Yehya Nadir, Wong Hector R
Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, PA.
Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, OH.
Crit Care Med. 2018 Jan;46(1):e9-e16. doi: 10.1097/CCM.0000000000002754.
The original Pediatric Sepsis Biomarker Risk Model and revised (Pediatric Sepsis Biomarker Risk Model-II) biomarker-based risk prediction models have demonstrated utility for estimating baseline 28-day mortality risk in pediatric sepsis. Given the paucity of prediction tools in pediatric acute respiratory distress syndrome, and given the overlapping pathophysiology between sepsis and acute respiratory distress syndrome, we tested the utility of Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II for mortality prediction in a cohort of pediatric acute respiratory distress syndrome, with an a priori plan to revise the model if these existing models performed poorly.
Prospective observational cohort study.
University affiliated PICU.
Mechanically ventilated children with acute respiratory distress syndrome.
Blood collection within 24 hours of acute respiratory distress syndrome onset and biomarker measurements.
In 152 children with acute respiratory distress syndrome, Pediatric Sepsis Biomarker Risk Model performed poorly and Pediatric Sepsis Biomarker Risk Model-II performed modestly (areas under receiver operating characteristic curve of 0.61 and 0.76, respectively). Therefore, we randomly selected 80% of the cohort (n = 122) to rederive a risk prediction model for pediatric acute respiratory distress syndrome. We used classification and regression tree methodology, considering the Pediatric Sepsis Biomarker Risk Model biomarkers in addition to variables relevant to acute respiratory distress syndrome. The final model was comprised of three biomarkers and age, and more accurately estimated baseline mortality risk (area under receiver operating characteristic curve 0.85, p < 0.001 and p = 0.053 compared with Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II, respectively). The model was tested in the remaining 20% of subjects (n = 30) and demonstrated similar test characteristics.
A validated, biomarker-based risk stratification tool designed for pediatric sepsis was adapted for use in pediatric acute respiratory distress syndrome. The newly derived Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model demonstrates good test characteristics internally and requires external validation in a larger cohort. Tools such as Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model have the potential to provide improved risk stratification and prognostic enrichment for future trials in pediatric acute respiratory distress syndrome.
最初的儿童脓毒症生物标志物风险模型以及修订后的(儿童脓毒症生物标志物风险模型-II)基于生物标志物的风险预测模型已证明可用于估计儿童脓毒症的基线28天死亡风险。鉴于儿童急性呼吸窘迫综合征的预测工具匮乏,且考虑到脓毒症与急性呼吸窘迫综合征之间存在重叠的病理生理学,我们测试了儿童脓毒症生物标志物风险模型和儿童脓毒症生物标志物风险模型-II在一组儿童急性呼吸窘迫综合征患者中预测死亡率的效用,并预先计划如果这些现有模型表现不佳则对模型进行修订。
前瞻性观察队列研究。
大学附属医院的儿科重症监护病房。
机械通气的急性呼吸窘迫综合征患儿。
在急性呼吸窘迫综合征发作后24小时内采集血液并进行生物标志物测量。
在152例急性呼吸窘迫综合征患儿中,儿童脓毒症生物标志物风险模型表现不佳,儿童脓毒症生物标志物风险模型-II表现一般(受试者工作特征曲线下面积分别为0.61和0.76)。因此,我们随机选择了该队列的80%(n = 122)重新推导儿童急性呼吸窘迫综合征的风险预测模型。我们使用分类和回归树方法,除了考虑与急性呼吸窘迫综合征相关的变量外,还纳入了儿童脓毒症生物标志物风险模型中的生物标志物。最终模型由三个生物标志物和年龄组成,能更准确地估计基线死亡风险(受试者工作特征曲线下面积为0.85,与儿童脓毒症生物标志物风险模型和儿童脓毒症生物标志物风险模型-II相比,p < 0.001和p = 0.053)。该模型在其余20%的受试者(n = 30)中进行了测试,显示出相似的测试特征。
一种经过验证的、基于生物标志物的、为儿童脓毒症设计的风险分层工具被改编用于儿童急性呼吸窘迫综合征。新推导的儿童急性呼吸窘迫综合征生物标志物风险模型在内部显示出良好的测试特征,需要在更大的队列中进行外部验证。像儿童急性呼吸窘迫综合征生物标志物风险模型这样的工具有可能为未来儿童急性呼吸窘迫综合征的试验提供更好的风险分层和预后富集。