Journal
PEDIATRICS
Volume 130, Issue 1, Pages E115-E125Publisher
AMER ACAD PEDIATRICS
DOI: 10.1542/peds.2011-3693
Keywords
logistic models; premature infant; predictive value of tests; prognosis
Categories
Funding
- Eunice Kennedy Shriver National Institute of Child Health and Human Development
- National Institute of Child Health and Human Development
- Department of Health and Human Services [U10 HD21364, U10 HD21373, U10 HD21385, U10 HD21397, U10 HD21415, U10 HD27851, U10 HD27853, U10 HD27856, U10 HD27871, U10 HD27880, U10 HD27881, U10 HD27904, U10 HD34216, U10 HD36790, U10 HD40461, U10 HD40492, U10 HD40498, U10 HD40521, U10 HD40689]
- National Institutes of Health [UL1 RR24139, UL1 RR24160, UL1 RR25008, M01 RR30, M01 RR32, M01 RR39, M01 RR44, M01 RR70, M01 RR80, M01 RR125, M01 RR633, M01 RR750, M01 RR997, M01 RR6022, M01 RR7122, M01 RR8084, M01 RR16587]
- National Institutes of Health (NIH)
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OBJECTIVE: Methods are required to predict prognosis with changes in clinical course. Death or neurodevelopmental impairment in extremely premature neonates can be predicted at birth/admission to the ICU by considering gender, antenatal steroids, multiple birth, birth weight, and gestational age. Predictions may be improved by using additional information available later during the clinical course. Our objective was to develop serial predictions of outcome by using prognostic factors available over the course of NICU hospitalization. METHODS: Data on infants with birth weight <= 1.0 kg admitted to 18 large academic tertiary NICUs during 1998-2005 were used to develop multivariable regression models following stepwise variable selection. Models were developed by using all survivors at specific times during hospitalization (in delivery room [n = 8713], 7-day [n = 6996], 28-day [n = 6241], and 36-week postmenstrual age [n = 5118]) to predict death or death/neurodevelopmental impairment at 18 to 22 months. RESULTS: Prediction of death or neurodevelopmental impairment in extremely premature infants is improved by using information available later during the clinical course. The importance of birth weight declines, whereas the importance of respiratory illness severity increases with advancing postnatal age. The c-statistic in validation models ranged from 0.74 to 0.80 with misclassification rates ranging from 0.28 to 0.30. CONCLUSIONS: Dynamic models of the changing probability of individual outcome can improve outcome predictions in preterm infants. Various current and future scenarios can be modeled by input of different clinical possibilities to develop individual outcome trajectories and evaluate impact of possible morbidities on outcome. Pediatrics 2012;130:e115-e125
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