Abstract:
Background: Early neonatal death is death of infants in the first week of life. In 2019, 2.4 million newborns
died globally, and 99, 000 live births died in Ethiopia. Of this death, 34%-92% of deaths happen within 7 days
of postnatal period. Thus, the early neonatal period is the most critical time for an infant, requiring different
strategies to prevent mortality. Among strategies deriving and implementing early warning scores is crucial to
predict early neonatal mortality earlier upon hospital admission. However, no risk score has been derived in our
country and the study area. Therefore, this study will help for screening high-risk early neonates at admission
using easily measurable and accessible maternal and neonatal variables to estimate, and predict early neonatal
death.
Objectives: To derive and validate a risk score to predict mortality of early neonates at Felege Hiwot
Specialized Hospital neonatal intensive care unit, Bahir Dar, 2021
Methods: The document review was conducted from February 24, to April 08, 2021, on all early neonates
admitted to neonatal intensive care unit from January 1, 2018 to December 31, 2020. The total number of early
neonates included in the derivation study was 1100. Data were collected by using structured checklists prepared
on EpiCollect5 software. After exporting the data to R version 4.0.5 software, variables with (p < 0.25) from the
simple binary regression were entered into a multiple logistic regression model, and significant variables (p <
0.05) were kept in the model. The discrimination and calibration were assessed. The model was internally
validated using bootstrapping technique. To make the score easily applicable the regression coefficients from
the final multiple binary logistic regressions were used to assign integers to each variable.
Results: Admission weight, birth Apgar score, perinatal asphyxia, respiratory distress syndrome, mode of
delivery, sepsis, and gestational age at birth remained in the final multiple logistic regression prediction model.
The area under curve of receiver operating characteristic curve for early neonatal mortality score was 90.7%.
The model retained excellent discrimination under internal validation. Using the ―Youden Index‖ optimal cutoff
point for predicted probabilities of mortality 0.1363, the sensitivity, specificity, and positive predictive value,
negative predictive value was 89.4%, 82.5%, 55.5%, and 96.9%, respectively. The positive and negative
likelihood ratios of the model were also 5.10 and 0.13, respectively.
Conclusion and recommendation: The derived score has an excellent discriminative ability and good
prediction performance. This is an important tool for predicting early neonatal mortality in neonatal intensive
care units just at admission. Therefore, after external validation, this score will be a better model for application
in low and middle-income countries.
Keywords: derivation, validation, risk score, early neonatal mortality, NICU, Ethiopia