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ID07216053

Using Early Lung Ultrasound to Predict Breathing Problems in Late Preterm Babies Born Between 34 and 36 Weeks

Led by Hackensack Meridian Health · Updated on 2026-05-22

300

Participants Needed

1

Research Sites

N/A

Total Duration

AI-Summary

What this Trial Is About

Respiratory problems are a major challenge for newborns, especially late-preterm infants born between 34 and 36 weeks gestation. These infants face risks similar to more premature babies but may not always be born in hospitals with specialized neonatal care. This research aims to evaluate the usefulness of early point-of-care lung ultrasound LUS in predicting respiratory difficulties within the first 48 hours of life in these late-preterm newborns. It also compares the accuracy of three different lung ultrasound scoring systems to see which best predicts respiratory problems. In this observational study, babies born late-preterm who are initially breathing room air or receiving low-flow oxygen through a nasal cannula will receive a lung ultrasound within their first 4 hours of life. The ultrasound images will be scored using three established scoring methods. The babies will be monitored during their hospital stay to watch for any signs of respiratory distress or need for increased respiratory support during the first 48 hours after birth. Participants will be followed closely in the neonatal intensive care unit or well-baby nursery to track the onset and severity of breathing difficulties, including how soon respiratory support is needed and how long it is required. Researchers will use these observations to assess how well the lung ultrasound scores predict respiratory worsening. The study will also look at the need for invasive respiratory support and the timing of respiratory distress signs. The trial will continue through the initial hospital stay, aiming to improve early identification of at-risk late-preterm infants.

CONDITIONS

Brief Title

Predictive Value of Lung Ultrasound for Respiratory Decompensation in Late Preterm Neonates

Research Team

J

Jeanette Haugh

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