Predicting Mortality in Very Premature Infants
Author Information
Author(s): Stephanie Medlock, Anita C. J. Ravelli, Pieter Tamminga, Ben W. M. Mol, Ameen Abu-Hanna
Primary Institution: Academic Medical Center, University of Amsterdam
Hypothesis
The review aims to assess the quality of prediction models for mortality in very premature infants and identify important predictor variables.
Conclusion
Multivariate models can predict mortality better than birth weight or gestational age alone in very preterm infants.
Supporting Evidence
- 41 development studies and 18 validation studies were identified.
- Eight variables frequently predicted survival: average size for gestational age, female gender, non-white ethnicity, absence of serious congenital malformations, use of antenatal steroids, higher 5-minute Apgar score, normal temperature on admission, and better respiratory status.
- Twelve studies met methodological quality criteria, with three externally validated.
Takeaway
Doctors can use special models to better guess if very tiny babies will survive, instead of just looking at their weight and age.
Methodology
The review included studies that reported predictive performance of models for mortality in very preterm or very low birth weight populations.
Potential Biases
Potential biases due to the subjective nature of some input variables and treatment decisions affecting outcomes.
Limitations
The studies included were heterogeneous in population and mortality rate, and many had low reporting scores.
Participant Demographics
The studies included populations from 21 countries, with infants born at less than 32 weeks gestational age or less than 1500 g birth weight.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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