Back to all papers

Predictors of extubation success for premature infants.

June 24, 2026pubmed logopapers

Authors

Scarpelli VM,Galanti SG,Jibu IA,Zaytseva A,Kurepa D,Weinberger B

Affiliations (3)

  • Northwell Health, Cohen Children's Medical Center, Division of Neonatology, New Hyde Park, NY, USA.
  • Division of Neonatology, Cincinnati Children's Hospital, Cincinnati, OH, USA.
  • Northwell Health, Cohen Children's Medical Center, Division of Neonatology, New Hyde Park, NY, USA. [email protected].

Abstract

We aimed to determine whether clinical variables predict the success of extubation for premature infants. Using variables preceding 320 extubations of infants ≤30 weeks or ≤1250 g at birth, we built predictive models for success at 1-, 3-, and 7-days using machine learning algorithms. We also determined whether lung ultrasound (LUS) scores (n = 15) were associated with success, or predicted success, of extubation. Of 84 factors considered, nine were associated with success at 1 day, seven at 3 days, and six at 7 days. The accuracies of the predictive models were 78-84%. Median LUS scores were significantly lower preceding successful extubations (at 3 days) but not correlated with the findings of the predictive models. We devised robust models for predicting extubation success based on clinical antecedents. Further study is needed to determine whether LUS can further improve prediction of extubation readiness.

Topics

Journal Article

Ready to Sharpen Your Edge?

Subscribe to join 11k+ peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.

We respect your privacy. Unsubscribe at any time.