Utilizing Machine Learning Algorithms to Evaluate Sex-based Differences in Preoperative Hemoglobin Thresholds in Open Vascular Surgery

Abstract

Preoperative anemia is prevalent in over 40% of vascular surgical patients with sex-specific differences. Several studies have implicated preoperative anemia as a predictor of postoperative cardiac morbidity and all-cause mortality. Given that rescue transfusions are associated with postoperative mortality, morbidity, and prolonged length of stay, there is an urgent need to risk modify these patients in the preoperative setting. The objective of the present study is to assess the impact of sex differences in identifying a safe preoperative hemoglobin threshold.