Ultrasound performed shortly after birth can predict the respiratory support needs of late preterm and term infants: A diagnostic accuracy study. Issue 7 (12th April 2021)

• Record Type: Journal Article
• Authors: Xi, Guannan; Dai, Jiale; Wang, Xuefeng; Luo, Fei; Lu, Chengqiu; Yang, Yun; Wang, Jimei
• Is Part Of: Pediatric pulmonology. Volume 56:Issue 7(2021)
• Page Start: 2155
• Page End: 2163
• Publication Date: 2021-04-12
• Subjects: lung ultrasound -- predictive value -- respiratory support -- ROC; Pediatric respiratory diseases -- Periodicals; Pediatrics -- Periodicals; 618.922
• DOI: 10.1002/ppul.25389
• Languages: English
• ISSNs: 8755-6863

Abstract

Abstract: 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. Research Highlights: Six image patterns can be found in the results of just‐birth infants lung ultrasound (LUS) screening, including four "low‐risk" patterns and two "high‐risk" patterns The number of scanning areas with "high‐risk" patterns has a great predictive value for respiratory support (AUC = 0.95, optimal cut‐off value is 2 with a sensitivity of 87.8% and specificity of 91.1%). The predictive value of LUS is greater than that of assessment method based on respiratory symptoms (e.g., Acute Care of at‐Risk Newborns assessment score).