Cargando…
Predictors of time to death among preterm neonates admitted to neonatal intensive care units at public hospitals in southern Ethiopia: A cohort study
BACKGROUND: Although the survival of preterm neonates has improved, thanks to advanced and specialized neonatal intensive care, it remains the main reason for neonatal admission, death, and risk of lifelong complication. In this study, we assessed time to death and its predictors among preterm neona...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569587/ https://www.ncbi.nlm.nih.gov/pubmed/37824535 http://dx.doi.org/10.1371/journal.pone.0283143 |
_version_ | 1785119578293010432 |
---|---|
author | Huka, Alo Edin Oljira, Lemessa Weldesenbet, Adisu Birhanu Bushra, Abdulmalik Abdela Ahmed, Ibsa Abdusemed Tura, Abera Kenay Tuluka, Angefa Ayele |
author_facet | Huka, Alo Edin Oljira, Lemessa Weldesenbet, Adisu Birhanu Bushra, Abdulmalik Abdela Ahmed, Ibsa Abdusemed Tura, Abera Kenay Tuluka, Angefa Ayele |
author_sort | Huka, Alo Edin |
collection | PubMed |
description | BACKGROUND: Although the survival of preterm neonates has improved, thanks to advanced and specialized neonatal intensive care, it remains the main reason for neonatal admission, death, and risk of lifelong complication. In this study, we assessed time to death and its predictors among preterm neonates admitted to neonatal intensive care units (NICU) at public hospitals in southern Ethiopia. METHODS: A hospital based retrospective cohort was conducted among preterm neonates admitted to NICU at public hospitals in west Guji and Borena zones, Oromia National Regional State, southern Ethiopia. Simple random sampling technique was used to select records of preterm neonates admitted to both major hospitals in the study area. Data on neonatal condition, obstetric information, and status at discharge were collected from admission to discharge by trained research assistant through review of their medical records. Kaplan Meir curve and Log rank test were used to estimate the survival time and compare survival curves between variables. Cox-Proportional Hazards model was used to identify significant predictors of time to death at p<0.05. RESULT: Of 510 neonates enrolled, 130(25.5%; 95% CI: 22–29) neonates died at discharge or 28days. The median survival time was 18 days with an interquartile range of (IQR = 6, 24). The overall incidence of neonatal mortality was 47.7 (95% CI: 40.2–56.7) per 1000 neonatal days. In the multivariable cox-proportional hazard analysis, lack of antenatal care (AHR: 7.1; 95%CI: 4–12.65), primipara (AHR: 2.3; 95% CI: 1.16–4.43), pregnancy complications (AHR: 3.4; 95% CI: 1.94–6.0), resuscitation at birth (AHR: 2.1, 95% CI: 0.28–0.77) and not receiving Kangaroo mother care (AHR: 9.3, 95% CI: 4.36–19.9) were predictors of preterm neonatal death. CONCLUSION: Despite admission to NICU for advanced care and follow up, mortality of preterm neonates was found to be high in the study settings. Addressing major intrapartum complications is required to improve survival of neonates admitted to NICU. |
format | Online Article Text |
id | pubmed-10569587 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-105695872023-10-13 Predictors of time to death among preterm neonates admitted to neonatal intensive care units at public hospitals in southern Ethiopia: A cohort study Huka, Alo Edin Oljira, Lemessa Weldesenbet, Adisu Birhanu Bushra, Abdulmalik Abdela Ahmed, Ibsa Abdusemed Tura, Abera Kenay Tuluka, Angefa Ayele PLoS One Research Article BACKGROUND: Although the survival of preterm neonates has improved, thanks to advanced and specialized neonatal intensive care, it remains the main reason for neonatal admission, death, and risk of lifelong complication. In this study, we assessed time to death and its predictors among preterm neonates admitted to neonatal intensive care units (NICU) at public hospitals in southern Ethiopia. METHODS: A hospital based retrospective cohort was conducted among preterm neonates admitted to NICU at public hospitals in west Guji and Borena zones, Oromia National Regional State, southern Ethiopia. Simple random sampling technique was used to select records of preterm neonates admitted to both major hospitals in the study area. Data on neonatal condition, obstetric information, and status at discharge were collected from admission to discharge by trained research assistant through review of their medical records. Kaplan Meir curve and Log rank test were used to estimate the survival time and compare survival curves between variables. Cox-Proportional Hazards model was used to identify significant predictors of time to death at p<0.05. RESULT: Of 510 neonates enrolled, 130(25.5%; 95% CI: 22–29) neonates died at discharge or 28days. The median survival time was 18 days with an interquartile range of (IQR = 6, 24). The overall incidence of neonatal mortality was 47.7 (95% CI: 40.2–56.7) per 1000 neonatal days. In the multivariable cox-proportional hazard analysis, lack of antenatal care (AHR: 7.1; 95%CI: 4–12.65), primipara (AHR: 2.3; 95% CI: 1.16–4.43), pregnancy complications (AHR: 3.4; 95% CI: 1.94–6.0), resuscitation at birth (AHR: 2.1, 95% CI: 0.28–0.77) and not receiving Kangaroo mother care (AHR: 9.3, 95% CI: 4.36–19.9) were predictors of preterm neonatal death. CONCLUSION: Despite admission to NICU for advanced care and follow up, mortality of preterm neonates was found to be high in the study settings. Addressing major intrapartum complications is required to improve survival of neonates admitted to NICU. Public Library of Science 2023-10-12 /pmc/articles/PMC10569587/ /pubmed/37824535 http://dx.doi.org/10.1371/journal.pone.0283143 Text en © 2023 Huka et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Huka, Alo Edin Oljira, Lemessa Weldesenbet, Adisu Birhanu Bushra, Abdulmalik Abdela Ahmed, Ibsa Abdusemed Tura, Abera Kenay Tuluka, Angefa Ayele Predictors of time to death among preterm neonates admitted to neonatal intensive care units at public hospitals in southern Ethiopia: A cohort study |
title | Predictors of time to death among preterm neonates admitted to neonatal intensive care units at public hospitals in southern Ethiopia: A cohort study |
title_full | Predictors of time to death among preterm neonates admitted to neonatal intensive care units at public hospitals in southern Ethiopia: A cohort study |
title_fullStr | Predictors of time to death among preterm neonates admitted to neonatal intensive care units at public hospitals in southern Ethiopia: A cohort study |
title_full_unstemmed | Predictors of time to death among preterm neonates admitted to neonatal intensive care units at public hospitals in southern Ethiopia: A cohort study |
title_short | Predictors of time to death among preterm neonates admitted to neonatal intensive care units at public hospitals in southern Ethiopia: A cohort study |
title_sort | predictors of time to death among preterm neonates admitted to neonatal intensive care units at public hospitals in southern ethiopia: a cohort study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569587/ https://www.ncbi.nlm.nih.gov/pubmed/37824535 http://dx.doi.org/10.1371/journal.pone.0283143 |
work_keys_str_mv | AT hukaaloedin predictorsoftimetodeathamongpretermneonatesadmittedtoneonatalintensivecareunitsatpublichospitalsinsouthernethiopiaacohortstudy AT oljiralemessa predictorsoftimetodeathamongpretermneonatesadmittedtoneonatalintensivecareunitsatpublichospitalsinsouthernethiopiaacohortstudy AT weldesenbetadisubirhanu predictorsoftimetodeathamongpretermneonatesadmittedtoneonatalintensivecareunitsatpublichospitalsinsouthernethiopiaacohortstudy AT bushraabdulmalikabdela predictorsoftimetodeathamongpretermneonatesadmittedtoneonatalintensivecareunitsatpublichospitalsinsouthernethiopiaacohortstudy AT ahmedibsaabdusemed predictorsoftimetodeathamongpretermneonatesadmittedtoneonatalintensivecareunitsatpublichospitalsinsouthernethiopiaacohortstudy AT turaaberakenay predictorsoftimetodeathamongpretermneonatesadmittedtoneonatalintensivecareunitsatpublichospitalsinsouthernethiopiaacohortstudy AT tulukaangefaayele predictorsoftimetodeathamongpretermneonatesadmittedtoneonatalintensivecareunitsatpublichospitalsinsouthernethiopiaacohortstudy |