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Predicting Admission to Neonatal Care Unit at Mid-Pregnancy and Delivery Using Data from a General Obstetric
Gillian M Maher1,2, Joye McKernan3, Laura O'Byrne4,5
1INFANT Research Centre, University College Cork, Cork, Ireland. gillian.maher@ucc.ie.
Maternal and Child Health Journal
|October 17, 2024
Summary
This study developed risk prediction models to identify infants needing neonatal care unit admission. The models, based on mid-pregnancy and delivery factors, offer personalized risk assessments for expectant parents.
Area of Science:
- Maternal-fetal medicine
- Neonatal care
- Biostatistics
Background:
- Neonatal care unit (NICU) admission is a significant concern for expectant parents.
- Accurate prediction of NICU admission risk is crucial for informed decision-making and resource allocation.
Purpose of the Study:
- To develop and validate risk prediction models for neonatal care unit admission.
- To create nomograms for estimating individualized NICU admission risk at mid-pregnancy and delivery.
Main Methods:
- Utilized data from singleton deliveries at Cork University Maternity Hospital (2019-2020).
- Employed multivariable logistic regression with backward stepwise selection.
- Assessed model discrimination using ROC curve C-statistic and validated internally via bootstrapping.
Main Results:
- Identified six mid-pregnancy predictors (e.g., male infant, maternal smoking) and seven delivery predictors (e.g., gestational age < 39 weeks).
- Mid-pregnancy model C-statistic: 0.600; delivery model C-statistic: 0.738.
- Developed nomograms demonstrating good internal performance and external reproducibility.
Conclusions:
- The developed nomograms provide a practical tool for estimating individual NICU admission risk.
- Further research is needed to enhance early pregnancy prediction accuracy for improved parental counseling.
