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Prospective, Non-blinded, Randomized Controlled Trial on Early Administration of Pulmonary Surfactant Guided by Lung Ultrasound Scores in Very Preterm Infants: Study Protocol

Overview
Journal Front Pediatr
Specialty Pediatrics
Date 2024 Jul 25
PMID 39049843
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Abstract

Background: Bedside lung ultrasonography has been widely used in neonatal intensive care units (NICUs). Lung ultrasound scores (LUS) may predict the need for pulmonary surfactant (PS) application. PS replacement therapy is the key intervention for managing moderate to severe neonatal respiratory distress syndrome (NRDS), with early PS administration playing a positive role in improving patient outcomes. Lung ultrasonography aids in the prompt diagnosis of NRDS, while LUS offers a semi-quantitative assessment of lung health. However, the specific methodologies for utilizing LUS in clinical practice remain controversial. This study hypothesizes that, in very preterm infants [<32 weeks gestational age (GA)] exhibiting respiratory distress symptoms, determining PS application through early postnatal LUS combined with clinical indicators, as opposed to relying solely on clinical signs and chest x-rays, can lead to more timely PS administration, reduce mechanical ventilation duration, improve patient outcomes, and lower the occurrence of bronchopulmonary dysplasia (BPD).

Methods And Design: This is a protocol for a prospective, non-blinded, randomized controlled trial that will be conducted in the NICU of a hospital in China. Eligible participants will include very preterm infants (< 32 weeks GA) exhibiting signs of respiratory distress. Infants will be randomly assigned in a 1:1 ratio to either the ultrasound or control group. In the ultrasonography group, the decision regarding PS administration will be based on a combination of lung ultrasonography and clinical manifestations, whereas in the control group, it will be determined solely by clinical signs and chest x-rays. The primary outcome measure will be the mechanical ventilation duration. Statistical analysis will employ independent sample -tests with a significance level set at α = 0.05 and a power of 80%. The study requires 30 infants per group (in total 60 infants).

Results: This study aims to demonstrate that determining PS application based on a combination of LUS and clinical indicators is superior to traditional approaches.

Conclusions: This approach may enhance the accuracy of NRDS diagnosis and facilitate early prediction of PS requirements, thereby reducing the duration of mechanical ventilation. The findings of this research may contribute valuable insights into the use of LUS to guide PS administration.

Citing Articles

A study of machine learning to predict NRDS severity based on lung ultrasound score and clinical indicators.

Huang C, Ha X, Cui Y, Zhang H Front Med (Lausanne). 2024; 11:1481830.

PMID: 39554502 PMC: 11568467. DOI: 10.3389/fmed.2024.1481830.

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