Validation of Physiologic CPR Quality Using NOn-inVasive Waveform Analytics (CPR-NOVA)

使用非侵入性波形分析 (CPR-NOVA) 验证生理心肺复苏质量

• 批准号: 9910446
• 负责人: ROBERT ALLEN BERG
• 金额: $ 40.47万
• 依托单位: CHILDREN'S HOSP OF PHILADELPHIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-15 至 2022-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9910446
• 关键词: Affect; Algorithms; Ancillary Study; Area; Arterial Lines; Blood Pressure; Brain Injuries; Carbon Dioxide; Cardiopulmonary Resuscitation; Cardiovascular system; Caring; Chest; Child; Childhood; Clinical; Collection; Critical Care; Data; Databases; Defibrillators; Devices; Diastolic blood pressure; Disease; Event; Failure; Feedback; Funding; Future; Gold; Guidelines; Heart; Heart Arrest; Hospitals; Infrastructure; Intensive Care Units; Investigation; Life; Link; Lung; Machine Learning; Mechanics; Medical; Methods; Monitor; Morbidity - disease rate; National Heart, Lung, and Blood Institute; National Institute of Child Health and Human Development; Neurologic; Neurological outcome; Organ; Outcome; Parents; Patient Care; Patient Monitoring; Patients; Performance; Perfusion; Photoplethysmography; Physiologic Monitoring; Physiologic pulse; Physiological; Procedures; Process; Provider; Public Health; Pulse Oximetry; ROC Curve; Research; Resuscitation; Risk Factors; Signal Transduction; Survival Rate; Survivors; System; Techniques; Technology; Time; Validation; Vulnerable Populations; Work; classification algorithm; clinical care; clinically relevant; hemodynamics; improved; improved outcome; machine learning algorithm; machine learning method; modifiable risk; monitoring device; multimodality; novel; patient response; pediatric patients; prospective; response; survival outcome; ventilation

Project Abstract Pediatric cardiac arrest affects thousands of children each year. Progressive heart and lung failure is a predisposing cause in many of these events. Despite improvements in survival outcomes over the past two decades, more than half of these children still do not survive. As new brain injury complicates care among survivors, the burden to these children and the public's health is substantial. Cardiopulmonary resuscitation (CPR) – the medical procedure of providing chest compressions and ventilations during cardiac arrest – saves lives, and higher quality CPR is more effective at doing so. One method to improve CPR quality is through the use of CPR quality monitoring defibrillators. By providing real- time feedback on CPR mechanics targets such as chest compression depth and rate, they represent the best patient care option currently available to improve CPR performance. Unfortunately, most of these devices are either not approved for children or use pads that are too large for many pediatric patients. Thus, current technology limits the benefit of meaningful CPR quality monitoring to a small percentage of the children who suffer a cardiac arrest. Given the strong association between pediatric CPR quality and outcomes, new methods to monitor CPR quality are urgently needed to improve the care of this vulnerable population. Physiologic-directed CPR is a promising technique that uses the hemodynamic response of the patient to guide the ongoing resuscitation effort. This approach overcomes the technological limitations of existing CPR quality monitoring technology by using data from patient monitors. Unfortunately, because many patients do not have intra-arterial lines in place at the time of arrest to guide CPR, its clinical impact has been limited. To overcome this limitation, the objective of this ancillary application is to leverage the existing infrastructure of the National Institute of Child Health and Human Development-funded Collaborative Pediatric Critical Care Research Network (CPCCRN) and the unique hemodynamic waveform database of the National Heart, Lung, and Blood Institute-funded parent R01 – the ICU-Resuscitation (ICU-RESUS) Project – to validate two noninvasive physiologic CPR monitors applicable to nearly every pediatric cardiac arrest: 1) end-tidal carbon dioxide (ETCO2); and 2) PhotoPlethysmoGraphy (PPG) obtained via pulse oximetry. Using sophisticated machine learning methods, a prospective observational analytic investigation is proposed with the following Aims: 1) Evaluate ETCO2 as a noninvasive CPR quality monitor among children receiving at least 1 minute of CPR in a CPCCRN intensive care unit; and 2) Using novel machine learning classification algorithms, evaluate PPG and other candidate physiologic waveforms as noninvasive CPR quality monitors. By leveraging the substantial infrastructure of the CPCCRN, the novel hemodynamic waveform database of ICU-RESUS, and advanced machine learning analytics, this submission represents a unique opportunity to validate two noninvasive physiologic pediatric CPR quality monitors to improve clinical care and save lives. !

项目摘要 小儿心脏骤停每年影响成千上万的儿童。进行性心肺衰竭是一种 诱发因素尽管在过去的两年中， 几十年来，这些儿童中仍有一半以上无法生存。由于新的脑损伤使护理复杂化， 幸存者，这些儿童和公众健康的负担是巨大的。 心肺复苏术（CPR）-提供胸部按压的医疗程序， 心脏骤停时的心肺复苏-挽救生命，更高质量的心肺复苏术在这方面更有效。一 提高心肺复苏质量的方法是通过使用心肺复苏质量监控器。通过提供真实的- 心肺复苏力学指标的时间反馈，如胸外按压深度和速率，它们代表了最好的 目前可用于改善CPR性能的患者护理选项。不幸的是，这些设备中的大多数 要么未被批准用于儿童，要么使用对许多儿科患者来说太大的护垫。因此，当前 技术限制了有意义的CPR质量监测的益处， 心脏骤停鉴于小儿CPR质量和结果之间的密切联系，新方法 迫切需要监测心肺复苏质量，以改善对这一弱势群体的护理。 生理指导的CPR是一种有前途的技术，其使用患者的血液动力学反应来 指导正在进行的复苏工作。这种方法克服了现有CPR的技术局限性 通过使用来自患者监护仪的数据的质量监测技术。不幸的是，因为许多患者 在心脏骤停时没有动脉内导管来指导CPR，其临床影响有限。到 为了克服这一限制，该辅助应用程序的目标是利用现有的基础设施， 由国家儿童健康与人类发展研究所资助的儿科重症监护合作项目 研究网络（CPCCRN）和国家心脏，肺， 和血液研究所资助的父R 01-ICU复苏（ICU-RESUS）项目-以验证两个 无创生理CPR监护仪适用于几乎所有的小儿心脏骤停：1）呼气末碳 二氧化碳（ETCO 2）;和2）通过脉搏血氧仪获得的光电容积描记（PPG）。使用复杂 机器学习方法，提出了一个前瞻性的观察分析研究， 目的：1）在接受至少1分钟心肺复苏术的儿童中评估ETCO 2作为无创CPR质量监测器的作用。 CPCCRN重症监护室中的CPR;以及2）使用新型机器学习分类算法，评估 PPG和其他候选生理波形作为无创CPR质量监测器。 通过利用CPCCRN的大量基础设施， ICU-RESUS和先进的机器学习分析，本次提交是一个独特的机会， 验证两个无创生理儿科CPR质量监测器，以改善临床护理和挽救生命。!