Open Access

ARTICLE

A Prediction Nomogram for Early Major Adverse Events after Cardiac Surgery in Infants with Congenital Heart Disease: A Retrospective Study

Fan Yang^1,#, Xia Li^1,#, Zhiyuan Zhu^1,#, Shilin Wang^1,#, Zhongyuan Lu¹, Chao Yue², Leilei Duan¹, Xu Wang^1,*

1 Department of Pediatric Intensive Care Unit, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
2 Department of Cardiac Surgery, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

* Corresponding Author: Xu Wang. Email:
# These authors contributed equally to this work

Structural and Congenital Heart Disease 2026, 21(3), 7 https://doi.org/10.32604/schd.2026.075534

Received 03 November 2025; Accepted 28 July 2026; Issue published 31 July 2026

Abstract

Background: Early major adverse events (MAEs) after cardiac surgery are associated with substantial postoperative morbidity and mortality in infants with congenital heart disease (CHD). Early identification of patients at increased risk may facilitate timely intervention and optimize postoperative management. This study aimed to identify perioperative predictors of early MAEs and to develop a nomogram for individualized postoperative risk assessment. Methods: This single-center retrospective study included 766 infants with CHD who underwent cardiac surgery with cardiopulmonary bypass at Beijing Fuwai Hospital between January 2020 and December 2021. Early MAEs were defined as the occurrence of at least one major adverse event within 48 h after surgery, including unplanned reoperation, acute renal failure, sudden circulatory arrest, emergency chest reopening, extracorporeal membrane oxygenation, low cardiac output syndrome, refractory tachycardia, or all-cause mortality. Patients were randomly assigned to training and testing cohorts in a 7:3 ratio. Least absolute shrinkage and selection operator (LASSO) regression was used for feature selection, followed by multivariable logistic regression to construct the prediction nomogram. Model performance was evaluated by discrimination, calibration, and decision curve analysis. Results: Among the 766 infants included in the study, 144 (18.8%) experienced at least one early MAE. Five independent predictors were retained in the final model: body weight, aortic cross clamp time, postoperative 8th hour lactate, off CPB blood glucose and postoperative 4 h urine output. The area under the receiver operating characteristic curve was 0.781 in the training cohort and 0.764 in the testing cohort. Calibration analysis demonstrated good agreement between predicted and observed risks, with calibration-in-the-large values of −0.021 and −0.085 and calibration slopes of 0.958 and 0.931 in the training and testing cohorts, respectively. Decision curve analysis favorable potential clinical utility across a wide range of threshold probabilities. Conclusions: A nomogram incorporating five routinely available perioperative variables demonstrated moderate discrimination and satisfactory calibration for predicting early MAEs in infants with CHD after cardiac surgery. External validation is warranted before routine clinical implementation.

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