Evidence map›Paper›PMID 41663955›Full record

ArticleBMC cardiovascular disorders2026

Development and validation of a prediction model for early major adverse cardiovascular events in children undergoing surgical repair of supravalvular aortic stenosis.

Caiyi Wei, Jie Liu, Fengbo Pei, Bo Peng, Lizhi Lv, Lixue Zhang, Qing Gao, Qiang Wang, Yi Shi, Simeng Zhang

Abstract readValidation StudyMulticenter Study
In one paragraph

Article in BMC cardiovascular disorders, 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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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Caiyi Wei *Department of Cardiac Surgery, Peking University People's Hospital, Beijing, China.
Jie Liu *Department of Vascular Surgery, Chinese PLA General Hospital, Beijing, China.
Fengbo Pei *Department of Cardiac Surgery, Peking University People's Hospital, Beijing, China.
Bo PengDepartment of Cardiac Surgery, National Center for Cardiovascular Diseases and Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Lizhi LvDepartment of Pediatric Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
Lixue ZhangDepartment of Cardiac Surgery, Peking University People's Hospital, Beijing, China.
Qing GaoDepartment of Cardiac Surgery, Peking University People's Hospital, Beijing, China.
Qiang WangDepartment of Pediatric Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China. wq.cory@163.com.
Yi ShiDepartment of Cardiac Surgery, Peking University People's Hospital, Beijing, China. 13522720660@126.com.
Simeng ZhangDepartment of Cardiac Surgery, Peking University People's Hospital, Beijing, China. littlestephanie@126.com.

Funding

Beijing Nova Program 20230484441Peking University People's Hospital Talent Introduction Research Start-up Fund 2022-T-01
6 · The paper itself

Abstract

backgroundSurgical therapy of supravalvular aortic stenosis (SVAS) is associated with low overall early mortality but high incidence of postoperative adverse cardiac events. The aims of this study were to develop and validate a predictive model for major adverse cardiovascular events (MACE) in patients undergoing surgical repair of SVAS.

methodsThis study included 262 patients who underwent surgical repair of SVAS between 2002 and 2019 in Beijing and Yunnan, China. MACE occurred during postoperative hospitalization or within 30 days after SVAS repair. Multivariate logistic regression was used to select prognostic factors for MACE and construct a nomogram. The receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) were used to assess the predictive performance of the nomogram.

resultsAge, sex, body surface area, cardiopulmonary bypass time, and aortic valve z score were identified as prognostic factors. These five prognostic factors were used to construct the prediction nomogram. The area under the curve of the model was 0.859 (95% CI: 0.765–0.953). For the bootstrap sampling validation, the corrected C-index was 0.823, and the DCA showed the nomogram was clinically beneficial across a range of thresholds of 2–66%.

conclusionsA novel nomogram was developed to predict major adverse cardiovascular events in patients undergoing surgical repair of SVAS, which may serve as an effective tool to assist clinicians in individualized prognostic assessment.

trial registrationThis study was retrospectively registered at www.chictr.org.cn on May 16, 2021 (ChiCTR2100046494).

Indexed as

Aortic Stenosis, SupravalvularCardiac Surgical ProceduresDecision Support TechniquesNomogramsAge FactorsChildChild, PreschoolChinaFemaleHumansInfantMalePredictive Value of TestsReproducibility of ResultsRetrospective StudiesRisk AssessmentAdverse cardiovascular eventsNomogramSupravalvular aortic stenosisSurgical repair

Identifiers

PMID41663955
PMCPMC12983654

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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.