Risk factors of postoperative neurodevelopmental abnormalities in neonates with critical congenital heart disease

Zhejiang Da Xue Xue Bao Yi Xue Ban. 2023 Feb 25;52(1):110-116. doi: 10.3724/zdxbyxb-2022-0061.
[Article in English, Chinese]

Abstract

Objectives: To investigate the risk factors of postoperative neuro-developmental abnormalities in neonates with critical congenital heart disease (CCHD).

Methods: Clinical data of 50 neonates with CCHD admitted in the Cardiac Intensive Care Unit, The Children's Hospital, Zhejiang University School of Medicine from November 2020 to December 2021 were retrospectively analyzed. Neurological assessment was performed with cranial ultrasonography, CT/MRI, video electroencephalogram and clinical symptoms before and after surgical treatment for all patients, and neurodevelopmental abnormalities were documented. Binary logistic stepwise regression was used to analyze risk factors of postoperative new-onset neurodysplasia in children with CCHD, and the predictive value of the risk factors on postoperative neurodevelopmental abnormalities were evaluated using the receiver operating characteristic (ROC) curve.

Results: Neurodevelopmental abnormalities were detected in 22 cases (44.0%) and not detected in 28 cases (56.0%) before surgery. There were no significant differences in gender, birth weight, age at admission, gestational age, preoperative SpO2 level, prematurity, cyanotic congenital heart disease, and ventilator support between the two groups (all P>0.05). After surgery, there were 22 cases (44.0%) with new-onset neurological abnormalities and 28 cases (56.0%) without new-onset abnormalities. Multivariate logistic regression analysis showed that postoperative 24 h peak lactic acid (OR=1.537, 95%CI: 1.170-2.018, P<0.01) and postoperative length of ICU stay (OR=1.172, 95%CI:1.031-1.333, P<0.05) were independent risk factors for postoperative new-onset neurodevelopmental abnormalities. The area under ROC curve (AUC) of the postoperative 24 h peak lactic acid for predicting the new-onset neurological abnormalities after operation was 0.829, with cut-off value of 4.95 mmol/L. The diagnostic sensitivity and specificity were 90.0% and 64.3%, respectively. The AUC of postoperative length of ICU stay for predicting the new-onset neurological abnormalities after operation was 0.712, with cut-off value of 18.0 d. The diagnostic sensitivity and specificity were 50.0% and 96.4%, respectively. The AUC of the combination of the two indicators was 0.917, the diagnostic sensitivity and specificity were 95.5% and 64.3%, respectively.

Conclusions: The incidence of neurodysplasia in neonatal CCHD is high, and new neurological abnormalities may occur after surgery. The postoperative 24 h peak lactic acid and postoperative length of ICU stay are risk factors for new-onset neurodysplasia after surgery. The combination of the two indicators has good predictive value for neurodevelopmental outcomes after surgery in CCHD infants.

目的: 分析总结新生儿危重先天性心脏病(CCHD)围术期神经功能特点及术后新发神经发育异常的影响因素。方法: 回顾性分析2020年11月至2021年12月浙江大学医学院附属儿童医院心脏重症监护中心收治的50例CCHD新生儿的围手术期资料,利用头颅超声、头颅CT/MRI、视频脑电图及临床症状进行术前和术后神经系统评估,任何一项有阳性意义即判定为神经发育异常。采用二元logistic逐步回归分析CCHD患儿术后新发神经发育异常的影响因素,并采用受试者操作特征曲线(ROC曲线)评估影响因素对术后新发神经发育异常的预测价值。结果: 术前神经发育异常组22例(44.0%),正常组28例(56.0%),两组在性别、出生体重、入院年龄、胎龄、术前动脉血氧饱和度水平、是否早产、是否紫绀型先天性心脏病、是否呼吸机支持等方面差异无统计学意义(均P>0.05)。术后新发神经发育异常组22例(44.0%),无新发异常组28例(56.0%),多因素logistic回归分析结果显示,术后24 h乳酸峰值(OR=1.537,95%CI:1.170~2.018,P<0.01)和术后重症监护室(ICU)住院时间(OR=1.172,95%CI:1.031~1.333,P<0.05)是术后新发神经发育异常的危险因素。ROC曲线分析结果显示,术后24 h乳酸峰值预测术后新发神经发育异常的AUC为0.829,最佳截断值为4.95 mmol/L,诊断敏感度为90.9%、特异度为64.3%;术后ICU住院时间预测术后新发神经发育异常的AUC为0.712,最佳截断值为18.0 d,诊断敏感度为50.0%、特异度为96.4%;两者联合检测预测术后新发神经发育异常的AUC为0.917,诊断敏感度为95.5%、特异度为64.3%。结论: CCHD患儿围术期神经发育不良风险较高,部分患儿术前已存在异常。术后24 h乳酸峰值和术后ICU住院时间是术后神经发育不良的危险因素,两者联合检测对术后不良神经发育结局有较好的预测价值。.

Keywords: Critical congenital heart disease; Neonate; Neurodevelopment; Perioperative period; Risk factor.

MeSH terms

  • Child
  • Heart Defects, Congenital* / surgery
  • Humans
  • Infant
  • Infant, Newborn
  • Lactic Acid
  • Prognosis
  • ROC Curve
  • Retrospective Studies
  • Risk Factors

Substances

  • Lactic Acid