Evidence map›Paper›PMID 39022730›Full record

ArticleFrontiers in neurology2024

HR-MRI-based nomogram network calculator to predict stroke recurrence in high-risk non-disabling ischemic cerebrovascular events patients.

Zi-Ang Li, Yu Gao, Lin Han, Bei-Chen Xie, Yan-Cong Sun, Xiao-Yang Zhai, Ping Zhang, Yong-Dong Li, Jun-Yan Yue, Rui-Fang Yan and 1 more

Abstract read
In one paragraph

Article in Frontiers in neurology, 2024. 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. 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.

Zi-Ang LiDepartment of Radiology Center, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Yu GaoDepartment of Radiology Center, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Lin HanDepartment of Radiology Center, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Bei-Chen XieDepartment of Radiology Center, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Yan-Cong SunDepartment of Radiology Center, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Xiao-Yang ZhaiDepartment of Radiology Center, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Ping ZhangDepartment of Neurology Center, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Yong-Dong LiInstitute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jun-Yan YueDepartment of Radiology Center, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Rui-Fang YanDepartment of Radiology Center, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Hong-Kai CuiDepartment of Neurointerventional Center, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objective: To investigate the use of high-resolution magnetic resonance imaging (HR-MRI) to identify the characteristics of culprit plaques in intracranial arteries, and to evaluate the predictive value of the characteristics of culprit plaques combined with the modified Essen score for the recurrence risk of high-risk non-disabling ischemic cerebrovascular events (HR-NICE) patients. Methods: A retrospective analysis was conducted on 180 patients with HR-NICE at the First Affiliated Hospital of Xinxiang Medical University, including 128 patients with no recurrence (non-recurrence group) and 52 patients with recurrence (recurrence group). A total of 65 patients with HR-NICE were collected from the Sixth Affiliated Hospital of Shanghai Jiaotong University as a validation group, and their modified Essen scores, high-resolution magnetic resonance vessel wall images, and clinical data were collected. The culprit plaques were analyzed using VesselExplorer2 software. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for recurrence, and a nomogram was constructed using R software to evaluate the discrimination of the model. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) was used to evaluate the model performance. Calibration curves and Decision Curve Analysis (DCA) were used to evaluate the model efficacy. Results: Intra-plaque hemorrhage (OR = 3.592, 95% CI = 1.474-9.104, Conclusion: High-resolution vessel wall imaging combined with a modified Essen score can effectively assess the recurrence risk of HR-NICE patients, and the nomogram model can provide a reference for identifying high-risk populations with good clinical application prospects.

Indexed as

high-resolution vessel wall imaginghigh-risk non-disabling ischemic cerebrovascular eventsnomogramplaquestroke recurrence

Identifiers

PMID39022730
PMCPMC11252045

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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.