Neonatology Department, Hospital Sant Joan de Déu, BCNatal, Hospital Sant Joan de Déu-Hospital, Barcelona University, Barcelona, Spain.
Newborn Research Centre, The Royal Women's Hospital, Melbourne & University of Melbourne, Melbourne, Australia.
PLoS One. 2020 Jul 9;15(7):e0235794. doi: 10.1371/journal.pone.0235794. eCollection 2020.
Predictive models for preterm infant mortality have been developed internationally, albeit not valid for all populations. This study aimed to develop and validate different mortality predictive models, using Spanish data, to be applicable to centers with similar morbidity and mortality.
Infants born alive, admitted to NICU (BW<1500 g or GA<30 w), and registered in the SEN1500 database, were included. There were two time periods; development of the predictive models (2009-2012) and validation (2013-2015). Three models were produced; prenatal (1), first 24 hours of life (2), and whilst admitted (3). For the statistical analysis, hospital mortality was the dependent variable. Significant variables were used in multivariable regression models. Specificity, sensitivity, accuracy, and area under the curve (AUC), for all models, were calculated.
Out of 14953 included newborns, 2015 died; 373 (18.5%) in their first 24 hours, 1315 (65.3%) during the first month, and 327 (16.2%) thereafter, before discharge. In the development stage, mortality prediction AUC was 0.834 (95% CI: 0.822-0.846) (p<0.001) in model 1 and 0.872 (95% CI: 0.860-0.884) (p<0.001) in model 2. Model 3's AUC was 0.989 (95% CI: 0.983-0.996) (p<0.001) and 0.942 (95% CI: 0.929-0.956) (p<0.001) during the 0-30 and >30 days of life, respectively. During validation, models 1 and 2 showed moderate concordance, whilst that of model 3 was good.
Using dynamic models to predict individual mortality can improve outcome estimations. Development of models in the prenatal period, first 24 hours, and during hospital admission, cover key stages of mortality prediction in preterm infants.
国际上已经开发出了针对早产儿死亡率的预测模型，但这些模型并不适用于所有人群。本研究旨在使用西班牙数据开发和验证不同的死亡率预测模型，以适用于具有类似发病率和死亡率的中心。
纳入在新生儿重症监护病房（BW<1500 克或 GA<30 周）中存活并登记在 SEN1500 数据库中的新生儿。研究分为两个时期；预测模型的开发（2009-2012 年）和验证（2013-2015 年）。生成了三个模型；产前（1）、生命最初 24 小时（2）和住院期间（3）。在统计分析中，住院死亡率为因变量。多变量回归模型中使用了有显著意义的变量。计算了所有模型的特异性、敏感性、准确性和曲线下面积（AUC）。
在纳入的 14953 例新生儿中，有 2015 例死亡；其中 373 例（18.5%）在生命最初 24 小时内死亡，1315 例（65.3%）在第一个月内死亡，327 例（16.2%）在出院前死亡。在开发阶段，模型 1 的死亡率预测 AUC 为 0.834（95%CI：0.822-0.846）（p<0.001），模型 2 的 AUC 为 0.872（95%CI：0.860-0.884）（p<0.001）。模型 3 的 AUC 在 0-30 天和>30 天的分别为 0.989（95%CI：0.983-0.996）（p<0.001）和 0.942（95%CI：0.929-0.956）（p<0.001）。在验证阶段，模型 1 和模型 2 显示出中等一致性，而模型 3 的一致性较好。
使用动态模型预测个体死亡率可以提高预后估计。在产前、生命最初 24 小时和住院期间开发模型，可以涵盖早产儿死亡率预测的关键阶段。
