Evidence map›Paper›PMID 41291378›Full record

ArticleClinical rheumatology2026

Predictive modeling of cardiovascular risk in systemic sclerosis: a single-center retrospective study integrating clinical and imaging data.

Jingfeng Huang, Le Yang, Binhua Xie, Xiaowei Lu, Fangjie Shen, Xiaodong Zheng, Qianjiang Ding, Yuning Pan, Xinzhong Ruan

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Article in Clinical rheumatology, 2026. 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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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Jingfeng HuangDepartment of Radiology, The First Affiliated Hospital of Ningbo University, No.59 Liuting Street, Ningbo, 315000, China.
Le YangDepartment of Nuclear Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, 315000, China.
Binhua XieDepartment of Rheumatology, The First Affiliated Hospital of Ningbo University, Ningbo, 315000, China.
Xiaowei LuDepartment of Radiology, The First Affiliated Hospital of Ningbo University, No.59 Liuting Street, Ningbo, 315000, China.
Fangjie ShenDepartment of Radiology, The First Affiliated Hospital of Ningbo University, No.59 Liuting Street, Ningbo, 315000, China.
Xiaodong ZhengDepartment of Radiology, The First Affiliated Hospital of Ningbo University, No.59 Liuting Street, Ningbo, 315000, China.
Qianjiang DingDepartment of Radiology, The First Affiliated Hospital of Ningbo University, No.59 Liuting Street, Ningbo, 315000, China.
Yuning PanDepartment of Radiology, The First Affiliated Hospital of Ningbo University, No.59 Liuting Street, Ningbo, 315000, China.
Xinzhong RuanDepartment of Radiology, The First Affiliated Hospital of Ningbo University, No.59 Liuting Street, Ningbo, 315000, China. dyyyfsk@yeah.net.ORCID http://orcid.org/0000-0003-0905-5879

Funding

Medical Science and Technology Project of Zhejiang Province 2025KY1331Ningbo Public Welfare Science and Technology Program Project 2022S028
6 · The paper itself

Abstract

backgroundCardiovascular disease (CVD) is a leading cause of mortality in systemic sclerosis (SSc). Early risk identification is crucial for improving prognosis.

objectivesThe aim of this study was to develop a clinical prediction model for assessing cardiovascular disease risk in SSc patients via integrating clinical and imaging data.

methodsWe retrospectively analyzed the occurrence of CVD among 245 SSc patients and 245 controls. SSc patients were stratified by CVD event. Independent predictors of CVD risk were identified using Cox regression analysis in SSc patients. Receiver operator characteristic (ROC) curves assessed the model's predictive performance. Kaplan-Meier (KM) curves evaluated the association of these factors with event-free survival.

resultsSSc patients exhibited significantly higher CVD events than controls. Significant differences were observed between SSc patients with and without events regarding age, sex, disease duration, modified Rodnan skin score (mRSS), erythrocyte sedimentation rate (ESR), anti-Scl-70 antibody (ATA), anti-U3 RNP, pulmonary arterial hypertension (PAH), interstitial lung disease (ILD), coronary artery calcium score (CACS) and epicardial adipose tissue (EFV). Cox regression identified CACS, mRSS, EFV, and ATA as independent predictors of increased CVD risk. The combined model (CACS, EFV, mRSS, ATA) achieved an area under the curve (AUC) of 0.910, showing high accuracy for predicting CVD events in SSc. KM analysis confirmed significantly reduced event-free survival in patients with high CACS, high mRSS, ATA positivity, or high EFV (all P < 0.05).

conclusionCACS, mRSS, EFV, and ATA are independent risk factors for CVD events in SSc patients. A model combining these factors effectively predicts CVD incidence in this population. Key Points • CACS, mRSS, EFV, and ATA were identified as independent predictors of cardiovascular events. • The combination of CACS, EFV, mRSS, and ATA yielded a high AUC of 0.910, demonstrating strong predictive capability with high specificity and sensitivity for cardiovascular events in SSc individuals.

Indexed as

Cardiovascular DiseasesScleroderma, SystemicAdultAgedFemaleHeart Disease Risk FactorsHumansMaleMiddle AgedPrognosisProportional Hazards ModelsRetrospective StudiesRisk AssessmentRisk FactorsROC CurveAnti-Scl-70 antibodyCardiovascular eventsCoronary artery calcification scoreEpicardial fat volumeModified Rodnan skin scoreSystemic sclerosis

Identifiers

PMID41291378

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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.