Heart Rate Characteristics Monitoring in Newborn Infant

新生儿心率特征监测

• 批准号: 6872736
• 负责人: JOSEPH RANDALL MOORMAN
• 金额: $ 33.51万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-03-01 至 2009-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6872736
• 关键词: age difference; biomarker; clinical research; cytokine; diagnosis design /evaluation; disease /disorder proneness /risk; early diagnosis; gestational age; heart rate; human birth weight; human data; human subject; mathematical model; newborn human (0-6 weeks); noninvasive diagnosis; patient care management; septicemia; tissue /cell culture

DESCRIPTION (provided by applicant): Sepsis is a major health problem in high-risk newborn infants in the neonatal intensive care unit (NICU), where it occurs in 25 percent of very low birth weight infants and leads to a more than doubling of mortality and a 50 percent increase in hospital stay. Abnormal heart rate characteristics (HRC) of reduced variability and transient decelerations occur early in the course of neonatal sepsis, and predictive multivariable models for sepsis and death have been developed at one center and validated at another. Our long-term goal is to test the hypothesis that continuous HRC monitoring will improve care of these patients by earlier diagnosis of sepsis and other sub-acute, potentially catastrophic illnesses. We propose to advance toward this objective by completing three research aims. In Aim 1, we will test the hypothesis that incorporating conventional lab tests and clinical findings with HRC will lead to improved predictive models for early diagnosis of late-onset neonatal sepsis. In Aim 2, we will identify mechanism-specific tests and findings, and test the hypothesis that they add information in predictive models of late-onset neonatal sepsis. The clinical research design for these Aims is a derivation of multivariable predictive statistical models from one set of patients followed by a validation phase using clinical data from a second set of patients. In Aim 3, we will develop new mathematical measures that detect abnormal HRC early in the course of late-onset neonatal sepsis, in particular, measures of deceleration characteristics. We feel that HRC monitoring in the NICU is a truly novel approach, and we intend to lead the field in developing predictive algorithms for clinical use in the early diagnosis of neonatal sepsis.

描述（由申请人提供）：败血症是新生儿重症监护室（NICU）中高危新生儿的主要健康问题，25%的极低出生体重儿发生败血症，导致死亡率增加一倍以上，住院时间增加50%。 在新生儿败血症的早期发生变异性降低和短暂减速的异常心率特征（HRC），败血症和死亡的预测多变量模型已在一个中心开发，并在另一个中心验证。 我们的长期目标是检验这样一个假设，即持续的HRC监测将通过早期诊断脓毒症和其他亚急性、潜在的灾难性疾病来改善对这些患者的护理。 我们建议通过完成三个研究目标来实现这一目标。 在目标1中，我们将检验以下假设：将常规实验室检查和临床结果与HRC相结合将改进晚发型新生儿败血症早期诊断的预测模型。 在目标2中，我们将确定机制特异性测试和发现，并测试他们在晚发型新生儿败血症的预测模型中添加信息的假设。 这些目的的临床研究设计是从一组患者中推导出多变量预测统计模型，然后使用第二组患者的临床数据进行验证。 在目标3中，我们将开发新的数学措施，检测异常HRC早在晚发性新生儿败血症的过程中，特别是减速特性的措施。 我们认为，HRC监测在新生儿重症监护室是一个真正的新颖的方法，我们打算领导该领域的发展预测算法的临床应用在新生儿败血症的早期诊断。