Abstract: Objective: There is growing evidence for the usefulness of the lung ultrasound score (LUS) in neonatal intensive care. We evaluated whether the LUS is predictive of outcomes in infants with respiratory distress syndrome (RDS).
Study Design: Neonates less than 34 weeks of gestational age were eligible for this prospective, multicenter cohort study. The outcomes of interest were the need for mechanical ventilation (MV) at <72 hours of life, the need for surfactant (SF), successful weaning from continuous positive airway pressure (CPAP), extubation readiness, and bronchopulmonary dysplasia. Lung scans were taken at 0 to 6 hours of life (Day 1), on Days 2, 3, and 7, and before CPAP withdrawal or extubation. Sonograms were scored (range 0-16) by a blinded expert sonographer. The area under the receiver operating characteristic curve (AUC) was used to estimate the prediction accuracy of the LUS.
Results: A total of 647 scans were obtained from 155 newborns with a median gestational age of 32 weeks. On Day 1, a cutoff LUS of 6 had a sensitivity (Se) of 88% and a specificity (Sp) of 79% to predict the need for SF (AUC = 0.86), while a cutoff LUS of 7 predicted the need for MV at <72 hours of life (Se = 89%, Sp = 65%, AUC = 0.80). LUS acquired prior to weaning off CPAP was an excellent predictor of successful CPAP withdrawal, with a cutoff level of 1 (Se = 67%, Sp = 100%, AUC = 0.86).
Conclusion: The LUS has significant predictive ability for important outcomes in neonatal RDS.
Key Points: · Lung ultrasound has significant prognostic abilities in neonatal RDS.. · Early sonograms (0-6 h of life) accurately predict the requirement for SF and ventilation.. · Weaning off CPAP is effective when the LUS (range 0-16) is less than or equal to 1..
Competing Interests: P.S., M.S., W.B., I.S-K., P.K., and R.B. received honoraria from Chiesi Poland for lecturing and participation on advisory boards. R.H. is employed by Chiesi Poland, the sponsor of the study. The remaining authors report no conflict of interest.
(The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)
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