Predictive Models of Neurodevelopmental Outcomes After Neonatal Hypoxic-Ischemic Encephalopathy
Predictive Models of Neurodevelopmental Outcomes After Neonatal Hypoxic-Ischemic Encephalopathy
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DOI：
10.1542/peds.2020-022962
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发表时间：
2021-02-01
期刊：
影响因子：
8
通讯作者：
Massaro, An
中科院分区：
文献类型：
--
作者：
Peeples, Eric S.;Rao, Rakesh;Massaro, An
目的：根据 NICU 入院（“早期”）或出院（“累积”）时容易获得的数据，开发新生儿缺氧缺血性脑病（HIE）后死亡或神经发育障碍（NDI）的预测模型。方法：在这项回顾性队列分析中，我们使用了儿童医院新生儿联盟数据库（2010-2016 年）的数据。包括在 11 个参与地点妊娠≥ 35 周出生并接受 HIE 低温治疗的婴儿； 11 个月后没有记录贝利婴儿发育评分的婴儿被排除在外。主要结局是死亡或 NDI。 80% 的人群建立了多变量模型；在剩余的 20% 中进行了验证。结果：486 名婴儿中有 242 名出现主要结局； 180 人死亡，62 名幸存婴儿患有 NDI。在早期模型中，HIE 严重程度、产房内肾上腺素给药、呼吸支持以及入院时吸入氧分数 0.21 都很重要。 EEG 结果的严重程度与累积模型的 HIE 严重程度相结合，其他重要变量包括使用类固醇进行血压管理和 MRI 上的严重脑损伤。发现模型显示早期模型的曲线下面积为 0.852，累积模型的曲线下面积为 0.861，并且两个模型在验证队列中均表现良好（拟合优度 chi(2)：分别为 P = 0.24 和 0.06）。结论：建立可靠的预测模型将使临床医生能够更准确地评估 HIE 的严重程度，并可能为那些死亡或 NDI 风险最高的人提供更有针对性的早期治疗。在这项研究中，我们使用 CHND 的数据来生成临床数据模型，以预测 HIE 后的死亡或残疾。
OBJECTIVES: To develop predictive models for death or neurodevelopmental impairment (NDI) after neonatal hypoxic-ischemic encephalopathy (HIE) from data readily available at the time of NICU admission ("early") or discharge ("cumulative"). METHODS: In this retrospective cohort analysis, we used data from the Children's Hospitals Neonatal Consortium Database (2010-2016). Infants born at >= 35 weeks' gestation and treated with therapeutic hypothermia for HIE at 11 participating sites were included; infants without Bayley Scales of Infant Development scores documented after 11 months of age were excluded. The primary outcome was death or NDI. Multivariable models were generated with 80% of the cohort; validation was performed in the remaining 20%. RESULTS: The primary outcome occurred in 242 of 486 infants; 180 died and 62 infants surviving to follow-up had NDI. HIE severity, epinephrine administration in the delivery room, and respiratory support and fraction of inspired oxygen of 0.21 at admission were significant in the early model. Severity of EEG findings was combined with HIE severity for the cumulative model, and additional significant variables included the use of steroids for blood pressure management and significant brain injury on MRI. Discovery models revealed areas under the curve of 0.852 for the early model and of 0.861 for the cumulative model, and both models performed well in the validation cohort (goodness-of-fit chi(2): P = .24 and .06, respectively). CONCLUSIONS: Establishing reliable predictive models will enable clinicians to more accurately evaluate HIE severity and may allow for more targeted early therapies for those at highest risk of death or NDI.In this study, we use data from the CHND to generate models of clinical data to predict death or disability after HIE.