Diagnosis of Neonatal Opioid Withdrawal Syndrome (NOWS) and development of a NOWS-App

项目总结 PedialyDx Inc.提议复制之前的研究结果，并开发一种商业产品，该产品可以 协助诊断新生儿阿片类药物戒断综合征(NOWS)，即婴儿戒断 出生后不久，由于胎儿突然停止接触阿片类药物而出现的情况。现在已经有了 成为一个重大的公共卫生问题，从2004年的每1000名新生儿中有1.6名增加到每1000名新生儿中有8.8名 2016年，相关医院费用从2000年的1.9亿美元增加到2009年的7.2亿美元。准确 NOWS的诊断很重要，因为假阳性会导致婴儿不必要地接受 相应延长住院时间和巨额费用的药物治疗，或虚假- 负面反应会导致婴儿在应该接受治疗的时候得不到治疗，这可能会导致严重的医疗问题。 不幸的是，目前诊断NOWS的方法，无论是基于药理学的，如 标准的“芬尼根评分系统”，或非药理学的，如“东部，睡眠和控制台”是 因为他们的主观性而受到限制。使用专有声学分析软件和机器学习(ML) 算法，我们的团队已经初步确定了一个将婴儿哭声与芬尼根 精确度为.81。PedialyDx的NOWS-APP将通过2个月为NOWS儿童提供更好的护理 创新：1)使用声学哭声分析进行更客观的评估将导致更准确的诊断和 治疗(更少的假阳性、更少的假阴性和更精确的住院时间)和2)节省 时间，导致成本节约，在管理诺沃斯婴儿。我们的初步数据是 在单个受控临床环境中收集，这证明了我们的算法可以 客观地评估婴儿的哭声。接下来，我们将通过扩展我们的NOWS-APP来推进其商业化 在我们现有的数据集上，通过收集来自真实世界设置的数据来优化我们针对NOWS的ML算法。在……里面 目标1，我们将进行一项多中心研究(7个地点)，以扩大婴儿哭闹作为一种指标的研究。 好了。在目标2中，我们将完成NOWS-APP的开发。本项目圆满完成 将使我们的NOWS-App产品准备好提交给FDA。本申请中提出的工作 还将使PedialyDx在推进其婴儿哭声技术平台方面迈出重要一步，以实现 适用于其他情况的产品，如自闭症和其他发育障碍、绞痛和疼痛的筛查。

PROJECT SUMMARY PedialyDx Inc. proposes to replicate previous research findings and develop a commercial product that can assist in the diagnosis of Neonatal Opioid Withdrawal Syndrome (NOWS), the withdrawal that infants experience shortly after birth due to the abrupt discontinuation of fetal exposure to opioids. NOWS has become a significant public health problem, increasing from 1.6 per 1000 births in 2004 to 8.8 per 1000 births in 2016, with associated hospital charges increasing from $190M in 2000 to $720M in 2009. Accurate diagnosis of NOWS is important because false-positives can result in babies unnecessarily receiving pharmacological treatment with corresponding prolonged hospitalization and substantial cost, or false- negatives result in babies not being treated when they should, potentially leading to serious medical problems. Unfortunately, current methods to diagnose NOWS, whether pharmacologically based such as the “gold standard” Finnegan scoring system, or non-pharmacologically based such as “East, Sleep and Console” are limited because of their subjectivity. Using proprietary acoustic analysis software and Machine Learning (ML) algorithms, our team has identified a preliminary “cry signature” relating baby cry acoustics to the Finnegan with .81 accuracy. PedialyDx’s NOWS-app will deliver improved care for children with NOWS through 2 innovations: 1) more objective assessment using acoustic cry analysis will lead to more accurate diagnosis and treatment (fewer false positives, fewer false negatives, and more precise hospitalization stays) and 2) save time, leading to cost savings, in the management of babies with NOWS. Our preliminary data has been collected in a single controlled clinical setting, which has demonstrated proof of concept that our algorithm can objectively assess baby cries. Next, we will advance the commercialization of our NOWS-app by expanding upon our existing dataset by collecting data from real-world settings to optimize our ML algorithm for NOWS. In Aim 1, we will conduct a multi-center study (7 sites) to extend the research of baby cry as an indicator of NOWS. In Aim 2, we will complete the development of the NOWS-app. Successful completion of this project will result in our NOWS-App product ready for submission to the FDA. The work proposed in this application will also allow PedialyDx to take important steps toward advancing its baby cry technology platform to enable products for other conditions, such as screening for autism and other developmental disorders, colic and pain.