背景:在儿童流感的神经系统并发症中,最严重的是急性坏死性脑病(ANE),高死亡率和神经系统后遗症。ANE的特征在于在发病后1-2天内快速进展至死亡。然而,关于ANE早期诊断的知识是有限的,常被误诊为单纯性癫痫发作/惊厥或轻度急性流感相关性脑病(IAE).
目的:开发并验证早期预测模型,将ANE与两种常见的神经系统并发症区分开来。流感儿童的癫痫发作/惊厥和轻度IAE。
方法:这项回顾性病例对照研究包括ANE患者(中位年龄3.8(2.3,5.4)岁),仅癫痫发作/惊厥(中位年龄2.6(1.7,4.3)岁),或轻度IAE(中位年龄2.8(1.5,6.1)岁)在2012年11月至2020年1月在中国三级儿科医学中心。采用随机森林算法筛选特征并构建预测模型。
结果:在433名患者中,278(64.2%)仅有癫痫/抽搐,106例(24.5%)有轻度IAE,49人(11.3%)患有ANE。模型的判别性能令人满意,模型开发(84.2%)和内部验证(88.2%)的准确率均高于0.80。癫痫/惊厥被错误分类的可能性较小(3.7%,2/54),但轻度IAE(22.7%,5/22)容易被误诊为癫痫/惊厥,和一小部分(4.5%,其中1/22)容易被误诊为ANE。有ANE的孩子,22.2%(2/9)被误诊为轻度IAE,没有人被误诊为癫痫/惊厥。
结论:该模型可以将ANE与癫痫/惊厥区分开,准确率高,与轻度IAE区分开,准确率接近80%,为流感儿童的早期管理提供有价值的信息。
BACKGROUND: Among the neurological complications of influenza in children, the most severe is acute necrotizing encephalopathy (ANE), with a high mortality rate and neurological sequelae. ANE is characterized by rapid progression to death within 1-2 days from onset. However, the knowledge about the early diagnosis of ANE is limited, which is often misdiagnosed as simple seizures/convulsions or mild acute influenza-associated encephalopathy (IAE).
OBJECTIVE: To develop and validate an early prediction model to discriminate the ANE from two common neurological complications, seizures/convulsions and mild IAE in children with influenza.
METHODS: This retrospective case-control study included patients with ANE (median age 3.8 (2.3,5.4) years), seizures/convulsions alone (median age 2.6 (1.7,4.3) years), or mild IAE (median age 2.8 (1.5,6.1) years) at a tertiary pediatric medical center in China between November 2012 to January 2020. The random forest algorithm was used to screen the characteristics and construct a prediction model.
RESULTS: Of the 433 patients, 278 (64.2%) had seizures/convulsions alone, 106 (24.5%) had mild IAE, and 49 (11.3%) had ANE. The discrimination performance of the model was satisfactory, with an accuracy above 0.80 from both model development (84.2%) and internal validation (88.2%). Seizures/convulsions were less likely to be wrongly classified (3.7%, 2/54), but mild IAE (22.7%, 5/22) was prone to be misdiagnosed as seizures/convulsions, and a small proportion (4.5%, 1/22) of them was prone to be misdiagnosed as ANE. Of the children with ANE, 22.2% (2/9) were misdiagnosed as mild IAE, and none were misdiagnosed as seizures/convulsions.
CONCLUSIONS: This model can distinguish the ANE from seizures/convulsions with high accuracy and from mild IAE close to 80% accuracy, providing valuable information for the early management of children with influenza.