Decision-making in pediatric blunt solid organ injury: A deep learning approach to predict massive transfusion, need for operative management, and mortality risk.
Journal:
Journal of pediatric surgery
PMID:
33218680
Abstract
BACKGROUND: The principal triggers for intervention in the setting of pediatric blunt solid organ injury (BSOI) are declining hemoglobin values and hemodynamic instability. The clinical management of BSOI is, however, complex. We therefore hypothesized that state-of-art machine learning (computer-based) algorithms could be leveraged to discover new combinations of clinical variables that might herald the need for an escalation in care. We developed algorithms to predict the need for massive transfusion (MT), failure of non-operative management (NOM), mortality, and successful non-operative management without intervention, all within 4 hours of emergency department (ED) presentation.