Evidence map›Paper›PMID 40352772›Full record

ArticleFrontiers in neurology2025

Development and validation of a blood biomarker-based model for differentiating stroke etiology in acute large vessel occlusion.

Weiwei Gao, Renjing Zhu, Jingjing She, Rong Huang, Lijuan Cai, Shouyue Jin, Yanping Lin, Jianzhong Lin, Xingyu Chen, Liangyi Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Weiwei Gao *Department of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, National Advanced Center for Stroke, Xiamen Key Subspecialty of Neurointerventional Radiology, Xiamen University, Xiamen, China.
Renjing Zhu *Department of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, National Advanced Center for Stroke, Xiamen Key Subspecialty of Neurointerventional Radiology, Xiamen University, Xiamen, China.
Jingjing SheThe School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian, China.
Rong HuangSchool of Medicine, Xiamen University, Xiamen, China.
Lijuan CaiDepartment of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, National Advanced Center for Stroke, Xiamen Key Subspecialty of Neurointerventional Radiology, Xiamen University, Xiamen, China.
Shouyue JinDepartment of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, National Advanced Center for Stroke, Xiamen Key Subspecialty of Neurointerventional Radiology, Xiamen University, Xiamen, China.
Yanping LinDepartment of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, National Advanced Center for Stroke, Xiamen Key Subspecialty of Neurointerventional Radiology, Xiamen University, Xiamen, China.
Jianzhong LinDepartment of MRI, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Xingyu ChenDepartment of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, National Advanced Center for Stroke, Xiamen Key Subspecialty of Neurointerventional Radiology, Xiamen University, Xiamen, China.
Liangyi ChenDepartment of Neurology, Zhongshan Hospital of Xiamen University, School of Medicine, National Advanced Center for Stroke, Xiamen Key Subspecialty of Neurointerventional Radiology, Xiamen University, Xiamen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Early differentiation of stroke etiology in acute large vessel occlusion stroke (LVOS) is crucial for optimizing endovascular treatment strategies. This study aimed to develop and validate a prediction model for pre-procedural etiological differentiation based on admission laboratory parameters. Methods: We conducted a retrospective cohort study at a comprehensive stroke center, enrolling consecutive patients with acute LVOS who underwent endovascular treatment between January 2018 and October 2024. The study cohort ( Results: Of 415 enrolled patients, 199 (48.0%) had cardioembolism (CE). The final model incorporated six independent predictors: age [adjusted odds ratio (aOR) 1.03], male sex (aOR 0.35), white blood cell count (aOR 0.86), platelet-large cell ratio (aOR 1.06), aspartate aminotransferase (aOR 1.02), and non-high-density lipoprotein cholesterol (aOR 0.75). The model demonstrated good discriminatory ability in both the training set (AUC = 0.802) and the validation set (AUC = 0.784). Decision curve analysis demonstrated consistent clinical benefit across threshold probabilities of 20%-75%. Conclusion: We developed and internally validated a practical model using routine admission laboratory parameters to differentiate between CE and large artery atherosclerosis in acute LVOS. This readily implementable tool could aid in preoperative decision-making for endovascular intervention.

Indexed as

cardioembolismlaboratory biomarkerslarge vessel occlusionprediction modelstroke etiology

Identifiers

PMID40352772
PMCPMC12061931

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Registered trials

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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.