Cargando…
Predictors of Neonatal Sepsis in Hospitals at Wolaita Sodo Town, Southern Ethiopia: Institution-Based Unmatched Case-Control Study, 2019
BACKGROUND: Neonatal sepsis plays a significant role in neonates' mortality in developing countries accounting for 30-50% of total deaths each year. Gaining insight into neonatal sepsis predictors will provide an opportunity for the stakeholders to reduce the causes of neonatal sepsis. This res...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7647789/ https://www.ncbi.nlm.nih.gov/pubmed/33178290 http://dx.doi.org/10.1155/2020/3709672 |
_version_ | 1783606981031886848 |
---|---|
author | Alemayehu, Atkuregn Alemayehu, Mihiretu Arba, Aseb Abebe, Hanna Goa, Abraham Paulos, Kebreab Obsa, Mohammed Suleiman |
author_facet | Alemayehu, Atkuregn Alemayehu, Mihiretu Arba, Aseb Abebe, Hanna Goa, Abraham Paulos, Kebreab Obsa, Mohammed Suleiman |
author_sort | Alemayehu, Atkuregn |
collection | PubMed |
description | BACKGROUND: Neonatal sepsis plays a significant role in neonates' mortality in developing countries accounting for 30-50% of total deaths each year. Gaining insight into neonatal sepsis predictors will provide an opportunity for the stakeholders to reduce the causes of neonatal sepsis. This research is aimed at determining the predictors of neonatal sepsis at Wolaita Sodo University Teaching Referral Hospital and Sodo Christian General Hospital, Ethiopia, April-July 2019. METHOD: This study employed an institution-based unmatched case-control study by selecting neonates in selected hospitals through consecutive sampling technique. The cases of this study are neonates diagnosed with sepsis. The study used a pretested structured questionnaire for a face-to-face interview to collect data from index mothers. Besides, the review of the record was done using checklists. The data were entered into EpiData version 3.1 and exported to Statistical Package for the Social Sciences version 24.0 for analysis. The study used descriptive, bivariate, and multivariate analyses. The odds ratio with 95% confidence interval was used to measure the association's strength. p < 0.05 was the cut-off point for declaration of statistical significance for the multivariate analysis. RESULTS: Factors significantly associated with neonatal sepsis among neonates were maternal age of 15-20 years and 21-30 years, mothers with low income/wealth, history of urinary tract infections/sexually transmitted infections, presence of intrapartum infections, antenatal care follow‐up < 3 visits, Apgar (Appearance, Pulse, Grimace, Activity, and Respiration) score < 7, low birth weight, and the time in which breastfeeding started after delivery < 60 minutes. CONCLUSION: Maternal age, wealth/income, maternal urinary tract infections/sexually transmitted infections, intrapartum fever, antenatal care visit ≤ 3 times, Apgar score < 7, low birth weight, and starting time of breastfeeding were independent predictors of neonatal sepsis. Therefore, maternal health education during antenatal care visits, perinatal and newborn care, and early initiation of breastfeeding might decrease neonatal mortality and morbidity due to sepsis. |
format | Online Article Text |
id | pubmed-7647789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-76477892020-11-10 Predictors of Neonatal Sepsis in Hospitals at Wolaita Sodo Town, Southern Ethiopia: Institution-Based Unmatched Case-Control Study, 2019 Alemayehu, Atkuregn Alemayehu, Mihiretu Arba, Aseb Abebe, Hanna Goa, Abraham Paulos, Kebreab Obsa, Mohammed Suleiman Int J Pediatr Research Article BACKGROUND: Neonatal sepsis plays a significant role in neonates' mortality in developing countries accounting for 30-50% of total deaths each year. Gaining insight into neonatal sepsis predictors will provide an opportunity for the stakeholders to reduce the causes of neonatal sepsis. This research is aimed at determining the predictors of neonatal sepsis at Wolaita Sodo University Teaching Referral Hospital and Sodo Christian General Hospital, Ethiopia, April-July 2019. METHOD: This study employed an institution-based unmatched case-control study by selecting neonates in selected hospitals through consecutive sampling technique. The cases of this study are neonates diagnosed with sepsis. The study used a pretested structured questionnaire for a face-to-face interview to collect data from index mothers. Besides, the review of the record was done using checklists. The data were entered into EpiData version 3.1 and exported to Statistical Package for the Social Sciences version 24.0 for analysis. The study used descriptive, bivariate, and multivariate analyses. The odds ratio with 95% confidence interval was used to measure the association's strength. p < 0.05 was the cut-off point for declaration of statistical significance for the multivariate analysis. RESULTS: Factors significantly associated with neonatal sepsis among neonates were maternal age of 15-20 years and 21-30 years, mothers with low income/wealth, history of urinary tract infections/sexually transmitted infections, presence of intrapartum infections, antenatal care follow‐up < 3 visits, Apgar (Appearance, Pulse, Grimace, Activity, and Respiration) score < 7, low birth weight, and the time in which breastfeeding started after delivery < 60 minutes. CONCLUSION: Maternal age, wealth/income, maternal urinary tract infections/sexually transmitted infections, intrapartum fever, antenatal care visit ≤ 3 times, Apgar score < 7, low birth weight, and starting time of breastfeeding were independent predictors of neonatal sepsis. Therefore, maternal health education during antenatal care visits, perinatal and newborn care, and early initiation of breastfeeding might decrease neonatal mortality and morbidity due to sepsis. Hindawi 2020-10-30 /pmc/articles/PMC7647789/ /pubmed/33178290 http://dx.doi.org/10.1155/2020/3709672 Text en Copyright © 2020 Atkuregn Alemayehu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Alemayehu, Atkuregn Alemayehu, Mihiretu Arba, Aseb Abebe, Hanna Goa, Abraham Paulos, Kebreab Obsa, Mohammed Suleiman Predictors of Neonatal Sepsis in Hospitals at Wolaita Sodo Town, Southern Ethiopia: Institution-Based Unmatched Case-Control Study, 2019 |
title | Predictors of Neonatal Sepsis in Hospitals at Wolaita Sodo Town, Southern Ethiopia: Institution-Based Unmatched Case-Control Study, 2019 |
title_full | Predictors of Neonatal Sepsis in Hospitals at Wolaita Sodo Town, Southern Ethiopia: Institution-Based Unmatched Case-Control Study, 2019 |
title_fullStr | Predictors of Neonatal Sepsis in Hospitals at Wolaita Sodo Town, Southern Ethiopia: Institution-Based Unmatched Case-Control Study, 2019 |
title_full_unstemmed | Predictors of Neonatal Sepsis in Hospitals at Wolaita Sodo Town, Southern Ethiopia: Institution-Based Unmatched Case-Control Study, 2019 |
title_short | Predictors of Neonatal Sepsis in Hospitals at Wolaita Sodo Town, Southern Ethiopia: Institution-Based Unmatched Case-Control Study, 2019 |
title_sort | predictors of neonatal sepsis in hospitals at wolaita sodo town, southern ethiopia: institution-based unmatched case-control study, 2019 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7647789/ https://www.ncbi.nlm.nih.gov/pubmed/33178290 http://dx.doi.org/10.1155/2020/3709672 |
work_keys_str_mv | AT alemayehuatkuregn predictorsofneonatalsepsisinhospitalsatwolaitasodotownsouthernethiopiainstitutionbasedunmatchedcasecontrolstudy2019 AT alemayehumihiretu predictorsofneonatalsepsisinhospitalsatwolaitasodotownsouthernethiopiainstitutionbasedunmatchedcasecontrolstudy2019 AT arbaaseb predictorsofneonatalsepsisinhospitalsatwolaitasodotownsouthernethiopiainstitutionbasedunmatchedcasecontrolstudy2019 AT abebehanna predictorsofneonatalsepsisinhospitalsatwolaitasodotownsouthernethiopiainstitutionbasedunmatchedcasecontrolstudy2019 AT goaabraham predictorsofneonatalsepsisinhospitalsatwolaitasodotownsouthernethiopiainstitutionbasedunmatchedcasecontrolstudy2019 AT pauloskebreab predictorsofneonatalsepsisinhospitalsatwolaitasodotownsouthernethiopiainstitutionbasedunmatchedcasecontrolstudy2019 AT obsamohammedsuleiman predictorsofneonatalsepsisinhospitalsatwolaitasodotownsouthernethiopiainstitutionbasedunmatchedcasecontrolstudy2019 |