Utilizing Machine Learning to Predict Perioperative Blood Transfusion in Pediatric Craniosynostosis Patients Undergoing Cranial Vault Remodeling
Patients undergoing craniosynostosis repair are at increased risk for transfusion based on age, comorbidities, surgical approach, and ethnicity. These findings highlight the need for early intervention and strategies to reduce transfusion risk in vulnerable populations.
Authors
- Michael Alperovich
- Shaila Ghanekar
- Omar Allam (ORCID: https://orcid.org/0000-0002-7385-7959)
- Aladine A. Elsamadicy (ORCID: https://orcid.org/0000-0002-7658-6461)
- Michael L. DiLuna (ORCID: https://orcid.org/0000-0002-6896-3837)
- Brianna C. Theriault (ORCID: https://orcid.org/0000-0003-3907-3808)
- Paul Serrato (ORCID: https://orcid.org/0000-0003-2550-3221)
- Shashank Rajkumar (ORCID: https://orcid.org/0000-0001-6738-7682)
- Avani DiLuna
Institutions
- Northwell Health (US)
- North Shore University Hospital (US)
- Long Island Jewish Medical Center (US)
- Yale University (US)
Publication Details
- Journal
- Journal of Craniofacial Surgery
- Published
- 2025-10-28
- DOI
- https://doi.org/10.1097/scs.0000000000011828
- Citations
- 1
- Primary Topic
- Craniofacial Disorders and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.82