Evidence map›Paper›PMID 37706007›Full record

ArticleFrontiers in neurology2023

Risk factors and a prediction model for unruptured intracranial aneurysms in patients with ischemic stroke using carotid intima-media thickness and systemic atherosclerosis.

Gaiming Gao, Dezhi Kang, Jinning Zhang, Zhixian Jiang, Xueyang He, Yanyu Wu

Abstract read
In one paragraph

Article in Frontiers in neurology, 2023. 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

6 authors.

Gaiming GaoDepartment of Neurosurgery, First Hospital of Quanzhou, Quanzhou, Fujian, China.
Dezhi KangDepartment of Neurosurgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Jinning ZhangDepartment of Neurosurgery, First Hospital of Quanzhou, Quanzhou, Fujian, China.
Zhixian JiangDepartment of Neurosurgery, First Hospital of Quanzhou, Quanzhou, Fujian, China.
Xueyang HeDepartment of Neurosurgery, First Hospital of Quanzhou, Quanzhou, Fujian, China.
Yanyu WuDepartment of Anesthesiology, First Hospital of Quanzhou, Quanzhou, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Systemic atherosclerosis and carotid intima-media thickness (IMT) have been widely used in clinical practice for ischemic stroke; however, little is known about the risk factors for unruptured intracranial aneurysms (UIAs) in patients with ischemic stroke (IS). Therefore, we performed this study to identify the risk factors and construct a prediction model for UIA in patients with IS. Methods: Data were retrospectively collected from patients with IS from 2015 to 2022 at the First Hospital of Quanzhou City, Quanzhou, Fujian, China. Risk factors for UIA in patients with IS were identified using a multivariate logistic regression model, and a receiver operating characteristic (ROC) curve was applied to construct the prediction model. Results: Out of the 122 patients with IS, 52 who presented with UIA (ISUIA) were categorized into the study group and the remaining 70 IS patients without UIA into the control group. Patients in the ISUIA group had lower carotid IMT and carotid artery plaque scores than those in the IS group ( Conclusion: The findings revealed that the risk factors for UIA in patients with IS included aspirin use, elevated CRP level, and smaller carotid IMT, and the predictive value of the prediction model was relatively better.

Indexed as

carotid intima-media thicknessischemic strokeprediction modelrisk factorssystemic atherosclerosisunruptured intracranial aneurysms

Identifiers

PMID37706007
PMCPMC10495834

What Socratic holds

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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 Socratic graph.