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Predictors of neonatal mortality: development and validation of prognostic models using prospective data from rural Bangladesh
OBJECTIVE: To assess the extent to which maternal histories of newborn danger signs independently or combined with birth weight and/or gestational age (GA) can capture and/or predict postsecond day (age>48 hours) neonatal death. METHODS: Data from a cluster-randomised trial conducted in rural Ban...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042570/ https://www.ncbi.nlm.nih.gov/pubmed/32133171 http://dx.doi.org/10.1136/bmjgh-2019-001983 |
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author | Khan, Farhad A Mullany, Luke C Wu, Lee F-S Ali, Hasmot Shaikh, Saijuddin Alland, Kelsey West Jr, Keith P Labrique, Alain B |
author_facet | Khan, Farhad A Mullany, Luke C Wu, Lee F-S Ali, Hasmot Shaikh, Saijuddin Alland, Kelsey West Jr, Keith P Labrique, Alain B |
author_sort | Khan, Farhad A |
collection | PubMed |
description | OBJECTIVE: To assess the extent to which maternal histories of newborn danger signs independently or combined with birth weight and/or gestational age (GA) can capture and/or predict postsecond day (age>48 hours) neonatal death. METHODS: Data from a cluster-randomised trial conducted in rural Bangladesh were split into development and validation sets. The prompted recall of danger signs and birth weight measurements were collected within 48 hours postchildbirth. Maternally recalled danger signs included cyanosis (any part of the infant’s body was blue at birth), non-cephalic presentation (part other than head came out first at birth), lethargy (weak or no arm/leg movement and/or cry at birth), trouble suckling (infant unable to suckle/feed normally in the 2 days after birth or before death, collected 1-month postpartum or from verbal autopsy). Last menstrual period was collected at maternal enrolment early in pregnancy. Singleton newborns surviving 2 days past childbirth were eligible for analysis. Prognostic multivariable models were developed and internally validated. RESULTS: Recalling ≥1 sign of lethargy, cyanosis, non-cephalic presentation or trouble suckling identified postsecond day neonatal death with 65.3% sensitivity, 60.8% specificity, 2.1% positive predictive value (PPV) and 99.3% negative predictive value (NPV) in the development set. Requiring either lethargy or weight <2.5 kg identified 89.1% of deaths (at 39.7% specificity, 1.9% PPV and 99.6% NPV) while lethargy or preterm birth (<37 weeks) captured 81.0% of deaths (at 53.6% specificity, 2.3% PPV and 99.5% NPV). A simplified model (birth weight, GA, lethargy, cyanosis, non-cephalic presentation and trouble suckling) predicted death with good discrimination (validation area under the receiver-operator characteristic curve (AUC) 0.80, 95% CI 0.73 to 0.87). A further simplified model (GA, non-cephalic presentation, lethargy, trouble suckling) predicted death with moderate discrimination (validation AUC 0.74, 95% CI 0.66 to 0.81). CONCLUSION: Maternally recalled danger signs, coupled to either birth weight or GA, can predict and capture postsecond day neonatal death with high discrimination and sensitivity. |
format | Online Article Text |
id | pubmed-7042570 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-70425702020-03-04 Predictors of neonatal mortality: development and validation of prognostic models using prospective data from rural Bangladesh Khan, Farhad A Mullany, Luke C Wu, Lee F-S Ali, Hasmot Shaikh, Saijuddin Alland, Kelsey West Jr, Keith P Labrique, Alain B BMJ Glob Health Original Research OBJECTIVE: To assess the extent to which maternal histories of newborn danger signs independently or combined with birth weight and/or gestational age (GA) can capture and/or predict postsecond day (age>48 hours) neonatal death. METHODS: Data from a cluster-randomised trial conducted in rural Bangladesh were split into development and validation sets. The prompted recall of danger signs and birth weight measurements were collected within 48 hours postchildbirth. Maternally recalled danger signs included cyanosis (any part of the infant’s body was blue at birth), non-cephalic presentation (part other than head came out first at birth), lethargy (weak or no arm/leg movement and/or cry at birth), trouble suckling (infant unable to suckle/feed normally in the 2 days after birth or before death, collected 1-month postpartum or from verbal autopsy). Last menstrual period was collected at maternal enrolment early in pregnancy. Singleton newborns surviving 2 days past childbirth were eligible for analysis. Prognostic multivariable models were developed and internally validated. RESULTS: Recalling ≥1 sign of lethargy, cyanosis, non-cephalic presentation or trouble suckling identified postsecond day neonatal death with 65.3% sensitivity, 60.8% specificity, 2.1% positive predictive value (PPV) and 99.3% negative predictive value (NPV) in the development set. Requiring either lethargy or weight <2.5 kg identified 89.1% of deaths (at 39.7% specificity, 1.9% PPV and 99.6% NPV) while lethargy or preterm birth (<37 weeks) captured 81.0% of deaths (at 53.6% specificity, 2.3% PPV and 99.5% NPV). A simplified model (birth weight, GA, lethargy, cyanosis, non-cephalic presentation and trouble suckling) predicted death with good discrimination (validation area under the receiver-operator characteristic curve (AUC) 0.80, 95% CI 0.73 to 0.87). A further simplified model (GA, non-cephalic presentation, lethargy, trouble suckling) predicted death with moderate discrimination (validation AUC 0.74, 95% CI 0.66 to 0.81). CONCLUSION: Maternally recalled danger signs, coupled to either birth weight or GA, can predict and capture postsecond day neonatal death with high discrimination and sensitivity. BMJ Publishing Group 2020-01-27 /pmc/articles/PMC7042570/ /pubmed/32133171 http://dx.doi.org/10.1136/bmjgh-2019-001983 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Research Khan, Farhad A Mullany, Luke C Wu, Lee F-S Ali, Hasmot Shaikh, Saijuddin Alland, Kelsey West Jr, Keith P Labrique, Alain B Predictors of neonatal mortality: development and validation of prognostic models using prospective data from rural Bangladesh |
title | Predictors of neonatal mortality: development and validation of prognostic models using prospective data from rural Bangladesh |
title_full | Predictors of neonatal mortality: development and validation of prognostic models using prospective data from rural Bangladesh |
title_fullStr | Predictors of neonatal mortality: development and validation of prognostic models using prospective data from rural Bangladesh |
title_full_unstemmed | Predictors of neonatal mortality: development and validation of prognostic models using prospective data from rural Bangladesh |
title_short | Predictors of neonatal mortality: development and validation of prognostic models using prospective data from rural Bangladesh |
title_sort | predictors of neonatal mortality: development and validation of prognostic models using prospective data from rural bangladesh |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042570/ https://www.ncbi.nlm.nih.gov/pubmed/32133171 http://dx.doi.org/10.1136/bmjgh-2019-001983 |
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