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Clinical algorithms for the identification of sick newborns in community‐based settings
Author(s) -
KamathRayne Beena D,
MacGuire Emily R,
McClure Elizabeth M,
Goldenberg Robert L,
Jobe Alan H
Publication year - 2012
Publication title -
acta paediatrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 115
eISSN - 1651-2227
pISSN - 0803-5253
DOI - 10.1111/j.1651-2227.2011.02540.x
Subject(s) - medicine , pediatrics , intensive care medicine , vital signs , identification (biology) , algorithm , surgery , botany , computer science , biology
Clinical algorithms can be powerful tools for the identification of sick newborns at risk of neonatal mortality. Several studies have evaluated clinical signs for newborns aged 0–60 days to identify severe illness; however, few studies have focused specifically on the most vulnerable time period for neonatal death, the first week of life. Therefore, we reviewed the studies that evaluated clinical signs in newborns 0–60 days, focusing on infants 0 to <7 days. Based on a comparison of relevant studies, we then identified the common, important clinical signs shown to be useful for the identification of at‐risk newborns by health workers in community‐based and low‐resource settings. Conclusion: We concluded that further work is urgently needed to develop a clinical algorithm for widespread validation in various community‐based settings, which focuses specifically on newborns <7 days at risk of early neonatal mortality.