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Updated: Jul 25, 2026

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Equations to support predictive automated postnatal growth curves for premature infants
W R Riddle1, S C DonLevy, X F Qi
1Department of Radiology and Radiological Sciences, Medical Center North, Vanderbilt University Medical Center, Nashville, TN 37232-2675, USA. bill.riddle@vanderbilt.edu
Insights
This study provides essential growth chart equations for premature infants, crucial for monitoring health in neonatal intensive care units. These tools aid in tracking infant development and identifying potential health issues early.
Area of Science:
- Neonatal Medicine
- Pediatric Health
- Growth Monitoring
Background:
- Growth charts are vital in pediatrics for assessing infant health and nutritional status.
- Established reference data exists for term infants, but not for premature infants in Neonatal Intensive Care Units (NICUs).
- Current predictive methods for preterm infants are difficult to implement with traditional tools.
Purpose of the Study:
- To address the lack of established growth data for premature infants.
- To develop practical tools for monitoring preterm infant growth.
- To present mathematical equations for predicting key growth parameters in preterm infants.
Main Methods:
- Review of published perinatal growth curves.
- Derivation of mathematical equations for growth prediction.
- Focus on postnatal weight, head circumference, and length.
Main Results:
- Equations for predicting postnatal weight in preterm infants.
- Equations for predicting head circumference in preterm infants.
- Equations for predicting length in preterm infants.
Conclusions:
- The derived equations provide a foundation for creating electronic preterm growth charts.
- These tools can improve the monitoring of health and development in NICU populations.
- Facilitates better assessment of nutritional and general health status for premature infants.
Abstract:
Growth charts are used in pediatric medicine to plot anthropomorphic measurements over time, serving as a screen for diseases related to a patient's nutritional and general health status. Whereas reference data for term infants are available from the Center for Disease Control, reference data for premature infants in a neonatal intensive care unit have not been established. Predictive curves for preterm patients, which are based on a patient's postmenstrual age and anthropomorphic measurements at birth, cannot be easily implemented with traditional paper-based methods. Preterm growth charts can be generated in an electronic health record system, but doing so requires mathematical equations or computer-readable tables. This report examines published perinatal growth curves and presents equations for predicted postnatal weight, head circumference and length in preterm infants.
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