangzhou, 510630, Guangdong, China. lzq1828@outlook.com.ORCID http://orcid.org/0000-0002-2118-0368
Vincent C T MokDepartment of Medicine and Therapeutics, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, The Chinese University of Hong Kong, Hong Kong, China.
Aimin WuDepartment of Neurology, The Third Affiliated Hospital of Sun Yat-sen University, Tianhe Road No. 600, Guangzhou, 510630, Guangdong, China.
Sun Yat-sen University · CNChinese University of Hong Kong · HK

Funding

Guangzhou Science, Technology and Innovation Commission 201704020222National Natural Science Foundation of China 8167118
6 · The paper itself

Abstract

purposeVisibility of deep medullary veins (DMVs) seen at SWI is predictive of poor prognosis in ischemic stroke. Few attentions have been paid to DMVs in atherosclerotic cerebral small vessel disease (aCSVD) which is attributed to long-term imbalanced microhemodynamics. We conducted this retrospective study to explore the association between DMVs profiles and aCSVD risk factors, neuroimaging markers.

methodsTwo hundred and two patients identified as aCSVD from January 2017 to March 2019 were included in the study. Their demographic, clinical, laboratory, and neuroimaging data were reviewed. The quantity and morphology of DMVs were assessed with a 5-grade (range 0~4) visual rating scale. Total CSVD burden was calculated with an ordinal "SVD score" (range 0~4). Spearman rank correlation and multivariable logistic regression analysis were performed to determine the association between DMV scale and CSVD markers.

resultsDMV scale showed strong positive correlation with CSVD burden (r

conclusionMultifactorial association between DMV scale and epidemiological, radiological contributors of aCSVD suggests DMV's involved pathomechanism may participate in aCSVD development. Attach importance to DMV radiological profile in aCSVD will provide more neuroimaging information for diagnosis and prognosis.

Indexed as

AgedBiomarkersCerebral Small Vessel DiseasesCerebral VeinsCross-Sectional StudiesFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNeuroimagingRetrospective StudiesWhite MatterBiomarkersCerebral small vessel diseaseCSVD burdenDeep medullary veinNeuroimaging marker

Identifiers

PMID31955350
OpenAlexW2999809778

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.