Purpose: The need for perioperative blood management measures aimed at improving patient outcomes and reducing allogenic blood transfusion (ABT) is increasingly recognised. Our study aim is to create an algorithm to predict and manage the need for blood transfusion in patients with hip fractures.
Methods: We retrospectively assessed 1,484 patients with hip fractures and analysed the probability of receiving an ABT within 72 hours of admission. Univariate, multiple logistic regression analysis and a probability algorithm for predicting the need for blood transfusion on the basis of independent multivariate predictors were used.
Results: Significant predictors for ABT were: older age; lower haemoglobin on admission; female gender; type of surgical implant (cephalomedullary nail and dynamic hip screw more than hemiarthroplasty); and a shorter wait time from admission to surgery. A regression model algorithm correctly predicted the need for an ABT in 73 % of the cases.
Conclusion: An algorithm and a simple clinical tool were devised to predict and manage the need for a blood transfusion within 72 hours of admission in patients with hip fractures.