Evidence map›Paper›PMID 40280803›Full record

ArticleThe journal of prevention of Alzheimer's disease2025

Association of the difference between cystatin C- and creatinine-based estimated glomerular filtration rate with cerebral small vessel disease: A large prospective cohort study.

Zhiming Li, Fei Wang, Jincheng Liu, Benbo Xiong, Han Wang, Zijie Wang, Xiao Hu, Qi Li

Abstract read
In one paragraph

Article in The journal of prevention of Alzheimer's disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Zhiming LiDepartment of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Fei WangDepartment of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Jincheng LiuDepartment of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China; Department of Neurology, Xiangyang Hospital of Traditional Chinese Medicine, Xiangyang, Hubei, China.
Benbo XiongDepartment of Clinical Medicine, The Second School of Clinical Medicine, Anhui Medical University, China.
Han WangDepartment of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Zijie WangDepartment of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Xiao HuDepartment of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Qi LiDepartment of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China. Electronic address: qili_md@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveIt remains unclear whether the difference between the estimated glomerular filtration rate based on cystatin C and creatinine (eGFRdiff) is associated with cerebral small vessel disease (CSVD). We investigated the correlation of eGFRdiff with SCVD and further evaluated the mediating role of blood pressure.

methodsThis prospective cohort study included 35,590 neurologically healthy participants at baseline (2006 to 2010) from the UK Biobank. eGFRdiff is divided into two indicators: absolute difference (eGFRabdiff) and ratio (eGFRrediff) based on the calculation between cystatin C and creatinine. CSVD was assessed by calculating white matter hyperintensity volume (WMHV) from T2-FLAIR brain MRI scans (conducted between 2014 and 2021), with values normalized to intracranial volume and log-transformed. Multiple linear regression models and mediation analysis was used to evaluate the associations of eGFRdiff with WMHV.

resultsParticipants with negative eGFRabdiff had higher WMHV (β = 0.07, 95 % confidence interval [CL] = 0.04 ∼ 0.10), while participants with positive eGFRabdiff had smaller WMHV (β = -0.05, 95 %CL = -0.09 ∼ -0.02), compared to midrange eGFRabdiff group. Meanwhile, participants with eGFRrediff ≤ 0.7 had higher WMHV compared with participants with eGFRrediff > 0.7 (β = 0.08, 95 %CL = 0.01∼ 0.15) .In addition, hypertension mediated the associations between eGFRdiff and WMHV (12.6 % ∼13.2 %).

conclusioneGFRdiff was independently associated with WMHV. Our findings suggested that monitoring eGFRdiff has potential benefits in identifying the burden of CSVD in the general population in future.

Indexed as

Cerebral Small Vessel DiseasesCreatinineCystatin CGlomerular Filtration RateAgedBiomarkersFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedProspective StudiesWhite MatterBiomarkersCreatinineCystatin CBlood pressureCerebral small vessel diseaseDementiaEstimated glomerular filtration rateWhite matter hyperintensity

Identifiers

PMID40280803
PMCPMC12321633

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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.