{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T04:07:47Z","timestamp":1771042067285,"version":"3.50.1"},"reference-count":28,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T00:00:00Z","timestamp":1760659200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T00:00:00Z","timestamp":1760659200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100007560","name":"Chiesi Farmaceutici","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007560","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Ultrasound Medicine"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Six\u2010region lung ultrasound (LUS) scores show good predictive value for predicting surfactant need in preterm infants but rely on a fixed threshold, which may lead to misclassification near the cut\u2010off and lack data\u2010driven justification for selecting these 6 regions. This study explored whether evaluating individual regions\u2014and combinations\u2014could improve predictive accuracy and utility.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Data from preterm infants born at \u226434\u2009weeks and enrolled in the Serial Lung Ultrasound for Surfactant Replacement Therapy (SLURP) cohort study were analyzed to develop predictive models for surfactant administration based on regional LUS scores. Univariate, bivariate, and machine learning analyses were conducted to identify the most informative lung regions. Rule\u2010based, decision tree, and logistic regression models were then developed, compared to the 6\u2010region model, and validated on an external dataset.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The training set consisted of 77 patients from the SLURP cohort study. The rule\u2010based, decision tree, and logistic regression models showed the best performance, primarily using 2 lung regions\u2014left lateral and left upper posterior. A refined model that included the right upper anterior (RUA) region further improved performance. On the external test set (n\u2009=\u200942), the rule\u2010based model with RUA achieved the highest accuracy (0.93) and the lowest false negative rate (0.11), outperforming the 6\u2010region model. Adding more regions did not enhance accuracy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>A simplified, rule\u2010based model that accounts for the differential predictive value of individual lung regions may enhance the accuracy of LUS\u2010based prediction of surfactant need in preterm infants. It is also more accessible, effective, and time\u2010efficient for clinicians.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jum.70092","type":"journal-article","created":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T11:40:52Z","timestamp":1760701252000},"page":"569-581","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Simplified and Data\u2010Driven Lung Ultrasound Approach for Predicting Surfactant Need in Preterm Infants"],"prefix":"10.1002","volume":"45","author":[{"given":"Virginie","family":"Meau\u2010Petit","sequence":"first","affiliation":[{"name":"Neonatal Unit Franco\u2010Britannique Hospital  Levallois\u2010Perret France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3983-8461","authenticated-orcid":false,"given":"Clemence","family":"Mottez","sequence":"additional","affiliation":[{"name":"Centre of Artificial Intelligence in Medicine 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Kannan","family":"Loganathan","sequence":"additional","affiliation":[{"name":"Neonatal Unit James Cook University Hospital  Middlesbrough UK"},{"name":"Clinical Academic Office, Faculty of Medical Sciences Newcastle University  Newcastle UK"},{"name":"Department of Physics Durham University  Durham 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