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Ultrasound performed shortly after birth can predict the respiratory support needs of late preterm and term infants: A diagnostic accuracy study
Author(s) -
Xi Guannan,
Dai Jiale,
Wang Xuefeng,
Luo Fei,
Lu Chengqiu,
Yang Yun,
Wang Jimei
Publication year - 2021
Publication title -
pediatric pulmonology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.866
H-Index - 106
eISSN - 1099-0496
pISSN - 8755-6863
DOI - 10.1002/ppul.25389
Subject(s) - medicine , lung ultrasound , confidence interval , receiver operating characteristic , respiratory system , pediatrics , predictive value , predictive value of tests , prospective cohort study , respiratory disease , lung
Background Late preterm and term infants may develop respiratory issues with severe outcomes. Early identification of these diseases shortly after infants' birth can improve their management. Lung ultrasound (LUS) has been used to diagnose neonatal respiratory diseases. However, few LUS methods have been reported to predict the need for respiratory support, the basis of infant respiratory diseases management. Methods We conducted a prospective diagnostic accuracy study following the Standards for the Reporting of Diagnostic Accuracy Studies guidelines at a tertiary academic hospital between 2019 and 2020. A total of 310 late preterm and term infants with mild respiratory symptoms were enrolled. The LUS assessment was performed for each participant at one of the following times: 0.5, 1.0, 2.0, or 4.0 h after birth. Predictive reliability was tested by receiver operating characteristic curve analysis. The main outcome was the need for any respiratory support determined according to international guidelines. Results Seventy‐four infants needed respiratory support, and 236 were healthy according to a 3‐day follow‐up confirmation. Six LUS imaging patterns were found. Two “high‐risk” patterns were strongly correlated with respiratory support needs (area under the curve [AUC] = 0.95; 95% confidence interval [CI]: 0.92–0.98, p < .001). The optimal cut‐off value for “high‐risk” patterns was 2 (sensitivity = 87.8% and specificity = 91.1%). The predictive value of LUS was greater than that of a symptom‐based method (the Acute Care of at‐Risk Newborns assessment score) (AUCs' p < .01). Conclusions LUS can be used to predict the need for respiratory support in late preterm and term infants and is more reliable than tools based on respiratory symptoms.