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Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Neonatal Multimorbidity is a Poor Predictor of Health and Developmental Outcomes after Preterm Birth
Jonathan S Litt1, Mandy B Belfort2, Erika M Edwards3
1Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA.
Insights
Neonatal multimorbidity is common in extremely low birth weight infants, but current models have modest predictive ability for 24-month outcomes. Further research is needed to improve prognostic accuracy for this vulnerable population.
Area of Science:
- Neonatalogy
- Pediatric Outcomes Research
- Biostatistics
Background:
- Extremely low birth weight (ELBW) infants face significant health challenges.
- Neonatal morbidities are common in ELBW infants and impact long-term development.
- Predictive models are crucial for identifying high-risk ELBW infants.
Purpose of the Study:
- To evaluate and compare the predictive capabilities of three multimorbidity-based models.
- To assess the prediction of early childhood outcomes in infants born with ELBW.
- To identify the most effective model for predicting developmental delay, rehospitalization, and therapeutic service use.
Main Methods:
- Analysis of 8332 surviving ELBW infants from the Vermont Oxford Network (2010-2020).
- Inclusion of neonatal morbidities such as bronchopulmonary dysplasia, intraventricular hemorrhage, and necrotizing enterocolitis.
- Comparison of three gestational age-adjusted risk models: morbidity count, specific morbidity count, and latent classes.
Main Results:
- Thirty-five percent of ELBW infants experienced two or more neonatal morbidities.
- Morbidity counts and latent classes were associated with increased risk for adverse 24-month outcomes.
- All three models demonstrated modest predictive ability (AUC = 0.66).
Conclusions:
- Neonatal multimorbidity is prevalent in ELBW infants and linked to later outcomes.
- Current diagnosis-based multimorbidity risk models have limited prognostic value.
- Improved characterization of multimorbidity is essential for enhancing clinical utility.
Objective:
To test and compare the capability of 3 multimorbidity-based models to predict outcomes in early childhood among infants born with extremely low birth weight (<1000 g, ELBW).
Study Design:
Participants included 8332 surviving ELBW infants born 2010-2020 in North America who contributed follow-up data at 24-months corrected age to the Vermont Oxford Network. Neonatal morbidities included bronchopulmonary dysplasia, grade 3-4 intraventricular hemorrhage, periventricular leukomalacia, stage 3-4 retinopathy of prematurity, late infection, necrotizing enterocolitis, and spontaneous intestinal perforation. Outcomes included: 1) developmental delay (Bayley score <70 in ≥1 domain), 2) rehospitalization, and 3) therapeutic service use. We compared 3 gestational age-adjusted risk models with the following predictors: 1) morbidity count, 2) count of 3 morbidities (bronchopulmonary dysplasia, intraventricular hemorrhage, and retinopathy of prematurity), and 3) multimorbidity-based latent classes.
Results:
Thirty five percent of the study sample had ≥2 neonatal morbidities. Most (64%) received ≥2 therapeutic services, 36% were re-hospitalized, and 19% had developmental delay at 24-months. Morbidity counts and multimorbidity-based latent classes were associated with increased risk for poor 24-month outcomes compared with no morbidity. However, the predictive ability of all 3 models was modest (area under the receiver operating curve = 0.66).
Conclusions:
Neonatal multimorbidity is common among ELBW infants and associated with later health and developmental outcomes. However, diagnosis-based multimorbidity risk models have poor prognostic ability. More robust characterization of multimorbidity symptom severity, physiologic impact, and environmental correlates may improve the clinical utility of future risk models.
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