Author:
Yasin Shemsu,Abdisa Lemesa,Roba Hirbo Shore,Tura Abera Kenay
Abstract
BackgroundNeonatal deaths are still a major leading cause of social and economic crises. Identifying neonatal near-miss events and identifying their predictors is crucial to developing comprehensive and pertinent strategies to alleviate neonatal morbidity and death. However, neither neonatal near-miss events nor their predictors were analyzed in the study area. Therefore, this study is aimed at assessing the predictors of neonatal near-misses among neonates born at Worabe Comprehensive Specialized Hospital, Southern Ethiopia, in 2021MethodsA hospital-based unmatched case-control study was conducted from 10 November 2021 to 30 November 2021. A pre-tested, structured, and standard abstraction checklist was used to collect the data. After checking the data for completeness and consistency, it was coded and entered into Epi-Data 3.1 and then exported to Stata version 14 for analysis. All independent variables with a p-value ≤0.25 in bivariable binary logistic regression were entered into a multivariable analysis to control the confounding. Variables with p-values <0.05 were considered statistically significant.ResultsIn this study, 134 neonatal near-miss cases and 268 controls were involved. The identified predictors of neonatal near-misses were rural residence [adjusted odds ratio (AOR): 2.01; 95% confidence interval (CI): 1.31–5.84], no antenatal care (ANC) follow-up visits (AOR: 2.98; 95% CI: 1.77–5.56), antepartum hemorrhage (AOR: 2.12; 95% CI: 1.18–4.07), premature rupture of the membrane (AOR: 2.55; 95% CI: 1.54–5.67), and non-vertex fetal presentation (AOR: 3.05; 95% CI: 1.93–5.42).ConclusionThe current study identified rural residents, no ANC visits, antepartum hemorrhage, premature rupture of membrane, and non-vertex fetal presentation as being significantly associated with neonatal near-miss cases. As a result, local health planners and healthcare practitioners must collaborate in enhancing maternal healthcare services, focusing specifically on the early identification of issues and appropriate treatment.