Am J Perinatol 2014; 31(06): 441-446
DOI: 10.1055/s-0033-1351658
Original Article
Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

What is the Best Predictor of Mortality in a Very Low Birth Weight Infant Population with a High Mortality Rate in a Medical Setting with Limited Resources?

M. Gooden
1   Department of Child and Adolescent Health, Faculty of Medical Sciences, The University of the West Indies, Mona, Jamaica
,
N. Younger
2   Tropical Medicine Research Institute, The University of the West Indies, Mona, Jamaica
,
H. Trotman
1   Department of Child and Adolescent Health, Faculty of Medical Sciences, The University of the West Indies, Mona, Jamaica
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Weitere Informationen

Publikationsverlauf

15. November 2012

14. Juni 2013

Publikationsdatum:
14. August 2013 (online)

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Abstract

Objective To determine the best predictor of mortality risk in very low birth weight (VLBW) infants in resource limited settings.

Methods The Clinical Risk Index for Babies (CRIB) II score and the simplified age-weight-sex (SAWS) score for all VLBW infants born during the period January 2005 to June 2006 at the University Hospital of the West Indies were retrospectively calculated. The respective ability of each score, birth weight, and calculated or assessed gestational age to predict mortality was quantified using the area under receiver operating curves.

Results Fifty two (48%) males and 57 (52%) females were entered into the study, out of which 58 (53%) infants died. The CRIB II score was found to be a better predictor of mortality (p = 0.02) when compared with calculated gestational age but had similar predictive power when compared with assessed gestational age. The SAWS score was found to have equal predictive value of mortality (p = 0.1) as the CRIB II score, however it was a better predictor of mortality than calculated gestational age (p = 0.002) but had no predictive advantage over assessed gestational age. Birth weight however, proved to be the best predictor of mortality (p < 0.01) with an area under the curve of 0.91 (standard error 0.03; 95% confidence interval 0.85–0.96).

Conclusion In resource poor settings where mortality of VLBW infants is high there may be no benefit in the addition of other variables to birth weight in predicting outcome.