TY - JOUR
T1 - The Global Network Neonatal Cause of Death algorithm for low-resource settings
AU - Garces, Ana L.
AU - McClure, Elizabeth M.
AU - Pérez, Wilton
AU - Hambidge, K. Michael
AU - Krebs, Nancy F.
AU - Figueroa, Lester
AU - Bose, Carl L.
AU - Carlo, Waldemar A.
AU - Tenge, Constance
AU - Esamai, Fabian
AU - Goudar, Shivaprasad S.
AU - Saleem, Sarah
AU - Patel, Archana B.
AU - Chiwila, Melody
AU - Chomba, Elwyn
AU - Tshefu, Antoinette
AU - Derman, Richard J.
AU - Hibberd, Patricia L.
AU - Bucher, Sherri
AU - Liechty, Edward A.
AU - Bauserman, Melissa
AU - Moore, Janet L.
AU - Koso-Thomas, Marion
AU - Miodovnik, Menachem
AU - Goldenberg, Robert L.
N1 - Publisher Copyright:
©2017 Foundation Acta Pædiatrica. Published by John Wiley & Sons Ltd
PY - 2017/6
Y1 - 2017/6
N2 - Aim: This study estimated the causes of neonatal death using an algorithm for low-resource areas, where 98% of the world's neonatal deaths occur. Methods: We enrolled women in India, Pakistan, Guatemala, the Democratic Republic of Congo, Kenya and Zambia from 2014 to 2016 and tracked their delivery and newborn outcomes for up to 28 days. Antenatal care and delivery symptoms were collected using a structured questionnaire, clinical observation and/or a physical examination. The Global Network Cause of Death algorithm was used to assign the cause of neonatal death, analysed by country and day of death. Results: One-third (33.1%) of the 3068 neonatal deaths were due to suspected infection, 30.8% to prematurity, 21.2% to asphyxia, 9.5% to congenital anomalies and 5.4% did not have a cause of death assigned. Prematurity and asphyxia-related deaths were more common on the first day of life (46.7% and 52.9%, respectively), while most deaths due to infection occurred after the first day of life (86.9%). The distribution of causes was similar to global data reported by other major studies. Conclusion: The Global Network algorithm provided a reliable cause of neonatal death in low-resource settings and can be used to inform public health strategies to reduce mortality.
AB - Aim: This study estimated the causes of neonatal death using an algorithm for low-resource areas, where 98% of the world's neonatal deaths occur. Methods: We enrolled women in India, Pakistan, Guatemala, the Democratic Republic of Congo, Kenya and Zambia from 2014 to 2016 and tracked their delivery and newborn outcomes for up to 28 days. Antenatal care and delivery symptoms were collected using a structured questionnaire, clinical observation and/or a physical examination. The Global Network Cause of Death algorithm was used to assign the cause of neonatal death, analysed by country and day of death. Results: One-third (33.1%) of the 3068 neonatal deaths were due to suspected infection, 30.8% to prematurity, 21.2% to asphyxia, 9.5% to congenital anomalies and 5.4% did not have a cause of death assigned. Prematurity and asphyxia-related deaths were more common on the first day of life (46.7% and 52.9%, respectively), while most deaths due to infection occurred after the first day of life (86.9%). The distribution of causes was similar to global data reported by other major studies. Conclusion: The Global Network algorithm provided a reliable cause of neonatal death in low-resource settings and can be used to inform public health strategies to reduce mortality.
KW - Global Network Cause of Death algorithm
KW - Infection
KW - Low- to middle-income countries
KW - Neonatal mortality
KW - Preterm birth
UR - http://www.scopus.com/inward/record.url?scp=85017198215&partnerID=8YFLogxK
U2 - 10.1111/apa.13805
DO - 10.1111/apa.13805
M3 - Article
C2 - 28240381
AN - SCOPUS:85017198215
SN - 0803-5253
VL - 106
SP - 904
EP - 911
JO - Acta Paediatrica, International Journal of Paediatrics
JF - Acta Paediatrica, International Journal of Paediatrics
IS - 6
ER -
