Wu Yu-Li, Jing Yong-Le, Liu Wei-Hua, Gong Xin-Yuan, Che Lu, Xue Jing-Yi, Li Tian-Ying, Jiang Lei, Huang Xiao-Yu, Yu Wen-Li, Weng Yi-Qi
Department of Anesthesiology, Tianjin First Central Hospital, Tianjin 300192, China.
Department of Cardiology, Tianjin First Central Hospital, Tianjin 300192, China.
World J Gastrointest Surg. 2025 Apr 27;17(4):103263. doi: 10.4240/wjgs.v17.i4.103263.
Myocardial injury is common during liver transplantation and is associated with poor outcomes. The development of a reliable prediction system for this type of injury is crucial for reducing the incidence of cardiac complications in children receiving living donor liver transplantation (LDLT). However, establishing a practical myocardial injury prediction system for children with biliary atresia remains a considerable challenge.
To create and validate a nomogram model for predicting myocardial injury in children with biliary atresia who received LDLT.
Clinical data from pediatric patients who received LDLT for biliary atresia between November, 2019 and January, 2022 were retrospectively analyzed. The complete dataset was randomly partitioned into a training set and a validation set at a ratio of 7:3. Least absolute shrinkage and selection operator regression was used to preliminarily screen out the predictors of myocardial injury. The prediction model was established multivariable logistic regression and presented in the form of a nomogram.
This study included 321 patients, 150 (46.7%) of whom had myocardial injury. The participants were randomly allocated into two groups: A training group consisting of 225 patients and a validation group comprising 96 patients. The predictors in this nomogram included the preoperative neutrophil-to-lymphocyte ratio, high sensitivity C-reactive protein level, pediatric end-stage liver disease score and postreperfusion syndrome. The area under the curve for predicting myocardial injury was 0.865 in the training set and 0.856 in the validation set. The calibration curve revealed that the predicted values were very close to the actual values in the two sets. Decision curve analysis revealed that the prediction model offered a favorable net benefit.
The nomogram developed in this study effectively predicts myocardial injury in pediatric LDLT patients, showing good accuracy and potential for clinical application.
心肌损伤在肝移植过程中很常见，且与不良预后相关。开发一种针对此类损伤的可靠预测系统对于降低接受活体肝移植（LDLT）儿童的心脏并发症发生率至关重要。然而，为胆道闭锁患儿建立实用的心肌损伤预测系统仍然是一项巨大挑战。
创建并验证一个用于预测接受LDLT的胆道闭锁患儿心肌损伤的列线图模型。
对2019年11月至2022年1月期间因胆道闭锁接受LDLT的儿科患者的临床数据进行回顾性分析。完整数据集以7:3的比例随机分为训练集和验证集。采用最小绝对收缩和选择算子回归初步筛选心肌损伤的预测因素。通过多变量逻辑回归建立预测模型，并以列线图的形式呈现。
本研究纳入321例患者，其中150例（46.7%）发生心肌损伤。参与者被随机分为两组：由225例患者组成的训练组和由96例患者组成的验证组。该列线图中的预测因素包括术前中性粒细胞与淋巴细胞比值、高敏C反应蛋白水平、儿童终末期肝病评分和再灌注综合征。训练集中预测心肌损伤的曲线下面积为0.865，验证集中为0.856。校准曲线显示两组的预测值与实际值非常接近。决策曲线分析表明该预测模型具有良好的净效益。
本研究开发的列线图可有效预测儿科LDLT患者的心肌损伤，具有良好的准确性和临床应用潜力。
