Earlier detection of late onset neonatal sepsis using temporal analysis of continuous physiological data streams in a Chinese neonatal intensive care unit
作者单位：Neonatal Intensive UnitChildren's Hospital for Fudan University Health Informatics Research LaboratoryUniversity of Ontario Institute of Technology Department of PaediatricsUniversity of Toronto
会议名称：《2015年泛长三角围产医学学术年会暨浙江省围产医学学术年会》
会议日期：2015年
学科分类：1002[医学-临床医学] 100202[医学-儿科学] 10[医学]
关 键 词：sepsis infant late onset neonatal sepsis physiological data streams temporal analysis
摘 要：Objective:Late-onset neonatal sepsis(LONS)is an important cause of morbidity and mortality in *** clinical symptoms of LONS are often subtle and nonspecific and therefore early and accurate diagnosis is *** rate variability(HRV)may be decreased up to 24 hours before the diagnosis of *** aimed to test whether HRV and respiratory rate variability(RRV)behaviors present prior to the clinical suspicion of LONS within two North American cohorts were evident within a population of neonatal patients from China Method:We collected physiological data prospectively from a cohort of 43 infants born at less than 34 weeks gestational age at neonatal unit at Fudan University Children’s *** were 6 infants who developed LONS within this *** was defined as a blood culture positive infection or clinical infection occurring at more than 3 days of *** all infants in the cohort HRV and RRV were determined by a process of temporal abstraction of one second values of heart rate and respiratory rate captured from Phillips MP30 and MP50 ***:LONS was suspected in 6 out of 43 babies in the *** 6 episodes,4microbiologically confirmed sepsis from sterile sites,2 were clinical *** representative patient examples,we illustrate an analytics user interface design that shows the potential in using our HRV and RRV analytics for early identification of LONS with1 second spot readings Conclusion:Continuous HRV and RRV monitoring provides a valuable tool for early identification of *** work will expand this pilot study to increase the sample size and capture additional clinical practice data to provide greater insight into the relationship between the behaviours of continuous physiological data streams and the early identification of LONS.