Evidence map›Paper›PMID 39414918›Full record

ArticleScientific reports2024

Construction of vulnerable plaque prediction model based on multimodal vascular ultrasound parameters and clinical risk factors.

Lei Yan, Xiaojian Ye, Liyun Fu, Wanqing Hou, Shengnan Lin, Hongda Su

Abstract read
In one paragraph

Article in Scientific reports, 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

6 authors.

Lei Yan *Department of Ultrasound, The First Affiliated Hospital of Fujian Medical University, 20# Chazhong Road, Fuzhou, 350005, Fujian, China. yanlei20082336@163.com.
Xiaojian Ye *Department of Ultrasound, The First Affiliated Hospital of Fujian Medical University, 20# Chazhong Road, Fuzhou, 350005, Fujian, China.
Liyun FuDepartment of Ultrasound, The First Affiliated Hospital of Fujian Medical University, 20# Chazhong Road, Fuzhou, 350005, Fujian, China.
Wanqing HouDepartment of Ultrasound, The First Affiliated Hospital of Fujian Medical University, 20# Chazhong Road, Fuzhou, 350005, Fujian, China.
Shengnan LinDepartment of Ultrasound, The First Affiliated Hospital of Fujian Medical University, 20# Chazhong Road, Fuzhou, 350005, Fujian, China.
Hongda SuDepartment of Ultrasound, The First Affiliated Hospital of Fujian Medical University, 20# Chazhong Road, Fuzhou, 350005, Fujian, China.

Funding

Fujian Provincial Health Technology Project 2020GGB032Leading Project Foundation of Science and Technology, Fujian Province 2022Y0010
6 · The paper itself

Abstract

The rupture of vulnerable plaque (VP) are significant pathogenic factors leading to cardiovascular and cerebrovascular diseases. This study aims to construct a vulnerable plaque prediction model (VPPM) by combining multimodal vascular ultrasound parameters and clinical risk factors, and to validate it. A total of 196 atherosclerotic patients who underwent carotid endarterectomy (CEA) from January 2017 to December 2023 were collected and divided into a modeling group (n = 137) and a validation group (n = 59). Clinical information including: hypertension, diabetes, smoking history, and body mass index (BMI) was included in the analysis. All patients underwent carotid ultrasound and contrast-enhanced ultrasound (CEUS) examination after admission, with main ultrasound parameters including thickness, echogenicity types, stenosis degree, and CEUS neovascularization grading of plaques. Independent risk factors for VP in CEA patients were screened through binary Logistic regression analysis, and a prediction model was established along with a nomogram. The calibration curve, receiver-operating characteristic curve (ROC), and decision curve analysis (DCA) were employed to assess the calibration, diagnostic efficacy, and clinical utility of the VPPM model. There were no significant statistical differences in multimodal vascular ultrasound parameters and clinical risk factors between the modeling and validation groups (P > 0.05). Binary Logistic regression analysis identified plaque thickness, echo type, CEUS neovascularization grading, BMI, and smoking history as 5 variables entering the prediction model. The VPPM model showed good diagnostic efficacy, with an area under the ROC curve of 0.959 (95% CI 0.915-0.999). Using the nomogram with a VPPM risk assessment score of 135.42 as the diagnostic cutoff value in the modeling group, the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and Youden index were 88.1%, 94.1%, 14.98, 0.126, and 82.2%, respectively. In the DCA curve, the VPPM model curve was significantly better than two extreme lines, indicating good clinical utility. The VPPM model constructed by integrating multimodal ultrasound parameters and clinical key risk factors has high diagnostic efficacy and is expected to be an auxiliary tool for clinical diagnosis of vulnerable plaques.

Indexed as

Plaque, AtheroscleroticUltrasonographyAgedCarotid ArteriesCarotid StenosisEndarterectomy, CarotidFemaleHumansMaleMiddle AgedNomogramsRisk AssessmentRisk FactorsROC CurveContrast-enhanced ultrasoundMultimodalPrediction modelVascular ultrasoundVulnerable plaque

Identifiers

PMID39414918
PMCPMC11484977

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LicenceCC BY-NC-ND
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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.