Evidence map›Paper›PMID 40353049›Full record

ArticleAging medicine (Milton (N.S.W))2025

Risk Factors and Predictive Model for Ischemic Complications in Endovascular Treatment of Intracranial Aneurysms: Insights From a Large Patient Cohort.

Jianwen Jia, Zeping Jin, Mirzat Turhon, Yixin Lin, Xinjian Yang, Yang Wang, Yunpeng Liu

Abstract read
In one paragraph

Article in Aging medicine (Milton (N.S.W)), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Jianwen JiaDepartment of Neurosurgery, Beijing Chao-Yang Hospital Capital Medical University Beijing People's Republic of China.
Zeping JinDepartment of Neurosurgery, Beijing Chao-Yang Hospital Capital Medical University Beijing People's Republic of China.
Mirzat TurhonDepartment of Neurosurgery, Beijing Tiantan Hospital Capital Medical University Beijing People's Republic of China.
Yixin LinDepartment of Neurosurgery, Beijing Chao-Yang Hospital Capital Medical University Beijing People's Republic of China.
Xinjian YangDepartment of Neurosurgery, Beijing Tiantan Hospital Capital Medical University Beijing People's Republic of China.
Yang WangDepartment of Neurosurgery, Beijing Chao-Yang Hospital Capital Medical University Beijing People's Republic of China.
Yunpeng LiuDepartment of Neurosurgery, Beijing Chao-Yang Hospital Capital Medical University Beijing People's Republic of China.ORCID https://orcid.org/0000-0002-9760-2715

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: There remains a conspicuous absence of systematic analysis concerning the risk factors for the development of ischemic complications in the interventional treatment of IAs. Our study aimed to identify the risk factors for ischemic complications after the interventional treatment of IAs and to make an individualized prediction of the occurrence of ischemic complications, providing important reference guidance for clinicians. Methods: This study encompassed a sample of 473 patients diagnosed with intracranial aneurysms (IA) and treated at our center between February 2022 and April 2024. Ischemic complications were identified via clinical symptomatology and corroborated with diagnostic subtraction angiography (DSA), computed tomography (CT), or magnetic resonance imaging (MRI). We used a machine learning (ML) approach to screen potential variables for ischemic complications and identify correlations between them, and subsequently constructed a logistic regression model to quantify these correlations. Results: Patients were categorized based on the occurrence or absence of ischemic complications. A total of five potential factors were screened using LASSO regression, XGBoost, and Randomforest algorithms: hypertension, history of alcohol consumption, multiple IAs, rupture status, and antiplatelet agent. Multivariate analysis further disclosed that hypertension, history of alcohol consumption, ruptured aneurysms, and antiplatelet agent were independent risk factors for postoperative ischemic complications. The predictive model, derived from the multivariate regression analysis results, demonstrated robust reliability. Conclusions: Hypertension, history of alcohol consumption, ruptured aneurysms, and antiplatelet agent as independent risk factors for ischemic complications following the interventional treatment of IAs. Accordingly, we constructed the first risk prediction model regarding ischemic complications of all IAs based on these factors, aiming to enhance prognostic judgment and treatment strategy planning.

Indexed as

intracranial aneurysmsischemic complicationspredictive modelradiographic

Identifiers

PMID40353049
PMCPMC12064986

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.