• Grace Yin, Nada Radulovic, Melissa O'Neill, David Lightfoot, and Brodie Nolan.
• School of Medicine, Faculty of Health Sciences, Queen's University, Kingston, Ontario, Canada.
• Prehosp Emerg Care. 2023 Jan 1; 27 (5): 575585575-585.

AbstractBackground: Hemorrhage is a leading cause of preventable mortality from trauma, necessitating resuscitation through blood product transfusions. Early and accurate identification of patients requiring transfusions in the prehospital setting may reduce delays in time to transfusion upon arrival to hospital, reducing mortality. The purpose of this study is to characterize existing literature on predictors of transfusion and analyze their utility in the prehospital context.Objectives: The objectives of this study are to characterize the existing quantity and quality of literature regarding predictor scores for transfusion in injured patients, and to analyze the utility of predictor scores for massive transfusions in the prehospital setting and identify prehospital predictor scores for future research.Methods: A search strategy was developed in consultation with information specialists. A literature search of OVID MEDLINE from 1946 to the present was conducted for primary studies evaluating the predictive ability of scoring systems or single variables in predicting transfusion in all trauma settings.Results: Of the 5,824 studies identified, 5,784 studies underwent title and abstract screening, 94 studies underwent full text review, and 72 studies were included in the final review. We identified 16 single variables and 52 scoring systems for predicting transfusion. Among single predictor variables, fluids administered and systolic blood pressure had the highest reported sensitivity (100%) and specificity (89%) for massive transfusion protocol (MTP) activation, respectively. Among scoring systems for transfusion, the Shock Index and Modified Shock Index had the highest reported sensitivity (96%), whereas the Pre-arrival Model had the highest reported specificity (95%) for MTP activation. Overall, 20 scores were identified as applicable to the prehospital setting, 25 scores were identified as potentially applicable, and 7 scores were identified as not applicable.Conclusions: We identified an extensive list of predictive single variables, validated scoring systems, and derived models for massive transfusion, presented their properties, and identified those with potential utility in the prehospital setting. By further validating applicable scoring tools in the prehospital setting, we may begin to administer more timely transfusions in the trauma population.

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