Evidence mapPaperPMID 41272002Full record

ArticleScientific reports2025

Exploring the predictive values of ABSI and BRI in premature coronary artery disease based on a real world study.

Wan-Xin Shi, Yuan Liu, Xin-Qiao Wei, Yan Min, Ying-Hong Weng, Yan-Li Liu, Yu-Jie Guo, Liu Miao

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Article in Scientific reports, 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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8 authors.

Wan-Xin Shi *Department of Cardiology, Liuzhou People's Hospital, Affiliated of Guangxi Medical University, 8 Wenchang Road, Liuzhou, 545006, Guangxi, China.
Yuan Liu *Department of Cardiology, Liuzhou People's Hospital, Affiliated of Guangxi Medical University, 8 Wenchang Road, Liuzhou, 545006, Guangxi, China.
Xin-Qiao WeiDepartment of Cardiology, Liuzhou People's Hospital, Affiliated of Guangxi Medical University, 8 Wenchang Road, Liuzhou, 545006, Guangxi, China.
Yan MinDepartments of Nephrology, Liuzhou People's Hospital, Affiliated of Guangxi Medical University, 8 Wenchang Road, Liuzhou, 545006, Guangxi, China.
Ying-Hong WengDepartment of Traditional Chinese Medicine, Liuzhou People's Hospital, Affiliated of Guangxi Medical University, 8 Wenchang Road, Liuzhou, 545006, Guangxi, China.
Yan-Li LiuDepartment of Cardiology, Liuzhou People's Hospital, Affiliated of Guangxi Medical University, 8 Wenchang Road, Liuzhou, 545006, Guangxi, China.
Yu-Jie GuoDepartment of Cardiology, Liuzhou People's Hospital, Affiliated of Guangxi Medical University, 8 Wenchang Road, Liuzhou, 545006, Guangxi, China.
Liu MiaoDepartment of Cardiology, Liuzhou People's Hospital, Affiliated of Guangxi Medical University, 8 Wenchang Road, Liuzhou, 545006, Guangxi, China. dr.miaoliu@qq.com.

Funding

Guangxi Medical High-level Backbone Talent Program G201903047Guangxi self-financing research projects Z20190738, Z20200165 and Z20190083National Natural Science Foundation of Guangxi 2020GXNSFAA297003Project of Liuzhou Science and Technology 2020NBAB0818The funding of National Natural Science Foundation of China 82060072the project of Liuzhou people's Hospital LYRGCC202107, LYRGCC202116 and LYRGCC202203
6 · The paper itself

Abstract

Exploring predictors of premature coronary artery disease (PCAD) based on a real-world study. We employed 50,190 individuals and collected their baseline characteristics, including medical history, anthropometric measurements, and blood biochemistry indicators from 2001 to 2018. PCAD were screened strictly based on diagnostic and exclusion criteria, and ultimately 14,469 individuals (including 387 in coronary angiography for the diagnosis of PCAD and 14082 in the control who thought that the degree of coronary stenosis did not meet diagnostic criteria) were included in analyzed. Propensity score matching (PSM) was used to assess these patients. We used multivariable Cox proportional hazards regression to identify risk factors and developed a nomogram to estimate the risk of major adverse cardiac events (MACE) over the 36-month follow-up period. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of the risk factors. All patients were followed up for 36 months,and a survival curve was plotted. Before PSM matching, PCAD patients exhibited significantly higher levels of several risk factors, including body mass index (BMI), waist circumference (WC), triglycerides (TG), hemoglobin A1c (HbA1c), glucose, and various cardiovascular indicators such as systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP), compared to the control group (P < 0.001). After PSM matching, only the body roundness index (BRI) remained significantly higher in PCAD patients (P < 0.001).In Cox regression analysis and nomogram development, gender, age, smoking, serum creatinine, aspartate aminotransferase (AST), ABSI, and BRI were identified as significant risk factors for PCAD (P < 0.01-0.05), both before and after PSM matching. The ROC curve analysis showed that combining ABSI and BRI improved diagnostic performance, with an area under the curve (AUC) of 0.73.Survival analysis revealed that high ABSI and BRI significantly predicted poorer prognosis in PCAD patients, regardless of PSM matching (P < 0.05). Further survival analysis combining ABSI and BRI demonstrated that, after PSM matching, high ABSI consistently indicated a worse prognosis, irrespective of BRI levels. ABSI and BRI are high-risk factors for PCAD, and ABSI combined with BRI with a higher diagnosis. High ABSI is associated with poor prognosis in PCAD patients, and the exact mechanism needs to be further explored.

Indexed as

Coronary Artery DiseaseAdultBlood PressureBody Mass IndexCoronary AngiographyFemaleHumansMaleMiddle AgedNomogramsPredictive Value of TestsPrognosisPropensity ScoreProportional Hazards ModelsRisk FactorsROC CurveABSIBRIPCADPropensity score matchingReal-world study

Identifiers

PMID41272002
PMCPMC12639007

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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.