Multiple Events Model for the Infant Mortality at Kigali University Teaching Hospital

Abstract

Introduction: The present study applies multiple events survival analysis to infant mortality at the Kigali University Teaching Hospital (KUTH) in Rwanda. Materials and Methods: The primary dataset consists of newborns from KUTH recorded in the year 2016 and in the current paper, a complete case analysis was used. Two events per subject were modeled namely death and the occurrence of at least one of the following conditions that may also cause long-term death to infants such as severe oliguria, severe prematurity, very low birth weight, macrosomia, severe respiratory distress, gastroparesis, hemolytic, trisomy, asphyxia and laparoschisis. Covariates of interest include demographic covariates namely the age and the place of residence for parents; clinical covariates for parents include obstetric antecedents, type of childbirth and previous abortion. Clinical covariates for babies include APGAR, gender, number of births at a time, weight, circumference of the head, and height. Results/Conclusion: The results revealed that Wei, Lin and Weissfeld Model (WLWM) fit the data well. The covariates age, abortion, gender, number, APGAR, weight and head were found to have a significant effect.