Neonatal Multimorbidity is a Poor Predictor of Health and Developmental Outcomes after Preterm Birth

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.