SINGAPORE—External validation of a novel surgical transfusion risk prediction model has concluded that the machine learning model—dubbed S-PATH—has excellent external validity and discrimination across diverse healthcare institutions.
The study found that when it comes to identifying patients who need preoperative blood typing and antibody screening, the S-PATH approach was consistently more efficient than the conventional maximum surgical blood ordering schedule (MSBOS)