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Predictors of Neonatal Mortality: A Retrospective Cross-Sectional Study From the Special Newborn Care Unit of a Tertiary Care Hospital
Background In India, a significant number of newborns die each year, with Madhya Pradesh having the highest neonatal mortality rate. However, there is a lack of information on factors that can predict neonatal mortality. Objective This study aimed to examine the factors influencing neonatal mortalit...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cureus
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10160311/ https://www.ncbi.nlm.nih.gov/pubmed/37153252 http://dx.doi.org/10.7759/cureus.37143 |
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author | Singh, Sandhya Agrawal, Roopa Agarwal, Gaurav Das, Abhijit Sahu, Rupesh |
author_facet | Singh, Sandhya Agrawal, Roopa Agarwal, Gaurav Das, Abhijit Sahu, Rupesh |
author_sort | Singh, Sandhya |
collection | PubMed |
description | Background In India, a significant number of newborns die each year, with Madhya Pradesh having the highest neonatal mortality rate. However, there is a lack of information on factors that can predict neonatal mortality. Objective This study aimed to examine the factors influencing neonatal mortality among neonates admitted to a tertiary care centre's special newborn care unit (SNCU). Methods This retrospective record-based observational study was done at a tertiary care centre, where data from the special newborn care unit (SNCU) from 1st January 2021 to 31st December 2021 was used. We included data of all newborns who were treated in SNCU during the said period and excluded those who got referred or left against medical advice. We abstracted data on age at admission, gender, category, maturity status, birth weight, place of delivery, mode of transport, type of admission, indication of admission, duration of stay and outcome. Qualitative variables were described using frequency and percentage. The chi-square test was used to find out the association of different variables with the outcome, while multivariate logistic regression was conducted to identify risk factors of neonatal mortality. A p-value of <0.05 was considered significant. Results We finalized data of 1052 neonates for analysis. Among them, 846 neonates were successfully discharged while 206 neonates were deceased. The major cause of admission was perinatal asphyxia followed by prematurity. The major cause of mortality in this study was sepsis followed by respiratory distress syndrome, birth asphyxia, and prematurity. Mortality of neonates was significantly associated with maturity status, birth weight, place of delivery, age during admission and duration of stay. Prematurity (OR=3.762, 95% CI:1.93-7.33), birth weight 1000-1499g (OR=4.78, 95% CI:2.21-10.32), birth weight <1000g (OR=25.11, 95% CI:5.71-110.24), age at admission <1-day (OR=2.312, 95% CI:1.03-5.19), duration of stay 1-3-days (OR=12.98, 95% CI:7.48-22.52) and <1-day (OR=1271.88, 95% CI:121.39-13325.69) were significant predictors of mortality in our study. Conclusion Our study emphasizes monitoring and addressing risk factors like maturity status, birth weight, and age at admission to reduce neonatal mortality, with a focus on early management of preterm births and low birth weight. |
format | Online Article Text |
id | pubmed-10160311 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cureus |
record_format | MEDLINE/PubMed |
spelling | pubmed-101603112023-05-06 Predictors of Neonatal Mortality: A Retrospective Cross-Sectional Study From the Special Newborn Care Unit of a Tertiary Care Hospital Singh, Sandhya Agrawal, Roopa Agarwal, Gaurav Das, Abhijit Sahu, Rupesh Cureus Pediatrics Background In India, a significant number of newborns die each year, with Madhya Pradesh having the highest neonatal mortality rate. However, there is a lack of information on factors that can predict neonatal mortality. Objective This study aimed to examine the factors influencing neonatal mortality among neonates admitted to a tertiary care centre's special newborn care unit (SNCU). Methods This retrospective record-based observational study was done at a tertiary care centre, where data from the special newborn care unit (SNCU) from 1st January 2021 to 31st December 2021 was used. We included data of all newborns who were treated in SNCU during the said period and excluded those who got referred or left against medical advice. We abstracted data on age at admission, gender, category, maturity status, birth weight, place of delivery, mode of transport, type of admission, indication of admission, duration of stay and outcome. Qualitative variables were described using frequency and percentage. The chi-square test was used to find out the association of different variables with the outcome, while multivariate logistic regression was conducted to identify risk factors of neonatal mortality. A p-value of <0.05 was considered significant. Results We finalized data of 1052 neonates for analysis. Among them, 846 neonates were successfully discharged while 206 neonates were deceased. The major cause of admission was perinatal asphyxia followed by prematurity. The major cause of mortality in this study was sepsis followed by respiratory distress syndrome, birth asphyxia, and prematurity. Mortality of neonates was significantly associated with maturity status, birth weight, place of delivery, age during admission and duration of stay. Prematurity (OR=3.762, 95% CI:1.93-7.33), birth weight 1000-1499g (OR=4.78, 95% CI:2.21-10.32), birth weight <1000g (OR=25.11, 95% CI:5.71-110.24), age at admission <1-day (OR=2.312, 95% CI:1.03-5.19), duration of stay 1-3-days (OR=12.98, 95% CI:7.48-22.52) and <1-day (OR=1271.88, 95% CI:121.39-13325.69) were significant predictors of mortality in our study. Conclusion Our study emphasizes monitoring and addressing risk factors like maturity status, birth weight, and age at admission to reduce neonatal mortality, with a focus on early management of preterm births and low birth weight. Cureus 2023-04-04 /pmc/articles/PMC10160311/ /pubmed/37153252 http://dx.doi.org/10.7759/cureus.37143 Text en Copyright © 2023, Singh et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Pediatrics Singh, Sandhya Agrawal, Roopa Agarwal, Gaurav Das, Abhijit Sahu, Rupesh Predictors of Neonatal Mortality: A Retrospective Cross-Sectional Study From the Special Newborn Care Unit of a Tertiary Care Hospital |
title | Predictors of Neonatal Mortality: A Retrospective Cross-Sectional Study From the Special Newborn Care Unit of a Tertiary Care Hospital |
title_full | Predictors of Neonatal Mortality: A Retrospective Cross-Sectional Study From the Special Newborn Care Unit of a Tertiary Care Hospital |
title_fullStr | Predictors of Neonatal Mortality: A Retrospective Cross-Sectional Study From the Special Newborn Care Unit of a Tertiary Care Hospital |
title_full_unstemmed | Predictors of Neonatal Mortality: A Retrospective Cross-Sectional Study From the Special Newborn Care Unit of a Tertiary Care Hospital |
title_short | Predictors of Neonatal Mortality: A Retrospective Cross-Sectional Study From the Special Newborn Care Unit of a Tertiary Care Hospital |
title_sort | predictors of neonatal mortality: a retrospective cross-sectional study from the special newborn care unit of a tertiary care hospital |
topic | Pediatrics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10160311/ https://www.ncbi.nlm.nih.gov/pubmed/37153252 http://dx.doi.org/10.7759/cureus.37143 |
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