Department of Pediatrics, Neurodevelopmental and Behavioral Pediatrics, University of Virginia Children's, University of Virginia School of Medicine, Charlottesville, Virginia.
Department of Pediatrics, Neonatology, University of Virginia Children's, University of Virginia School of Medicine, Charlottesville, Virginia.
Am J Perinatol. 2024 May;41(S 01):e528-e535. doi: 10.1055/s-0042-1756335. Epub 2022 Sep 29.
Infants in the neonatal intensive care unit (NICU) are at high risk of adverse neuromotor outcomes. Atypical patterns of heart rate (HR) and pulse oximetry (SpO) may serve as biomarkers for risk assessment for cerebral palsy (CP). The purpose of this study was to determine whether atypical HR and SpO patterns in NICU patients add to clinical variables predicting later diagnosis of CP.
This was a retrospective study including patients admitted to a level IV NICU from 2009 to 2017 with archived cardiorespiratory data in the first 7 days from birth to follow-up at >2 years of age. The mean, standard deviation (SD), skewness, kurtosis and cross-correlation of HR and SpO were calculated. Three predictive models were developed using least absolute shrinkage and selection operator regression (clinical, cardiorespiratory and combined model), and their performance for predicting CP was evaluated.
Seventy infants with CP and 1,733 controls met inclusion criteria for a 3.8% population prevalence. Area under the receiver operating characteristic curve for CP prediction was 0.7524 for the clinical model, 0.7419 for the vital sign model, and 0.7725 for the combined model. Variables included in the combined model were lower maternal age, outborn delivery, lower 5-minute Apgar's score, lower SD of HR, and more negative skewness of HR.
In this study including NICU patients of all gestational ages, HR but not SpO patterns added to clinical variables to predict the eventual diagnosis of CP. Identification of risk of CP within the first few days of life could result in improved therapy resource allocation and risk stratification in clinical trials of new therapeutics.
· SD and skewness of HR have some added predictive value of later diagnosis of CP.. · SpO2 measures do not add to CP prediction.. · Combining clinical variables with early HR measures may improve the prediction of later CP..
新生儿重症监护病房(NICU)中的婴儿存在不良神经运动结局的高风险。心率(HR)和脉搏血氧饱和度(SpO)的非典型模式可能作为脑瘫(CP)风险评估的生物标志物。本研究旨在确定 NICU 患者的非典型 HR 和 SpO 模式是否增加了预测 CP 后期诊断的临床变量。
这是一项回顾性研究,纳入了 2009 年至 2017 年期间入住四级 NICU 的患者,在出生后 7 天内记录了心肺数据,并在>2 岁时进行了随访。计算了 HR 和 SpO 的平均值、标准差(SD)、偏度、峰度和交叉相关。使用最小绝对收缩和选择算子回归(临床、心肺和综合模型)开发了三个预测模型,并评估了它们预测 CP 的性能。
70 例 CP 患儿和 1733 例对照符合 3.8%的人群患病率标准。临床模型预测 CP 的曲线下面积为 0.7524,生命体征模型为 0.7419,综合模型为 0.7725。综合模型中包含的变量为母亲年龄较低、外产、5 分钟 Apgar 评分较低、HR 的 SD 较低和 HR 的负偏度较大。
在这项纳入所有胎龄 NICU 患者的研究中,HR 而非 SpO 模式增加了预测最终 CP 诊断的临床变量。在生命的最初几天内识别 CP 的风险可能会导致在新疗法的临床试验中改善治疗资源的分配和风险分层。
· HR 的 SD 和偏度对 CP 的后期诊断具有一定的预测价值。· SpO2 测量值不能增加 CP 预测。· 将临床变量与早期 HR 测量值相结合可能会提高 CP 的预测。