Modeling Determinants of Time-To-Death in Premature Infants Admitted to Neonatal Intensive Care Unit in Jimma University Specialized Hospital

Million Wesenu (), Sudhir Kulkarni and Tafere Tilahun
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Million Wesenu: Haramaya University
Sudhir Kulkarni: Jimma University
Tafere Tilahun: Jimma University

Annals of Data Science, 2017, vol. 4, issue 3, No 4, 381 pages

Abstract: Abstract Preterm birth is the term used to define births that occur before 37 completed weeks or 259 days of gestation. The aim of this study is to model survival probability of premature infants who were under follow-up and identify significant risk factors for mortality. Recorded hospital data were obtained for a cohort of 490 infants at Jimma University Specialized Hospital, Ethiopia. The infants have been under follow-up from January 2013 to December 2015. The non-parametric, semi-parametric and parametric survival models are used to estimate the survival time as well as examine the association between the survival time with different demographic, health and risk behavior variables. The analysis shows that most factors significantly contribute to a shorter survival time of premature infants. These factors include having prenatal Asphyxia, hyaline membrane disease, sepsis, jaundice, low gestational age, respiratory distress syndrome and initial temperature. It is therefore recommended that people ought to be cognizant on the burden of these risk factors and well informed about the prematurity.

Keywords: Premature infant; Time to death; Cox proportional hazards model; Log-logistic regression model (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s40745-017-0107-2

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