Outcome prediction in newborn infants: Past, present, and future

Area of Science:

• Neonatal intensive care and outcome prediction.
• Clinical informatics and data-driven healthcare.

Background:

• Perinatal and neonatal periods are critical for organ development.
• Neonatal illnesses lead to significant mortality, morbidity, and healthcare burdens.
• Accurate outcome prediction is vital for managing intensive care and informing families.

Purpose of the Study:

• To review published neonatal outcome risk prediction research from the Neonatal Research Network (NRN).
• To assess the current clinical utility of NRN-developed prediction tools.
• To explore future directions for advanced, individualized risk prediction in neonates.

Main Methods:

• Utilized comprehensive hospital and neurodevelopmental follow-up outcome data from NRN research databases.
• Focused on infants receiving intensive care for various diseases and conditions.
• Reviewed NRN's development of data-driven outcome risk prediction tools.

Main Results:

• The NRN has successfully developed and published outcome risk prediction tools.
• These tools facilitate data-driven, transparent discussions for family-centered communication and clinical management.
• Existing tools demonstrate clinical utility in managing neonatal intensive care outcomes.

Conclusions:

• NRN's risk prediction tools enhance clinical decision-making and family communication.
• Continued research is needed for advanced, individualized risk prediction models.
• These advancements aim to improve prognoses and post-discharge interventions for neonates.