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

Alexandre Tran; Marie-Joe Nemnom; Jacinthe Lampron; Maher Matar; Christian Vaillancourt; Monica Taljaard

doi:10.1016/j.injury.2018.11.014

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

Injury. 2019 Feb;50(2):318-323. doi: 10.1016/j.injury.2018.11.014. Epub 2018 Nov 10.

Authors

Alexandre Tran¹, Marie-Joe Nemnom², Jacinthe Lampron³, Maher Matar⁴, Christian Vaillancourt⁵, Monica Taljaard⁶

Affiliations

¹ Department of Surgery, University of Ottawa, Ottawa, ON, Canada; Clinical Epidemiology Program, The Ottawa Hospital Research Institute, Ottawa, ON, Canada. Electronic address: aletran@toh.ca.
² Clinical Epidemiology Program, The Ottawa Hospital Research Institute, Ottawa, ON, Canada. Electronic address: mnemnom@ohri.ca.
³ Department of Surgery, University of Ottawa, Ottawa, ON, Canada. Electronic address: jlampron@toh.ca.
⁴ Department of Surgery, University of Ottawa, Ottawa, ON, Canada. Electronic address: mmatar@toh.ca.
⁵ Clinical Epidemiology Program, The Ottawa Hospital Research Institute, Ottawa, ON, Canada; Department of Emergency Medicine, University of Ottawa, Ottawa, ON, Canada. Electronic address: cvaillancourt@ohri.ca.
⁶ Clinical Epidemiology Program, The Ottawa Hospital Research Institute, Ottawa, ON, Canada; School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada. Electronic address: mtaljaard@ohri.ca.

PMID: 30448330
DOI: 10.1016/j.injury.2018.11.014

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Keywords: Critical administration threshold; Prediction modeling; Surrogate; Traumatic bleeding.

MeSH terms

Adult
Blood Transfusion* / statistics & numerical data
Clinical Protocols
Female
Hemorrhage / mortality
Hemorrhage / therapy*
Hemostasis
Hospital Mortality
Humans
Injury Severity Score
Male
Middle Aged
Registries / statistics & numerical data*
Shock, Hemorrhagic / mortality
Shock, Hemorrhagic / therapy*
Survival Rate
Time Factors
Treatment Outcome
Wounds and Injuries / complications
Wounds and Injuries / mortality
Wounds and Injuries / therapy*