Development of criteria for identifying neonatal near‐miss cases: analysis of two WHO multicountry cross‐sectional studies
- 18 March 2014
- journal article
- research article
- Published by Wiley in BJOG: An International Journal of Obstetrics and Gynaecology
- Vol. 121 (s1), 110-118
- https://doi.org/10.1111/1471-0528.12637
Abstract
To develop and test markers of neonatal severe morbidity for the identification of neonatal near-miss cases. This is a database analysis of two World Health Organization cross-sectional studies: the Global Survey on Maternal and Perinatal Health (WHOGS) and the Multicountry Survey on Maternal and Newborn Health (WHOMCS). The WHOGS was performed in 373 health facilities in 24 countries (2004-2008). The WHOMCS was conducted in 359 health facilities in 29 countries (2010-2011). Data were collected from hospital records of all women admitted for delivery and their respective neonates. Pragmatic markers (birthweight <1750 g, Apgar score at 5 minutes <7, and gestational age <33 weeks) were developed with WHOGS data and validated with WHOMCS data. The diagnostic accuracy of neonatal characteristics and management markers of severity was determined in the WHOMCS. This analysis included 290 610 liveborn neonates from WHOGS and 310 436 liveborn neonates from WHOMCS. The diagnostic accuracy of pragmatic and management markers of severity for identifying early neonatal deaths was very high: sensitivity, 92.8% (95% CI 91.8-93.7%); specificity, 92.7% (95% CI 92.6-92.8%); positive likelihood ratio, 12.7 (95% CI 12.5-12.9); negative likelihood ratio, 0.08 (95% CI 0.07-0.09); diagnostic odds ratio, 163.4 (95% CI 141.6-188.4). A positive association was found between the frequency of neonatal near-miss cases and Human Development Index. Newborn infants presenting selected markers of severity and surviving the first neonatal week could be considered as neonatal near-miss cases. This definition and criteria may be seen as a basis for future applications of the near-miss concept in neonatal health. These tools can be used to inform policy makers on how best to apply scarce resources for improving the quality of care and reducing neonatal mortality.This publication has 21 references indexed in Scilit:
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