Predictive informatics monitoring in the Neonatal Intensive Care Unit

项目概要/摘要 意义：新生儿重症监护室中早产极低出生体重儿（VLBW）的发病率持续增加 以及败血症和坏死性小肠结肠炎（NEC）的死亡率，以及这些疾病的早期发现和治疗 疾病已被证明可以提高生存率和结果。持续监测的生命体征包含微妙的 在脓毒症和NEC的早期阶段的变化，但这些生理标志物是不可见的与当前 技术，即使是最先进的监测和经验丰富的临床医生。我们的团队继续建立 通过先进的时间序列和机器开发预警系统的经验和合作 学习数据分析，这将改善早产儿的结果。上一篇：我们的第一次预警 HeRO监测系统提醒临床医生注意心率异常特征， 败血症相关死亡率降低40%，在3003例VLBW婴儿的随机试验中。在过去的7年里， 支持产生了几个重要的发现，包括1）增加脉搏血氧饱和度氧合数据（SpO 2） 心电图数据改善脓毒症和NEC预测; 2）患者的中心特异性差异 人口统计学和护理实践影响算法性能; 3）心率和心率之间的高度互相关， SpO 2反映了多个部位的呼吸暂停和脓毒症风险增加。创新：拟议的工作 代表了病人护理的范式转变-监测器报告健康和疾病的发展趋势 而不是转瞬即逝的价值，从而改善新生儿重症监护病房中早产儿的预后。方法：在 目前，我们正在增加第四个大型新生儿重症监护室，以实现以下目标：目标1：使用先进的 时间序列分析和机器学习，以完善和扩展脓毒症的预测监测算法 目标2：确定人口统计学和中心对结果和算法性能的影响; 目标3：通过构建现有平台，在全球范围内共享多中心数据和分析。研究者：共同主要研究者 费尔柴尔德和Moorman有着长期的合作关系，并成功地领导了多中心临床和 分析研究的生命，这一赠款，并加强了团队增加新的合作者， 中心.环境：本提案涉及的中心在收集和分析能力方面是独一无二的。 强大的机构研究和计算支持使大型生命体征和临床数据集成为可能。

PROJECT SUMMARY/ABSTRACT Significance: Premature very low birth weight (VLBW) infants in the Neonatal ICU continue to suffer morbidity and mortality from sepsis and necrotizing enterocolitis (NEC), and early detection and treatment of these illnesses has been shown to improve survival and outcomes. Continuously monitored vital signs contain subtle changes in the early stage of sepsis and NEC, but these physiological markers are invisible with current technology, even for the most sophisticated monitors and experienced clinicians. Our group continues to build on experience and collaboration to develop early warning systems through advanced time series and machine learning data analytics that will improve outcomes for premature infants. Progress: Our first such early warning system, the HeRO monitor, alerts clinicians to abnormal heart rate characteristics and was shown to reduce sepsis-associated mortality by 40% in a randomized trial of 3003 VLBW infants. The past 7 years of NIH support produced several important discoveries, including 1) Adding pulse oximetry oxygenation data (SpO2) to electrocardiogram data improves sepsis and NEC prediction; 2) Center-specific differences in patient demographics and care practices impact algorithm performance; 3) High cross-correlation of heart rate and SpO2 reflects increased apnea and sepsis risk across multiple sites. Innovation: The proposed work represents a paradigm shift in patient care – monitors that report trends of development of health and illness rather than fleeting values, leading to improved outcomes of preterm infants in the NICU. Approach: In the current proposal we are adding a fourth large NICU to accomplish the following aims: Aim 1: Use advanced time series analytics and machine learning to refine and expand predictive monitoring algorithms for sepsis and NEC; Aim 2: Determine the impact of demographics and center on outcomes and algorithm performance; Aim 3: Share multi-center data and analytics globally by building on an existing platform. Investigators: Co-PI's Fairchild and Moorman have a longstanding collaboration and have led successful multicenter clinical and analytical research for the life of this grant and have strengthened the team by adding new collaborators and centers. Environment: The centers involved in this proposal are unique in their ability to collect and analyze large vital sign and clinical data sets, made possible by robust institutional research and computing support.