Evidence map›Paper›PMID 40773059›Full record

ArticleNeuroradiology2025

Acute stroke risk prediction model based on dual-energy CTA-derived carotid plaque, perivascular adipose tissue characteristics, and serum lipid parameters: a dual-center study.

He Zhang, Xu Xu, Juan Long, Chenzi Wang, Xiaohan Liu, Wenbei Xu, Xiaonan Sun, Peipei Dou, Dexing Zhou, Wei Cao and 2 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Neuroradiology, 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. 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

12 authors.

He ZhangDepartment of Medical Imaging, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.ORCID http://orcid.org/0009-0006-6466-1379
Xu XuDepartment of Medical Imaging, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Juan LongDepartment of Medical Imaging, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Chenzi WangDepartment of Medical Imaging, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Xiaohan LiuDepartment of Medical Imaging, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Wenbei XuDepartment of Medical Imaging, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Xiaonan SunDepartment of Medical Imaging, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Peipei DouDepartment of Medical Imaging, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Dexing ZhouDepartment of Medical Imaging, Jiawang District People's Hospital, Xuzhou, China.
Wei CaoDepartment of Medical Imaging, Xuzhou First People's Hospital, Xuzhou, China.
Kai XuDepartment of Medical Imaging, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China. xkpaper@163.com.
Yankai MengDepartment of Medical Imaging, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China. mengyankai@126.com.ORCID http://orcid.org/0000-0002-9671-538X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute stroke is a major global cause of mortality and disability. Accurate prediction of stroke risk is crucial for effective clinical management. This study aimed to develop a multidimensional prediction model for acute stroke using carotid plaque characteristics, lumen parameters, perivascular adipose tissue (PVAT) quantitative metrics derived from dual-energy computed tomography angiography (DE-CTA), and serum lipid biomarkers.

methodsThis retrospective dual-center study enrolled 212 patients who underwent DE-CTA and MRI between January 2023 and October 2024, comprising a training cohort (137 patients) and an external validation cohort (75 patients). Quantitative parameters including carotid plaque features (composition and intraplaque parameters), lumen metrics, PVAT quantitative indices, and serum lipid levels were collected. Patients with ipsilateral acute anterior circulation infarcts identified on MRI were classified as symptomatic (STA), and those without infarcts as asymptomatic (ATA). Variables were selected via univariate analysis and LASSO regression to construct a multivariate logistic regression model. Model performance was evaluated by ROC analysis, confusion matrix, calibration curves, and clinical decision curves, followed by external validation.

resultsExternal validation of the final model showed an area under the ROC curve (AUC) of 0.810, with a sensitivity of 80.8% and specificity of 65.3%, indicating robust predictive performance and good clinical applicability.

conclusionsThe multidimensional predictive model integrating DE-CTA-derived carotid plaque features, PVAT metrics, and serum lipid parameters effectively predicts acute stroke risk, providing a reliable quantitative tool for early screening and clinical intervention.

Indexed as

Adipose TissueCarotid StenosisComputed Tomography AngiographyLipidsPlaque, AtheroscleroticStrokeAgedBiomarkersFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesRisk AssessmentRisk FactorsBiomarkersLipidsAcute strokeDual-energy CTAIntraplaque hemorrhagePerivascular adipose tissuePlaque vulnerability

Identifiers

PMID40773059

What Socratic holds

Textmetadata
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Registered trials

None linked

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.