{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T13:07:37Z","timestamp":1793884057921,"version":"4.7.0"},"reference-count":41,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2021,4,12]],"date-time":"2021-04-12T00:00:00Z","timestamp":1618185600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pediatric Pulmonology"],"published-print":{"date-parts":[[2021,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We conducted a prospective diagnostic accuracy study following the Standards for the Reporting of Diagnostic Accuracy Studies\u00a0guidelines 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\u2009h 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Seventy\u2010four infants needed respiratory support, and 236 were healthy according to a 3\u2010day follow\u2010up confirmation. Six LUS imaging patterns were found. Two \u201chigh\u2010risk\u201d patterns were strongly correlated with respiratory support needs (area under the curve [AUC]\u2009=\u20090.95; 95% confidence interval [CI]: 0.92\u20130.98, <jats:italic>p<\/jats:italic>\u2009&lt;\u2009.001). The optimal cut\u2010off value for \u201chigh\u2010risk\u201d patterns was 2 (sensitivity\u2009=\u200987.8% and specificity\u2009=\u200991.1%). The predictive value of LUS was greater than that of a symptom\u2010based method (the Acute Care of at\u2010Risk Newborns assessment score) (AUCs' <jats:italic>p<\/jats:italic>\u2009&lt;\u2009.01).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec>","DOI":"10.1002\/ppul.25389","type":"journal-article","created":{"date-parts":[[2021,3,26]],"date-time":"2021-03-26T07:05:10Z","timestamp":1616742310000},"page":"2155-2163","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Ultrasound performed shortly after birth can predict the respiratory support needs of late preterm and term infants: A diagnostic accuracy study"],"prefix":"10.1002","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6888-5613","authenticated-orcid":false,"given":"Guannan","family":"Xi","sequence":"first","affiliation":[{"name":"Department of Neonatology Obstetrics and Gynecology Hospital of Fudan University  Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiale","family":"Dai","sequence":"additional","affiliation":[{"name":"Department of Neonatology Obstetrics and Gynecology Hospital of Fudan University  Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuefeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Neonatology Obstetrics and Gynecology Hospital of Fudan University  Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fei","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Neonatology Obstetrics and Gynecology Hospital of Fudan University  Shanghai 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