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. 2021 Feb 24:2021:3165390.
doi: 10.1155/2021/3165390. eCollection 2021.

Massive Blood Transfusion for Trauma Score to Predict Massive Blood Transfusion in Trauma

Osaree Akaraborworn  1 , Boonying Siribumrungwong  2 , Burapat Sangthong  1 , Komet Thongkhao  1
Affiliations

Massive Blood Transfusion for Trauma Score to Predict Massive Blood Transfusion in Trauma

Osaree Akaraborworn et al. Crit Care Res Pract. .

Abstract

Background: Massive blood loss is the most common cause of immediate death in trauma. A massive blood transfusion (MBT) score is a prediction tool to activate blood banks to prepare blood products. The previously published scoring systems were mostly developed from settings that had mature prehospital systems which may lead to a failure to validate in settings with immature prehospital systems. This research aimed to develop a massive blood transfusion for trauma (MBTT) score that is able to predict MBT in settings that have immature prehospital care.

Methods: This study was a retrospective cohort that collected data from trauma patients who met the trauma team activation criteria. The predicting parameters included in the analysis were retrieved from the history, physical examination, and initial laboratory results. The significant parameters from a multivariable analysis were used to develop a clinical scoring system. The discrimination was evaluated by the area under a receiver operating characteristic (AuROC) curve. The calibration was demonstrated with Hosmer-Lemeshow goodness of fit, and an internal validation was done.

Results: Among 867 patients, 102 (11.8%) patients received MBT. Four factors were associated with MBT: a score of 3 for age ≥60 years; 2.5 for base excess ≤-10 mEq/L; 2 for lactate >4 mmol/L; and 1 for heart rate ≥105 /min. The AuROC was 0.85 (95% CI: 0.78-0.91). At the cut point of ≥4, the positive likelihood ratio of the score was 6.72 (95% CI: 4.7-9.6, p < 0.001), the sensitivity was 63.6%, and the specificity was 90.5%. Internal validation with bootstrap replications had an AuROC of 0.83 (95% CI: 0.75-0.91).

Conclusions: The MBTT score has good discrimination to predict MBT with simple and rapidly obtainable parameters.

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Conflict of interest statement

The authors declare that there are no conflicts of interest related to this research.

Figures

Figure 1
Figure 1
Diagram of patient enrollment.
Figure 2
Figure 2
AuROC of the MBT score.
Figure 3
Figure 3
Observed and predicted rates for MBT for each MBT score. Size of the circle represents the population size for each score at the observed rate.
Figure 4
Figure 4
Comparison between the MBTT score and other scoring systems.
See this image and copyright information in PMC

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