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14 Prediction of massive blood transfusion in battlefield trauma: development and validation of the military acute severe haemorrhage (MASH) score
  1. Jackie Mclennan1,
  2. Jason Smith1,
  3. Kevin Mackway-jones2
  1. 1Academic Department of Military Emergency Medicine, Royal Centre for Defence Medicine, Birmingham
  2. 2Central Manchester University Hospital NHS Foundation Trust

Abstract

Background The predominant cause of preventable death from trauma is bleeding. Many patients need resuscitation with massive blood transfusion (MBT). In some theatres of military operation there is limited blood product availability and walking donor panels can be required. This study aimed to produce a tool to predict the need for MBT using information available on patient arrival at the ED for patients sustaining battlefield trauma.

Methods A retrospective database analysis was undertaken using the UK Joint Theatre Trauma Registry (JTTR) to provide derivation and validation datasets. Regression analysis of potential predictive factors was performed. MBT was defined either as receiving 6 or more units of red blood cells (RBCs) in 4 hours or 10 units of RBCs in 24 hours. Predictive factors were analysed through multi-logistic regression analysis to build predictive models; sensitivity and specificity of these models was assessed, and the best fit models were analysed in the validation dataset.

Results The derivation dataset was made up of 1298 casualties with a massive blood transfusion rate of 21.2% (n=275). The validation dataset contained 1186; MBT rate 6.7% (n=79). The majority of patients were young, male and with penetrating injury. Univariate regression analyses showing the predictive value of the variables within the MASH score are shown in table 1. A decision rule was produced using a combination of injury pattern, clinical observations and pre-hospital interventions. The test characteristics for three cut off thresholds for the rule are shown in Table 2 alongside the sensitivity analysis. The proposed rule, using a score of 3 or greater, demonstrated a sensitivity of 82.7% and a specificity of 88.8% for prediction of MBT, with an AUROC of 0.93 (95% CI:0.91 to 0.95).

Table 1

Univariate regression analysis of variables included in the MASH score in the derivation dataset which predict the requirement for 6 units of pRBCs in 4 hours or 10 units of pRBCs in 24 hours

Table 2

Performance of the MASH score in derivation and validation datasets showing test characteristics for three values of the MASH score with 95% confidence intervals with sensitivity analysis for a score of 3 in the validation dataset

Conclusions This study has produced the first military scoring system that uses clinical observations, injuries sustained and pre-hospital interventions to predict the need for MBT and therefore the requirement for an emergency donor panel in resource-limited environments. The MASH score has higher sensitivity and specificity than previous military prediction tools, and has the advantage of only using information which is rapidly available in the resuscitation bay. This is of importance to civilian practitioners with increasing possibility of major terrorist attacks.

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