关键词: 先天性心脏病, 体外循环, 低体温, 预测风险模型, 列线图

Abstract: Objective To investigate the risk factors of hypothermia in children with congenital heart disease (CHD) after cardiopulmonary bypass (CPB) rewarming, and to establish an individualized linear model to predict the risk of postoperative hypothermia. Methods The clinical data of children with CHD who underwent CPB between January 1 , 2019 and April 30 , 2019 were retrospectively analyzed. The independent risk factors of hypothermia after CPB in children with CHD were analyzed by binary logistic regression model. The R software was used to construct the prediction risk nomogram, and the prediction efficiency of the model was evaluated by ROC curve. Results Among the 711 children, 239 children ( 33 . 6 %) met with hypothermia after surgery during the study period, including 128 boys and 111 girls, with a median age of 13 months ( 5 . 7 - 36 months). The results of binary logistic regression analysis showed that the preoperative high nutritional score, longer fasting time, lower CPB flow temperature and CPB shutdown temperature < 36 ℃ were independent risk factors for hypothermia after CPB reheating (P< 0 . 05 ). Based on the above independent risk factors, the nomogram model was established. The area under ROC curve (AUC) of the model was 0 . 887 ( 95 %CI: 0 . 858 ~ 0 . 915 ), the Youden index was 0 . 734 , the sensitivity was 0 . 836 , and the specificity was 0 . 898 . Based on existing data, the total prediction accuracy, sensitivity and specificity were 79 . 8%, 57 . 1% and 90 . 9 % respectively. Conclusions Based on the four independent risk factors of preoperative nutrition, fasting time, CPB regimen, and CPB shutdown temperature, the nomogram model has a good predictive performance, and has a good clinical application value in the prediction of unplanned hypothermia after CPB reheating in children with CHD.

Key words: congenital heart disease, cardiopulmonary bypass, hypothermia, predictive risk model, nomogram