Department of Pediatrics, University of Texas Health San Antonio, San Antonio, Texas, USA.
Department of Biostatistics, Epidemiology and Molecular Pathology, Università Campus Bio-Medico di Roma, Rome, Italy.
Neonatology. 2022;119(4):418-427. doi: 10.1159/000524729. Epub 2022 May 20.
Understanding factors that associate with neonatal death may lead to strategies or interventions that can aid clinicians and inform families.
The aim of the study was to develop an early prediction model of neonatal death in extremely low gestational age (ELGA, <28 weeks) neonates.
A predictive cohort study of ELGA neonates was derived from the Swedish Neonatal Quality Register between the years 2011 to May 2021. The goal was to use readily available clinical variables, collected within the first hour of birth, to predict in-hospital death. Data were split into a train cohort (80%) to build the model and tested in 20% of randomly selected neonates. Model performance was assessed via area under the receiver operating characteristic curve (AUC) and compared to validated mortality prediction models and an external cohort of neonates.
Among 3,752 live-born extremely preterm infants (46% girls), in-hospital mortality was 18% (n = 685). The median gestational age and birth weight were 25.0 weeks (interquartile range [IQR] 24.0, 27.0) and 780 g (IQR 620, 940), respectively. The proposed model consisted of three variables: birth weight (grams), Apgar score at 5 min of age, and gestational age (weeks). The BAG model had an AUC of 76.9% with a 95% confidence interval (CI) (72.6%, 81.3%), while birth weight and gestational age had an AUC of 73.1% (95% CI: 68.4%,77.9%) and 71.3% (66.3%, 76.2%). In the validation cohort, the BAG model had an AUC of 68.9%.
The BAG model is a new mortality prediction model in ELGA neonates that was developed using readily available information.
了解与新生儿死亡相关的因素可能会为临床医生提供策略或干预措施，并为家庭提供信息。
本研究旨在为极早早产儿（<28 周）建立新生儿死亡的早期预测模型。
这是一项来自瑞典新生儿质量登记处的预测性队列研究，时间范围为 2011 年至 2021 年 5 月。该研究的目的是使用出生后第一个小时内收集的易于获得的临床变量来预测院内死亡。数据被分为训练队列（80%）来建立模型，并在随机选择的 20%的新生儿中进行测试。通过接受者操作特征曲线下的面积（AUC）来评估模型性能，并与验证的死亡率预测模型和外部新生儿队列进行比较。
在 3752 名活产极早产儿中（46%为女孩），院内死亡率为 18%（n=685）。中位胎龄和出生体重分别为 25.0 周（四分位距[IQR]24.0，27.0）和 780g（IQR 620，940）。所提出的模型由三个变量组成：出生体重（克）、5 分钟时的 Apgar 评分和胎龄（周）。BAG 模型的 AUC 为 76.9%，95%置信区间（CI）为 72.6%至 81.3%，而出生体重和胎龄的 AUC 分别为 73.1%（95%CI：68.4%，77.9%）和 71.3%（66.3%，76.2%）。在验证队列中，BAG 模型的 AUC 为 68.9%。
BAG 模型是一种新的极早早产儿死亡率预测模型，它是使用易于获得的信息开发的。
