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Developing a Multivariable Prediction Model to Identify a High-Volume Patent Ductus Arteriosus in Neonates Born

Amy A Hobson1, Daniel Dagle1, Craig G Rusin2

  • 1Division of Neonatology, Department of Pediatrics, University of Iowa, Iowa City, IA.

The Journal of Pediatrics
|December 24, 2025
PubMed
Summary

A new clinical model accurately predicts high-volume patent ductus arteriosus (PDA) in premature infants using logistic regression. This tool aids in identifying significant PDA shunts in neonates.

Keywords:
neonatal hemodynamicsshunt volumetargeted neonatal echocardiography

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Area of Science:

  • Neonatal Medicine
  • Pediatric Cardiology
  • Medical Informatics

Background:

  • Patent ductus arteriosus (PDA) is common in premature infants.
  • Hemodynamically significant PDA (hsPDA) requires timely diagnosis and management.
  • Accurate prediction of hsPDA volume is crucial for clinical decision-making.

Purpose of the Study:

  • To develop a predictive clinical model for high-volume, hemodynamically significant PDA in premature infants.
  • To utilize vital sign data and arterial blood pressure waveform analysis for PDA prediction.
  • To improve diagnostic accuracy for hsPDA in neonatal intensive care units.

Main Methods:

  • Retrospective cohort analysis of infants < 27 weeks gestational age.
  • Utilized targeted neonatal echocardiography (TNE) and modified Iowa PDA score.
  • Employed logistic regression modeling with vital sign data and Fourier-transformed arterial blood pressure waveforms.

Main Results:

  • The model achieved a high accuracy with a mean testing area under the curve of 0.8891.
  • Mean airway pressure was significantly higher in the high-volume PDA shunt group.
  • The model successfully classified 5-minute windows as high-volume PDA or no/low-volume shunt.

Conclusions:

  • Logistic regression modeling can accurately identify high-volume PDA shunts.
  • The developed model shows promise for clinical application in neonates.
  • Future research should explore moderate-volume shunts and clinical outcome correlations.