<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>25(1)</volume><submitter>Wagenaar JHL</submitter><pubmed_abstract>&lt;h4>Purpose&lt;/h4>To address capacity problems at tertiary-level neonatal intensive care units (NICUs) within current staffing limitations, our study aims to demonstrate the feasibility of identifying very preterm neonates not in need of highly specialised, tertiary-level, NICU care.&lt;h4>Methods&lt;/h4>We developed and internally validated a clinical prediction model to identify very preterm neonates in need of tertiary-level NICU care within the first 72 h after birth in the Netherlands. The outcome was defined as one or more of: 1) endotracheal surfactant administration, 2) endotracheal/mechanical ventilation, and 3) inotropic administration. Multivariable logistic regression, with a priori selected predictors, was used on a retrospective cohort of very preterm neonates admitted to the tertiary-level NICU of Erasmus MC Sophia Children's Hospital, between January 2018 and December 2022. Bootstrapping was used for internal validation.&lt;h4>Results&lt;/h4>Of 654 included neonates, 45.1% (n = 295) needed tertiary-level NICU care. The final model included six predictors. Evaluating the model's discriminative performance resulted in an area under the receiver operating characteristics (ROC) curve of 0.77 [95%CI: 0.73-0.80]. A low-risk classification threshold of 20% yielded high sensitivity (93% [95%CI 90-96%]) and a specificity of 26% [95%CI: 22-31%], predicting a low risk of needing tertiary-level NICU care for 114 neonates, accurately selecting 94 of them.&lt;h4>Conclusion&lt;/h4>This prediction model demonstrates the feasibility of perinatal identification of very preterm neonates not in need of tertiary-level NICU care. Future research should focus on updating the model to a source population of women with imminent preterm birth.</pubmed_abstract><journal>BMC pediatrics</journal><pagination>956</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12649062</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Development and internal validation of a clinical prediction model for the needed level of care in preterm neonates.</pubmed_title><pmcid>PMC12649062</pmcid><pubmed_authors>Kleinsmann MS</pubmed_authors><pubmed_authors>Reiss IKM</pubmed_authors><pubmed_authors>Wagenaar JHL</pubmed_authors><pubmed_authors>Franx A</pubmed_authors><pubmed_authors>Taal HR</pubmed_authors><pubmed_authors>Broekhoven M</pubmed_authors></additional><is_claimable>false</is_claimable><name>Development and internal validation of a clinical prediction model for the needed level of care in preterm neonates.</name><description>&lt;h4>Purpose&lt;/h4>To address capacity problems at tertiary-level neonatal intensive care units (NICUs) within current staffing limitations, our study aims to demonstrate the feasibility of identifying very preterm neonates not in need of highly specialised, tertiary-level, NICU care.&lt;h4>Methods&lt;/h4>We developed and internally validated a clinical prediction model to identify very preterm neonates in need of tertiary-level NICU care within the first 72 h after birth in the Netherlands. The outcome was defined as one or more of: 1) endotracheal surfactant administration, 2) endotracheal/mechanical ventilation, and 3) inotropic administration. Multivariable logistic regression, with a priori selected predictors, was used on a retrospective cohort of very preterm neonates admitted to the tertiary-level NICU of Erasmus MC Sophia Children's Hospital, between January 2018 and December 2022. Bootstrapping was used for internal validation.&lt;h4>Results&lt;/h4>Of 654 included neonates, 45.1% (n = 295) needed tertiary-level NICU care. The final model included six predictors. Evaluating the model's discriminative performance resulted in an area under the receiver operating characteristics (ROC) curve of 0.77 [95%CI: 0.73-0.80]. A low-risk classification threshold of 20% yielded high sensitivity (93% [95%CI 90-96%]) and a specificity of 26% [95%CI: 22-31%], predicting a low risk of needing tertiary-level NICU care for 114 neonates, accurately selecting 94 of them.&lt;h4>Conclusion&lt;/h4>This prediction model demonstrates the feasibility of perinatal identification of very preterm neonates not in need of tertiary-level NICU care. Future research should focus on updating the model to a source population of women with imminent preterm birth.</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Nov</publication><modification>2026-06-05T17:56:31.923Z</modification><creation>2026-05-19T03:12:06.7Z</creation></dates><accession>S-EPMC12649062</accession><cross_references><pubmed>41291564</pubmed><doi>10.1186/s12887-025-06316-x</doi></cross_references></HashMap>