Incidence, Risk Factors and Neonatal Outcomes of Unexpected Term Newborn Admissions at Kenyatta National Hospital

Abstract

Background: Whilst admission to neonatal units (NBU) is usually thought of in terms of congenital anomalies and prematurity, admission of term neonates, though unexpected, is not rare. The proportion of term newborns admitted to newborn units annually is approximately 5-18%, and most of these are unexpected. The incidence of term newborn admissions to neonatal units in Kenya is currently unknown. Globally, factors associated with admission of term neonates include extremes of maternal age, minority ethnicity, low socioeconomic status, operative mode of birth, elective delivery before 39 weeks, maternal hypertension and maternal diabetes. There are limited local and regional studies on the burden of and risk factors for unexpected term newborn admissions. This study used hospital data and records to determine the incidence and describe the risk factors of unexpected term newborn admissions to neonatal units, as well as the neonatal outcomes. Objective: To determine the incidence, risk factors, and early (one week) neonatal outcomes of unexpected term newborn unit (NBU) admissions at Kenyatta National Hospital (KNH). Methods: Study Design: This was a descriptive, hospital-based study comprising 2 components: an incidence study and a nested case-control study to evaluate the risk factors for NBU admission. Study Population: All term (37+0 – 41+6), live-born neonates born at KNH between Jan 1st 2019 – Dec 31st 2019 and the mothers of those newborns. A case was a term neonate admitted to NBU/NICU during the study period. The mother of a case was a mother-case. A control was a term neonate who was born during the study period and was not admitted to NBU/NICU. The mother of a control was a mother-control. Study Site: Kenyatta National Hospital. Sample Size: A sample size of 50 cases and 100 controls was used. Data Collection: Data was collected using a data extraction form, from files of the identified cases and selected controls. Data Analysis: Data was analysed using the Statistical Package for Social Sciences version 23 (SPSS). The incidence of unexpected term newborn admissions was determined by getting the total of all unexpected term newborn admissions taken as a 17 proportion of all the term live-born neonates born at the KNH during the study period and reported as a percentage. Comparison of the maternal sociodemographic and clinical characteristics, as well as neonatal characteristics were done with the use of Pearson Chi-square test. Neonatal outcomes were reported as frequencies and proportions. Univariate and multivariate analysis with the use of logistic regression was performed on the antepartum and intrapartum risk factors, maternal and clinical characteristics, and neonatal characteristics. Crude and adjusted Odds Ratio with their 95% confidence interval were reported. All statistical tests were considered to be significant where the p-value < 0.05. Results: Of the 10,315 term neonates born at KNH during the study period, 1,729 (16.76% (95% CI: 16.05%, 17.50%)) were unexpected term admissions. The median length of stay was 5.0 (IQR 3.0 – 6.5) days and 26% of neonates remained admitted after 1 week. The death rate within 1 week was 2%. In the fully adjusted model, the factors associated with the highest odds for term admission included: maternal comorbidities (aOR3.4 [95% CI: 1.04, 11.2]), antenatal Hb <10 g/dl (aOR3.0 [95% CI: 0.9, 10.8]), thin MSL (aOR11.5 [95% CI: 2.2, 59.5]), elective CS (aOR41.2 [95% CI: 7.0, 241.2]) and emergency CS (aOR4.3 [95% CI: 1.4, 13.3]). An identified protective factor was delivery in late term. Conclusion: This study contributes to the currently limited understanding of term, neonatal admission rates as a marker of obstetrical care quality. The incidence of unexpected term neonatal admissions at KNH is on the higher end of the worldwide range. Mothers at risk should receive augmented antenatal care to attenuate term neonatal admission. The crucial contributing factors should be earmarked and analysed further over a longer timeframe with a multi-disciplinary team to reduce the rate of admissions and enhance quality of care