Journal of Multidisciplinary Healthcare (Feb 2024)
Hierarchical Predictors of Mortality in Neonatal Sepsis at Jimma Medical Center, Ethiopia: A Case–Control Study
Abstract
Daniel Geleta,1,* Gemeda Abebe,1,2,* Netsanet Workneh,3,* Mekdes Ararso,3,* Tsion Tilahun,3,* Getenet Beyene1,* 1School of Medical Laboratory Sciences, Faculty of Health Sciences, Jimma University, Jimma, Oromia, Ethiopia; 2Mycobacteriology Research Center, Institute of Health, Jimma University, Jimma, Oromia, Ethiopia; 3Department of Pediatrics and Child Health, Faculty of Medicine, Jimma University, Jimma, Oromia, Ethiopia*These authors contributed equally to this workCorrespondence: Daniel Geleta, School of Medical Laboratory Sciences, Faculty of Health Sciences, Jimma University, Jimma, Oromia, P.O.Box. 378, Ethiopia, Tel +2510911723400, Email [email protected]: Neonatal sepsis made the neonatal period the most perilous time for child survival, and it continued to cause preventable mortalities worldwide. These mortalities stem from the interaction of several factors that have not been sufficiently studied and, in some cases, remain overlooked. Thus, the study aims to investigate the predictors of mortality that arise from the interaction of these factors and quantitatively determine their etiologic fraction.Methods: A case–control study with hierarchical data input was conducted at Jimma Medical Center (JMC) in Oromia, Ethiopia, spanning from May 2022 to July 2023. It employed logistic regression to calculate adjusted odds ratios (AORs) and their corresponding 95% confidence intervals (CI) at a significance level of p ≤ 0.05. The model adjusted odds ratios (ORs) for variables within each level and farther levels and presented an etiologic fraction (EF), indicating the proportion of neonatal mortality attributable to specific factors.Results: The analysis of 67 cases and 268 controls unveiled significant predictors of mortality in sepsis that emerged from distal, intermediate, and proximal levels. In the final model, thus, rural residence [AOR 3.1; 95% CI (1.5, 6.3), p ≤ 0.01], prolonged labor [AOR 4.5; 95% CI (2.2, 9.3), p ≤ 0.01], prematurity [AOR 3.9; 95% CI (1.9, 7.9), P ≤ 0.0], gram-negative bacteremia [AOR 3.8; 95% CI (1.9, 7.6); P ≤ 0.01], convulsion [AOR 3.2; 95% CI (1.6, 6.4); P ≤ 0.03], low birth weight [AOR 2.7; 95% CI (1.3, 5.4); P≤ 0.01], and delayed breastfeeding [AOR 2.5; 95% CI (1.2, 4.9); P ≤ 0.01] attributed a variable percentage of mortality.Conclusion: Factors emerging and interacting at distal (residence), intermediate (prolonged labor), and proximal (prematurity, birth weight, convulsion, bacterial etiology, and feeding) levels influence neonatal mortality in sepsis at JMC. Therefore, concurrently improving rural family characteristics, managing labor duration, strengthening diagnostic stewardship, and promoting essential newborn care can actively prevent and reduce these mortalities.Plain Language Summary: The existing body of literature indicates that neonatal mortality in sepsis is influenced by a complex interplay of factors at different hierarchical levels. These factors encompass maternal characteristics, neonatal health status, healthcare system capacity, and socio-economic conditions. To accurately predict outcomes related to neonatal sepsis mortality, it is vital to have a comprehensive understanding of the intricate relationship among these factors. However, previous studies have not thoroughly explored the extent and role of these factors in relation to neonatal sepsis mortality. In a recent study, researchers conducted a comprehensive investigation into the implications of factors at three levels: distal, intermediate, and proximate. Employing a case–control design and hierarchical data input, the study aimed to explore the etiological fraction associated with each level. The findings of this study shed light on the presence, interaction, and contribution of predictors at each level, emphasizing the vital importance of addressing factors at all levels to effectively prevent and control neonatal mortality in sepsis.Keywords: bacteremia, factor interaction, hierarchical predictors, neonatal sepsis
