Clinical markers of neonatal opioid withdrawal syndrome: onset, severity and longitudinal neurodevelopmental outcome

项目总结/摘要 这是一个行政补充，我们现有的NIDA资助赠款题为“临床标志物的新生儿 阿片类戒断综合征：发作、严重程度和纵向神经发育结局”（R 01 DA 049755）。 在美国，每15分钟就有一名婴儿出生时接触阿片类药物，其中许多人会出现困难的 治疗药物戒断综合征，新生儿阿片类药物戒断综合征（NOWS）。不幸的是， NOWS的诊断是高度主观的，包括仅仅基于护士判断的“高音哭声”。的 对NOWS婴儿哭声声学特征的客观测量是 本行政补充文件题为“新生儿临床标志物”， 阿片类戒断综合征：发作、严重程度和纵向神经发育结局”（R 01 DA 049755）： 目标1：确定通过母体测量的神经行为、哭泣、产前阿片类药物和其他物质暴露 头发，以及NOWS发病和严重程度的社会人口学预测因素。 目的2：评估这些临床标志物的预测有效性，并测试NOWS严重程度是否预测 6个月和18个月时的神经发育障碍。我们开发了一种基于计算机的哭声分析仪， 婴儿哭声的声学特征我们用哭声分析仪来确定 婴儿的哭声与NOWS和开发了一个NOWS哭“签名”，可以识别哪些婴儿发展NOWS 准确率高达91%然而，我们开发的哭泣技术在床边是不可用的。的 本行政补充的具体目的是开发一个基于云的自动分析系统 婴儿哭声的声学特征，用于诊断NOWS。拟议的软件将使我们能够 一个全自动的系统，其中用户使用电话或其他设备记录新生儿保育室中的婴儿哭声。 连接的设备，并在几秒钟内，收到诊断结果。本行政补充文件将 提供基于云的软件，通过提供更准确和可靠的诊断来改变临床实践 影响NOWS药物治疗的NOWS，包括住院时间， 有可能改善这些婴儿的长期预后。

PROJECT SUMMARY/ABSTRACT This is an administrative supplement to our existing NIDA-funded grant entitled “Clinical markers of neonatal opioid withdrawal syndrome: onset, severity and longitudinal neurodevelopmental outcome” (R01DA049755). Every 15 minutes in the United States, an infant is born exposed to opioids, many of which develop the difficult to treat drug withdrawal syndrome, Neonatal Opioid Withdrawal Syndrome (NOWS). Unfortunately, the diagnosis of NOWS is highly subjective and includes “high pitched cry” simply based on the nurse’s judgement. The objective measurement of the acoustic characteristics of the cry in babies with NOWS is a pivotal component of the Specific Aims of the active award for this Administrative Supplement entitled “Clinical markers of neonatal opioid withdrawal syndrome: onset, severity and longitudinal neurodevelopmental outcome” (R01DA049755): Aim 1: Determine neurobehavioral, cry, prenatal opioid and other substance exposure measured via maternal hair, and sociodemographic predictors of NOWS onset and severity. Aim 2: Evaluate the predictive validity of these clinical markers and test whether NOWS severity predicts neurodevelopment impairment at 6 and 18 months. We developed a computer-based cry analyzer that extracts the acoustic features of an infant’s cry. We used the cry analyzer to determine the acoustic characteristics of the cries of babies with NOWS and developed a NOWS cry “signature” that can identify which babies develop NOWS with a 91% accuracy rate. However, the cry technology that we developed is not usable at the bedside. The Specific Aim of this Administrative Supplement Is to develop a cloud-based system for the automated analysis of infant cry acoustical characteristics for the diagnosis of NOWS. The proposed software will enable us to have a fully automatic system, where a user records a baby cry in the newborn nursery using a phone or other connected device, and within a few seconds, receives the diagnostic result. This Administrative Supplement will provide the cloud-based software to change clinical practice by providing a more accurate and reliable diagnosis of NOWS which will affect the pharmacological treatment of NOWS including length of hospital stay and potentially improve the long-term outcome of these infants.