Predicting the Outcome of Sick Neonates Using the Sick Neonate Score: A Prospective Observational Study.

Area of Science:

• Neonatal Medicine
• Pediatric Critical Care
• Clinical Outcomes Research

Background:

• Neonatal transport is crucial for critically ill newborns transitioning to extrauterine life.
• Effective management of extramural neonates admitted to the Neonatal Intensive Care Unit (NICU) is vital.
• The Sick Neonate Score (SNS) is a potential tool for outcome prediction in this population.

Purpose of the Study:

• To evaluate the association between the Sick Neonate Score (SNS) and mortality.
• To assess the predictive accuracy of the SNS for extramural neonates admitted to the NICU.

Main Methods:

• Prospective observational study (November 2019 - October 2021).
• Inclusion of extramural neonates admitted to NICU, excluding those with surgical/congenital anomalies.
• Documentation of demographic data, referral reasons, transport details, and personnel. Assessment of neonate's condition upon arrival using SNS for outcome prediction.

Main Results:

• 422 neonates included; mortality rate was 27.3% (115 deaths).
• Common referral reasons: respiratory distress syndrome (28.2%), hyperbilirubinemia (21.6%), sepsis (19.9%).
• SNS showed high predictive value: sensitivity 91.3%, specificity 82.7%, AUC 0.913. A score ≤7 predicted poorer prognosis.

Conclusions:

• The Sick Neonate Score (SNS) is a simple, user-friendly tool for predicting mortality in extramural neonates.
• The SNS requires minimal technology and expertise, making it accessible for clinical use.
• The SNS demonstrates significant utility in assessing prognosis for critically ill neonates during transport and initial NICU admission.