Evidence map›Paper›PMID 40640701›Full record

ArticleBMC neurology2025

Local cerebral neurofilament light chain during acute stage is associated with clinical outcomes in stroke patients receiving endovascular thrombectomy.

Kunxin Lin, Youliang Wang, Wenlong Zhao, Yiru Zheng, Xiaohua Sun, Ling Fang, Ying Fu, Ning Wang, Qianqian Lin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Kunxin Lin *Department of Neurology, Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Youliang Wang *Department of Neurology, Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Wenlong ZhaoDepartment of Neurology, Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Yiru ZhengDepartment of Neurology, Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Xiaohua SunDepartment of Neurology, Mindong Hospital Affiliated to Fujian Medical University, Ningde, China.
Ling FangDepartment of Neurology, Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Ying FuDepartment of Neurology, Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Ning WangDepartment of Neurology, Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China. ningwang@fjmu.edu.cn.
Qianqian LinDepartment of Neurology, Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China. 782268043@qq.com.

Funding

Natural Science Foundation of Fujian Province 2020J011337the National Science Foundation of China U21A20360young and middle-aged research major project of Fujian Provincial Health Commission 2022ZQNZD005
6 · The paper itself

Abstract

backgroundPrediction of stroke outcomes is challenging due to limited predictive properties of clinical and radiological variables. We aimed to investigate whether local cerebral neurofilament light chain (NfL) could provide additional prognostic value.

methodsWe prospectively enrolled 110 consecutive patients with large vessel occlusion of the anterior circulation who underwent endovascular thrombectomy (EVT). We collected two different arterial blood samples during EVT: (1) Local: the region of the occluded vascular compartment; (2) Systemic: femoral artery. We used ultrasensitive single-molecule array assay to measure NfL levels, compare systemic and local NfL levels and explore the association of systemic and local NfL with imaging markers and clinical outcomes.

resultsOf the 220 blood samples from the 110 patients who received EVT, the local NfL levels was significantly lower than system levels. Compared with the lower level of local NfL, patients with higher local NfL were more likely male (74.5% vs. 54.5%, p = 0.017), had lower rate of intravenous thrombolysis (14.5% vs. 30.9%, p = 0.041), higher percentage of non-cardioembolic subtype (67.3% vs. 47.3%, p = 0.045). Neither system or local NfL levels correlated with baseline clinical-radiological variables including stroke severity, brain ischemic injury and collateral status. High local NfL could independently predict mortality (OR, 2.431; 95% CI, 1.099–5.378, p = 0.028) and functional outcome towards worse outcome at 90 days (OR, 2.596; 95% CI, 1.267–5.312, p = 0.009) after multivariable regression analysis.

conclusionsOur study suggested that elevated baseline local NfL accumulated in the ischemic vasculature might be a promising predictor for increased adverse clinical outcome of patients receiving EVT.

Indexed as

Endovascular ProceduresNeurofilament ProteinsStrokeThrombectomyAgedAged, 80 and overBiomarkersFemaleHumansMaleMiddle AgedPrognosisProspective StudiesTreatment OutcomeBiomarkersneurofilament protein LNeurofilament ProteinsClinical outcomesEndovascular thrombectomyIschemic strokeMortalityNeurofilament light chain

Identifiers

PMID40640701
PMCPMC12243266

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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.