Accuracy of massive transfusion as a surrogate for significant traumatic bleeding in health administrative datasets

Due to the challenge of identifying need for intervention in bleeding patients, there is a growing interest in prediction modeling. Massive transfusion (MT; 10 or more packed red cells in 24 h) is the most commonly studied dependent variable, serving as a surrogate for severe bleeding and its prediction guides the need for intervention. The critical administration threshold (CAT; 3 packed red cells in 1 h) has been proposed as an alternative. In this study, we aim to compare the classification accuracy of these two surrogates for hemorrhage-related outcomes in health administrative datasets.

We performed a secondary analysis of major trauma patients from the prospectively collected Ottawa Trauma Registry, from September 2014 to September 2017. We conducted a logistic regression analysis utilizing need for hemostasis or hemorrhagic death as dependent variables. We compared classification accuracy in terms of sensitivity, specificity, positive predictive value, negative predictive value and AUC. CAT + and MT + status is not mutually exclusive.

We studied 890 major trauma patients, including 145 CAT + and 48 MT + patients. CAT + demonstrated a superior association for the composite outcome of 24-hour hemorrhage-related mortality and need for hemostasis (AUC 0.815 vs. 0.644, p < 0.0001). This performance was driven by a substantial difference in sensitivity, noted to be 70.0% (95% CI 62.1-77.9%) for CAT + but only 30.0% (95% CI 22.1-37.9%) for MT+. CAT + and MT + demonstrated specificities of 92.9% (95% CI 91.1-94.7%) and 98.9% (98.1-99.6%) respectively.

This study illustrates the concepts of survivorship and competing risk bias for massive transfusion. Utilizing a composite outcome of need for hemostasis and early hemorrhagic death, we demonstrate that CAT + is more accurate for identifying significantly bleeding patients.