Division of Neonatology and Pediatric Intensive Care, Children's University Hospital of Geneva and University of Geneva, Geneva, Switzerland.
Université Paris Diderot, Sorbonne Paris Cité, INSERM U1141, Paris, France.
Neonatology. 2021;118(4):385-393. doi: 10.1159/000515898. Epub 2021 May 18.
Early prediction of survival without bronchopulmonary dysplasia (BPD) at 36 weeks of postmenstrual age remains challenging for infants born extremely preterm. We aimed to provide a new predictive model including variables available only at or soon after birth based on the literature and existing models.
We conducted a systematic review to identify all variables considered to be significant predictors of BPD and survival at birth in extremely preterm infants. We then assessed the external validity of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Neonatal Research Network BPD estimator on the PREMILOC cohort, a recent French study with a large sample of extremely preterm infants and a vast number of variables at baseline. Finally, we attempted to improve this model by testing the added value of other early predictors reported in previous studies.
Restricted to baseline predictors, the NICHD Neonatal Research Network BPD estimator confirmed its calibration and fair discrimination (area under the receiver operating characteristic [auROC] [95% CI] = 0.73 [0.68-0.77] when used with a published model and auROC [95% CI] = 0.77 [0.73-0.81] when fitted to the PREMILOC dataset). We were able to improve the discriminatory power by adding candidate variables at birth associated with BPD in previous studies. The modified best predicting model included gestational age at birth, birthweight, respiratory support at baseline, gender, center effect, and multiple pregnancy as baseline predictors. This model showed significantly better discrimination (auROC [95% CI] = 0.85 [0.82-0.88]) and better confirmed calibration (Hosmer-Lemeshow test, p = 0.45).
This new model, based on 6 early predictors, appears to improve the prediction soon after birth of BPD-free survival in extremely preterm infants.
对于极早产儿而言,在孕龄 36 周前预测没有支气管肺发育不良(BPD)的生存情况仍然具有挑战性。我们旨在提供一种新的预测模型,该模型基于文献和现有模型,仅纳入出生时或出生后不久的可用变量。
我们进行了系统综述,以确定所有被认为是极早产儿出生时 BPD 和生存的重要预测因素的变量。然后,我们评估了 Eunice Kennedy Shriver 国立儿童健康与人类发展研究所(NICHD)新生儿研究网络 BPD 估测器在 PREMILOC 队列中的外部有效性,PREMILOC 队列是一项最近的法国研究,其中包含大量的极早产儿样本和大量的基线变量。最后,我们通过测试以前研究中报告的其他早期预测因子的附加值,尝试改进该模型。
在基线预测因子的限制下,NICHD 新生儿研究网络 BPD 估测器证实了其校准和良好的区分能力(使用发表的模型时的接收器工作特征曲线下面积[auROC] [95%CI] = 0.73 [0.68-0.77],拟合 PREMILOC 数据集时 auROC [95%CI] = 0.77 [0.73-0.81])。我们能够通过添加与之前研究中 BPD 相关的出生时的候选变量来提高区分能力。经过修改的最佳预测模型包括出生时的胎龄、出生体重、基线时的呼吸支持、性别、中心效应和多胎妊娠作为基线预测因子。该模型显示出明显更好的区分能力(auROC [95%CI] = 0.85 [0.82-0.88])和更好的校准验证(Hosmer-Lemeshow 检验,p = 0.45)。
这个新模型基于 6 个早期预测因子,似乎可以提高极早产儿出生后不久预测无 BPD 生存的能力。