Time to Death and Its Predictors Among Neonates Admitted with Neonatal Sepsis at Public Hospitals of West Arsi Zone, Southern Ethiopia

Introduction: According to world health organization each year, 3.6 million deaths in children under the age of five are attributable to neonatal mortality, accounting for 41% of all deaths in children under the age of five. Most of these deaths occur in low-income countries, and almost a million of these neonatal deaths either directly or indirectly related to neonatal sepsis. This study aimed to assess the time to death and its predictors among neonates admitted with neonatal sepsis at public comprehensive and general hospitals in the West Arsi zone of southern Ethiopia. Method: This multicenter institution-based retrospective follow-up study conducted from May 30 to June 30, 2023. Kobo toolbox was used for data collection. Checked for completeness, edited, and coded using Microsoft Excel. The data imported into STATA version 18 and cleaned before analysis. The incidence rate estimated for the entire study period and specified intervals of hospital stay. The Weibull regression model was selected using Akaike information criteria and Bayesian information criteria and used to analyze the relationship between the outcome and independent variables. Variables in the bi-variable analysis with p-value ≤ 0.25 were as candidates for multivariable analysis. In the multivariable analysis, statistical significance was set at p < 0.05. The association summarized using an adjusted hazard ratio (AHR) with a 95% confidence interval. Result: Of the 526 neonates with neonatal sepsis, 67 (12.7%) (95% confidence interval [CI]: 10–15.9) died. The overall incidence of neonatal mortality was 16.1 per 1000 neonatal days. The mean time to death among neonates died was 7.9 days (95% CI: 7.63, 8.19). Respiratory distress at admission (Adjusted Hazard Ratio (AHR): 0.37, 95% CI: 0.18, 0.77), breastfeeding within one hour (AHR: 3.15, 95% CI: 1.38, 7.18), gravidity (AHR: 0.37, 95% CI: 0.15, 0.88), and maternal health problems (AHR: 0.44, 95% CI: 0.25, 0.79) were found to be significant predictors of neonatal mortality. Conclusion: This study revealed that among neonates, 67 (12.7%) (95% CI: 10, 15.9) died during the follow-up period. Respiratory distress during admission, initiation of breastfeeding within one hour of birth, gravidity, and maternal health problems were predictors of mortality among neonates admitted with neonatal sepsis. Early initiation of breast feeding, monitoring of high-risk mothers, and strengthening NICU care are some of recommendations.

Authors

Institutions

Publication Details

Published
2026-04-24
DOI
https://doi.org/10.11648/j.sdph.20260101.15
Primary Topic
Neonatal and Maternal Infections
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Time to Death and Its Predictors Among Neonates Admitted with Neonatal Sepsis at Public Hospitals of West Arsi Zone, Southern Ethiopia

Zeleke Girma, Mesfin Kote, Mamud Wakeyo
Neonatal and Maternal Infections
article

Time to Death and Its Predictors Among Neonates Admitted with Neonatal Sepsis at Public Hospitals of West Arsi Zone, Southern Ethiopia

Zeleke Girma, Mesfin Kote, Mamud Wakeyo
article en

Abstract

Introduction: According to world health organization each year, 3.6 million deaths in children under the age of five are attributable to neonatal mortality, accounting for 41% of all deaths in children under the age of five. Most of these deaths occur in low-income countries, and almost a million of these neonatal deaths either directly or indirectly related to neonatal sepsis. This study aimed to assess the time to death and its predictors among neonates admitted with neonatal sepsis at public comprehensive and general hospitals in the West Arsi zone of southern Ethiopia. Method: This multicenter institution-based retrospective follow-up study conducted from May 30 to June 30, 2023. Kobo toolbox was used for data collection. Checked for completeness, edited, and coded using Microsoft Excel. The data imported into STATA version 18 and cleaned before analysis. The incidence rate estimated for the entire study period and specified intervals of hospital stay. The Weibull regression model was selected using Akaike information criteria and Bayesian information criteria and used to analyze the relationship between the outcome and independent variables. Variables in the bi-variable analysis with p-value ≤ 0.25 were as candidates for multivariable analysis. In the multivariable analysis, statistical significance was set at p < 0.05. The association summarized using an adjusted hazard ratio (AHR) with a 95% confidence interval. Result: Of the 526 neonates with neonatal sepsis, 67 (12.7%) (95% confidence interval [CI]: 10–15.9) died. The overall incidence of neonatal mortality was 16.1 per 1000 neonatal days. The mean time to death among neonates died was 7.9 days (95% CI: 7.63, 8.19). Respiratory distress at admission (Adjusted Hazard Ratio (AHR): 0.37, 95% CI: 0.18, 0.77), breastfeeding within one hour (AHR: 3.15, 95% CI: 1.38, 7.18), gravidity (AHR: 0.37, 95% CI: 0.15, 0.88), and maternal health problems (AHR: 0.44, 95% CI: 0.25, 0.79) were found to be significant predictors of neonatal mortality. Conclusion: This study revealed that among neonates, 67 (12.7%) (95% CI: 10, 15.9) died during the follow-up period. Respiratory distress during admission, initiation of breastfeeding within one hour of birth, gravidity, and maternal health problems were predictors of mortality among neonates admitted with neonatal sepsis. Early initiation of breast feeding, monitoring of high-risk mothers, and strengthening NICU care are some of recommendations.

Vol. 1(1)
Wolaita Sodo University (ET), Arba Minch University (ET)
Openalex Percentile: Top 6%
Neonatal and Maternal Infections
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.