Survival Analysis of Premature Infants Admitted to Neonatal Int ensive Care Unit (NICU) in Northwest Ethiopia using Semi-Parametric Fr ailty ModelSheferaw Yehuala1, SalieAyalew2and Zinabu Teka2*
- *Corresponding Author:
- Zinabu Teka
Department of Statistics
College of Natural and Computational Science
University of Gondar, Ethiopia
E-mail: [email protected]
Received date: February 17, 2015; Accepted date: May 14, 2015; Published date: May 21, 2015
Citation: Yehuala S, Ayalew S, Teka Z (2015) Survival Analysis of Premature Infants Admitted to Neonatal Intensive Care Unit (NICU) in Northwest Ethiopia using Semi-Parametric Frailty Model. J Biom Biostat 6:223. doi:10.4172/2155-6180.1000223
Copyright: ©2015 Yehuala S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are are credited.
In this research, the cox proportional hazard model and the semi-parametric gamma frailty model were compared on the survival of premature infants admitted to neonatal intensive care unit from December 29, 2011 to April 6, 2014. A retrospective study design was used to collect the data from patients chart. A frailty effect (θ=0.252, P-Value = 0.0031 < α=0.05) was obtained from the semi-parametric gamma frailty model, and mortality was depend within and across categories of premature infants based on their gestational age. The values of frailty were dispersed and hence induce greater heterogeneity in the infant hazards. Therefore, when there is heterogeneity, semi-parametric gamma frailty model could be used and lead to acceptable conclusions. Both models identifies Antenatal Care Visit, gravidity of (6-10), HIV status of mother, Respiratory Distress Syndrome, Prenatal Asphyxia, anemia and breastfeed initiated as the most determinant and statistically associated with time to death of premature infants admitted to NICU. Based on the model comparison analysis, semi-parametric gamma frailty was the best model to fit the data.