Abstract
BACKGROUND: Heparin resistance (HR) is a common finding in pediatric cardiac surgery and generally refers to decreased sensitivity to heparin. Antithrombin (AT) deficiency is considered the primary mechanism of HR; however, the etiology of HR may be multifactorial. Early identification of HR might help optimize heparin anticoagulation management. This study aimed to develop a predictive nomogram for HR in neonates and young infants undergoing cardiac surgery. METHODS: From January 2020 to August 2022, a total of 296 pediatric patients 1 to 180 days of age were included in this retrospective study. The patients were randomly divided into development and validation cohorts in a 7:3 ratio. Univariable logistic regression and the Least Absolute Shrinkage and Selection Operator (LASSO) regularization were used for variable selection. A multivariable logistic regression was performed to identify predictors and establish a nomogram to predict HR risk. Discrimination, calibration, and clinical usefulness were assessed in the development and validation cohorts. RESULTS: After the multistep variable selection, AT activity, platelet count, and fibrinogen were predictors for HR in neonates and young infants. The prediction model constructed using these 3 factors achieved an area under the receiver operating characteristic curve (ROC-AUC) of 0.874 and 0.873 in the development and validation cohorts. The Hosmer-Lemeshow test did not find evidence of a lack of fit ( P = .768). The calibration curve of the nomogram was close to the ideal diagonal line. Furthermore, the model performed well in neonate and infant subgroups. CONCLUSIONS: A nomogram based on preoperative variables was developed to predict the HR risk in neonates and young infants undergoing cardiac surgery. This provides clinicians with a simple tool for the early prediction of HR, which may help optimize heparin anticoagulation strategies in this vulnerable patient population.