Neonatal apnea: Online risk score from new analyses of bedside monitor waveforms

描述(申请人提供)：新生儿呼吸暂停，或早产儿呼吸暂停，是新生儿重症监护病房(NICU)中最常见的早产儿严重疾病。在其定义、文件编制和管理方面的知识有很大差距。例如，尽管NICU持续进行电子监测，但仅根据临床判断诊断呼吸暂停发作，并仅在床边流程表上手动记录。缺乏量化和标准化的呼吸暂停指标阻碍了了解其自然病史、治疗方法及其与婴儿猝死综合征(SID)这一重大公共卫生问题的关系的努力。我们的长期目标是通过为医生和护士提供亚急性、潜在灾难性疾病的实时风险评估来改变NICU的做法。在这里，我们的具体目标是开发和验证多变量预测模型，用于使用NICU床边监护仪记录的波形和生命体征的旧的和新的数学测量来持续监测新生儿呼吸暂停。我们将提供短期呼吸暂停指数和累积呼吸暂停负担，作为适合机械性见解和随机治疗试验的管理和研究工具。该项目符合大机遇赠款计划的范围和要求。我们计划一个大规模的加速计划，以生成一个大型的新生儿临床和监测波形数据数据库，并开发监测算法。该数据库对其他研究人员来说是一个丰富的资源，这些算法将成为解决NICU目前数据解释障碍的创新解决方案，并有望改善婴儿健康。新的大规模计算硬件和软件已经在运行。我们的团队在NICU开发新的监测算法方面拥有独特的经验，代表着临床、工程和数学学科。没有其他实体可能构思或执行这项工作，似乎也没有其他资金来源。 公共卫生相关性：早产儿呼吸暂停(AOP)是一种常见的危及生命的疾病，通常延长早产儿昂贵的住院时间。虽然目前检测、记录和分类AOP的方法依赖于高度不可靠的护理观察，但现在计算机技术和存储容量随时可用来允许对来自常规床边监护仪的现有信号进行连续在线分析，以预测呼吸暂停风险。我们拥有技术、专业知识和现有的网络，可以开发和验证一种敏感的呼吸暂停风险测量方法，可以在其他NICU广泛实施，通过更早地安全出院来节省大量医院成本，并为呼吸控制的成熟提供宝贵的知识，并为AOP和婴儿猝死综合征(SID)的未来研究提供有用的工具和数据库。

DESCRIPTION (provided by applicant): Neonatal apnea, or apnea of prematurity, is the most common serious disorder of premature infants in the neonatal intensive care unit (NICU). There are significant gaps in knowledge in its definition, documentation and management. For example, despite continuous electronic monitoring in the NICU, apnea episodes are diagnosed based only on clinical judgment and recorded only by hand on bedside flow sheets. The lack of quantitative and standardized apnea metrics has stalled efforts to understand its natural history, its therapy, and its relationship to the major public health problem of sudden infant death syndrome, or SIDS. Our long term goals are to change NICU practice by providing doctors and nurses with real time risk assessment for subacute, potentially catastrophic diseases. Here, our Specific Aim is to develop and validate multivariable predictive models for continuous monitoring of neonatal apnea using old and new mathematical measures of waveforms and vital signs recorded on NICU bedside monitors. We will deliver a short-term apnea index and a cumulative apnea burden as management and research tools suitable for mechanistic insights and for randomized therapeutic trials. The project is responsive to the scope and requirements of the Grand Opportunities grants program. We plan a large-scale and accelerated program to generate a large database of neonatal clinical and monitor waveform data, and to develop monitoring algorithms. The database is a rich resource for other researchers, and the algorithms will be innovative solutions to current barriers to data interpretation in NICUs, and promise improved infant health. New large scale computing hardware and software is already running. Our team has unique experience in developing new monitoring algorithms in the NICU, and represents clinical, engineering and mathematical disciplines. No other entity is likely to conceive or to execute this work, and no other funding source seems likely. PUBLIC HEALTH RELEVANCE: Apnea of prematurity (AOP) is a common life-threatening disorder that often extends expensive hospitalization of premature babies. While methods for detecting, recording, and classifying AOP currently depend on highly unreliable nursing observations, computer technology and storage capacity are now readily available to permit continuous on line analysis of existing signals from routine bedside monitors to predict apnea risk. We have the technology, expertise, and existing network to develop and verify a sensitive measure of apnea risk which could be widely implemented in other NICUs to save substantial hospital costs through earlier safe hospital discharge, as well as to contribute valuable knowledge about maturation of respiratory control and provide a useful tool and database for future studies of AOP and Sudden Infant Death Syndrome (SIDS).