Prediction of pre-hospital blood transfusion in trauma patients based on scoring systems

BACKGROUND

Pre-hospital blood transfusion (PHBT) is a safe and gradually expanding procedure applied to trauma patients. A proper decision to activate PHBT with the presently limited diagnostic options at the site of an incident poses a challenge for pre-hospital crews. The purpose of this study was to compare the selected scoring systems and to determine whether they can be used as valid tools in identifying patients with PHBT requirements.

METHODS

A retrospective single-center study was conducted between June 2018 and December 2020. Overall, 385 patients (aged [median; IQR]: 44; 24-60; 73% males) were included in this study. The values of five selected scoring systems were calculated in all patients. To determine the accuracy of each score for the prediction of PHBT, the Receiver Operating Characteristic (ROC) analysis was used and to measure the association, the odds ratio with 95% confidence intervals was counted (Fig. 1).

RESULTS

Regarding the proper indication of PHBT, shock index (SI) and pulse pressure (PP) revealed the highest value of AUC and sensitivity/specificity ratio (SI: AUC 0.88; 95% CI 0.82-0.93; PP: AUC 0.85 with 95% CI 0.79-0.91).

CONCLUSION

Shock index and pulse pressure are suitable tools for predicting PHBT in trauma patients.

A Simple Cardiovascular Model for the Study of Hemorrhagic Shock

Hemorrhagic shock is the number one cause of death on the battlefield and in civilian trauma as well. Mathematical modeling has been applied in this context for decades; however, the formulation of a satisfactory model that is both practical and effective has yet to be achieved. This paper introduces an upgraded version of the 2007 Zenker model for hemorrhagic shock termed the ZenCur model that allows for a better description of the time course of relevant observations. Our study provides a simple but realistic mathematical description of cardiovascular dynamics that may be useful in the assessment and prognosis of hemorrhagic shock. This model is capable of replicating the changes in mean arterial pressure, heart rate, and cardiac output after the onset of bleeding (as observed in four experimental laboratory animals) and achieves a reasonable compromise between an overly detailed depiction of relevant mechanisms, on the one hand, and model simplicity, on the other. The former would require considerable simulations and entail burdensome interpretations. From a clinical standpoint, the goals of the new model are to predict survival and optimize the timing of therapy, in both civilian and military scenarios.

Fractures of the femur and blood transfusions

BACKGROUND

Blood loss estimation after trauma (i.e. physical injury) and early identification of potential sources of bleeding are important for planning of investigation and management of trauma. Long bone fractures have been reported to be associated with substantial volumes of blood loss requiring blood transfusion. The aim of this study was to assess rates and amounts of blood transfusion in the setting of isolated extra capsular femur fractures and to determine variables associated with the need for transfusion within the first 48 h of admission.

METHODS

A retrospective cohort study was conducted of patients in The Alfred Trauma Registry with isolated extra capsular femur fractures over a 7-year period. We compared patients with a femoral shaft fracture (FSF) to patients with either distal femur or proximal femur fractures (i.e. extremity fracture). We collected data potentially associated with blood transfusion within 48 h as well as operation details and patient outcomes.

RESULTS

There were 293 patients included, of which 121 had FSF and 172 extremity fracture. 105 (36%) patients received a blood transfusion during their admission. Admission haemoglobin (AOR 0.92; 95%CI 0.89-0.94, p < 0.01) was the only independently associated variable with blood transfusion within the first 48 h of hospital admission.

CONCLUSION

Volume of blood transfused to patients with extra-capsular femoral fractures was low and usually in the post-operative period. FSF, compared to femoral extremity fractures, were not more likely to receive blood transfusion within the first 48 h of admission, and did not receive a higher volume of blood overall. In the setting of major trauma with haemorrhagic shock, alternate sources of bleeding should be sought.

Prehospital identification of trauma patients requiring transfusion: results of a retrospective study evaluating the use of the trauma induced coagulopathy clinical score (TICCS) in 33,385 patients from the TraumaRegister DGU®

BACKGROUND

Identifying trauma patients that need emergent blood product transfusion is crucial. The Trauma Induced Coagulopathy Clinical Score (TICCS) is an easy-to-measure score developed to meet this medical need. We hypothesized that TICCS would assist in identifying patients that need a transfusion in a large cohort of severe trauma patients from the TraumaRegister DGU^® (TR-DGU).

MATERIALS AND METHODS

A total of 33,385 severe trauma patients were extracted from the TR-DGU for retrospective analysis. The TICCS was adapted for the registry structure. Blood transfusion was defined as the use of at least one unit of red blood cells (RBC) during acute hospital treatment.

RESULTS

With an area under the receiving operating curve (AUC) of 0.700 (95% CI: 0.691-0.709), the TICCS appeared to be moderately discriminant for determining the need for RBC transfusion in the trauma population of the TR-DGU. A TICCS cut-off value of ≥12 yielded the best trade-off between true positives and false positives. The corresponding positive predictive value and negative predictive values were 48.4% and 89.1%, respectively.

CONCLUSION

This retrospective study confirms that the TICCS is a useful and simple score for discriminating between trauma patients with and without the need for emergent blood product transfusion.

Prediction of Massive Transfusion in Trauma Patients with Shock Index, Modified Shock Index, and Age Shock Index

Objectives: The shock index (SI) and its derivations, the modified shock index (MSI) and the age shock index (Age SI), have been used to identify trauma patients with unstable hemodynamic status. The aim of this study was to evaluate their use in predicting the requirement for massive transfusion (MT) in trauma patients upon arrival at the hospital. Participants: A patient receiving transfusion of 10 or more units of packed red blood cells or whole blood within 24 h of arrival at the emergency department was defined as having received MT. Detailed data of 2490 patients hospitalized for trauma between 1 January 2009, and 31 December 2014, who had received blood transfusion within 24 h of arrival at the emergency department, were retrieved from the Trauma Registry System of a level I regional trauma center. These included 99 patients who received MT and 2391 patients who did not. Patients with incomplete registration data were excluded from the study. The two-sided Fisher exact test or Pearson chi-square test were used to compare categorical data. The unpaired Student t-test was used to analyze normally distributed continuous data, and the Mann-Whitney U-test was used to compare non-normally distributed data. Parameters including systolic blood pressure (SBP), heart rate (HR), hemoglobin level (Hb), base deficit (BD), SI, MSI, and Age SI that could provide cut-off points for predicting the patients’ probability of receiving MT were identified by the development of specific receiver operating characteristic (ROC) curves. High accuracy was defined as an area under the curve (AUC) of more than 0.9, moderate accuracy was defined as an AUC between 0.9 and 0.7, and low accuracy was defined as an AUC less than 0.7. Results: In addition to a significantly higher Injury Severity Score (ISS) and worse outcome, the patients requiring MT presented with a significantly higher HR and lower SBP, Hb, and BD, as well as significantly increased SI, MSI, and Age SI. Among these, only four parameters (SBP, BD, SI, and MSI) had a discriminating power of moderate accuracy (AUC > 0.7) as would be expected. A SI of 0.95 and a MSI of 1.15 were identified as the cut-off points for predicting the requirement of MT, with an AUC of 0.760 (sensitivity: 0.563 and specificity: 0.876) and 0.756 (sensitivity: 0.615 and specificity: 0.823), respectively. However, in the groups of patients with comorbidities such as hypertension, diabetes mellitus, or coronary artery disease, the discriminating power of these three indices in predicting the requirement of MT was compromised. Conclusions: This study reveals that the SI is moderately accurate in predicting the need for MT. However, this predictive power may be compromised in patients with HTN, DM or CAD. Moreover, the more complex calculations of MSI and Age SI failed to provide better discriminating power than the SI.