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

新生儿呼吸暂停：根据床边监护仪波形的新分析得出的在线风险评分

基本信息

批准号：
7944052
负责人：
JOHN KATTWINKEL
金额：
$ 101.33万
依托单位：
UNIVERSITY OF VIRGINIA
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-09-30 至 2012-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7944052
关键词：
Algorithms Apnea Applications Grants Area Arts Beds Birth Catastrophic Illness Censuses Cessation of life Characteristics Chest Clinical Clinical Engineering Computer software Computers Coupled Data Databases Detection Diagnosis Discipline Discipline of Nursing Disease Documentation Early Diagnosis Electrocardiogram Electronics Entropy Event Failure Foundations Frequencies Funding Agency Future Goals Grant Hand Handwriting Healthcare Heart Rate Home environment Hospital Costs Hospitalization Hospitals Impedance Plethysmography Infant Infant Health Intercept Judgment Knowledge Length of Stay Life Low Birth Weight Infant Measures Methods Metric Modeling Monitor Morbidity - disease rate National Institute of Child Health and Human Development National Institute of General Medical Sciences Natural History Neonatal Neonatal Apneic Attack Neonatal Intensive Care Units Nurses Outcome Oxygen Patients Premature Infant Public Health Randomized Records Research Research Personnel Resources Risk Risk Assessment Running Signal Transduction Solutions Sudden infant death syndrome System Technology Testing Therapy Clinical Trials Time United States National Institutes of Health Validation Ventilator Vital Statistics Work base cost data acquisition digital experience improved indexing innovation insight model development mortality neonatal sepsis predictive modeling premature programs public health relevance respiratory tool treatment planning

项目摘要

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).

描述（由申请人提供）：新生儿呼吸暂停或早产儿呼吸暂停是新生儿重症监护室（NICU）早产儿最常见的严重疾病。其定义、文档和管理方面的知识存在重大差距。例如，尽管新生儿重症监护室有持续的电子监测，但呼吸暂停发作仅根据临床判断来诊断，并且仅在床边流程图上手工记录。由于缺乏定量和标准化的呼吸暂停指标，了解其自然史、治疗方法及其与婴儿猝死综合症（SIDS）这一主要公共卫生问题的关系的努力陷入停滞。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 的实践。在这里，我们的具体目标是开发和验证多变量预测模型，使用 NICU 床边监护仪记录的波形和生命体征的新旧数学测量来连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，作为适合机械见解和随机治疗试验的管理和研究工具。该项目响应了大机会补助计划的范围和要求。我们规划了一个大规模的加速计划，以生成新生儿临床和监测波形数据的大型数据库，并开发监测算法。该数据库对于其他研究人员来说是丰富的资源，算法将成为解决新生儿重症监护病房中当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。我们的团队在开发新生儿重症监护室新监测算法方面拥有独特的经验，并代表临床、工程和数学学科。没有其他实体可能构思或执行这项工作，而且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，通常会延长早产儿昂贵的住院治疗时间。虽然检测、记录和分类 AOP 的方法目前依赖于高度不可靠的护理观察，但现在可以随时使用计算机技术和存储容量来连续在线分析来自常规床边监护仪的现有信号，以预测呼吸暂停风险。我们拥有技术、专业知识和现有网络来开发和验证呼吸暂停风险的敏感测量方法，该测量方法可以在其他 NICU 中广泛实施，通过尽早安全出院来节省大量医院费用，并提供有关呼吸系统成熟的宝贵知识。控制并为未来 AOP 和婴儿猝死综合症 (SIDS) 的研究提供有用的工具和数据库。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Predictive monitoring for respiratory decompensation leading to urgent unplanned intubation in the neonatal intensive care unit.

DOI：
10.1038/pr.2012.155
发表时间：
2013-01
期刊：
Pediatric research
影响因子：
3.6
作者：
Clark MT;Vergales BD;Paget-Brown AO;Smoot TJ;Lake DE;Hudson JL;Delos JB;Kattwinkel J;Moorman JR
通讯作者：
Moorman JR

A new algorithm for detecting central apnea in neonates.

DOI：
10.1088/0967-3334/33/1/1
发表时间：
2012-01
期刊：
Physiological measurement
影响因子：
3.2
作者：
Lee H;Rusin CG;Lake DE;Clark MT;Guin L;Smoot TJ;Paget-Brown AO;Vergales BD;Kattwinkel J;Moorman JR;Delos JB
通讯作者：
Delos JB

Accurate automated apnea analysis in preterm infants.

DOI：
10.1055/s-0033-1343769
发表时间：
2014-02
期刊：
American journal of perinatology
影响因子：
2
作者：
Vergales BD;Paget-Brown AO;Lee H;Guin LE;Smoot TJ;Rusin CG;Clark MT;Delos JB;Fairchild KD;Lake DE;Moorman R;Kattwinkel J
通讯作者：
Kattwinkel J

Cardiorespiratory dynamics measured from continuous ECG monitoring improves detection of deterioration in acute care patients: A retrospective cohort study.