Data on the application of early coagulation support protocol in the management of major trauma patients

This article provides additional data on the application of early coagulation support protocol in the management of major trauma patients. Data come from a retrospective analysis reported in the article “Early coagulation support protocol: a valid approach in real-life management of major trauma patients. Results from two Italian centres” [1]. Data contain information about the relationship between differences in resource use and mortality outcomes, and patient demographic and clinical features at presentation. Furthermore, a comparison between resource consumption, the probability of multiple transfusions and the mortality outcomes among propensity-score matched patients is reported.


Data
Among the 518 patients admitted into the participating centres due to major trauma (overall cohort), 235, who had, or were at risk of, active bleeding, matched one of the inclusion criteria (study Specifications Table   Subject Critical Care and Intensive Care Medicine Specific subject area Haemostasis/coagulopathy Type of data Tables  Graph  How data were acquired Data were retrospectively acquired from the registry data of the emergency department of two Italian trauma centres. Data format Raw and analysed Parameters for data collection Overall cohort: patients who were consecutively admitted with major trauma who had, or were at risk of, active bleeding, managed according to the massive transfusion (2011 e2012) or the early coagulation protocol (2013e2014). Study cohort: patients who, according to international guidelines, was considered at risk of requiring multiple transfusions. Description of data collection Data from all major trauma patients with ISS >15 who were admitted to the ICU were included into Trauma Centre's databases (overall cohort). Data from patients who met the inclusion criteria were included into the multicentre database (study cohort). These data were matched with blood bank registries and the amounts of packed red blood cells, fresh frozen plasma, and platelet units administered within 24-h after admission were recorded. Value of the Data These data, alongside with those reported in the related research article, show that the application of the ECS protocol guarantees early coagulation support in major trauma patients with high bleeding risk. Basing on these data, ECS protocol may be adopted by clinicians in real-life management of major trauma patients. These data can be used to design further prospective studies with the aim to standardize timing and dosing of fibrinogen in the application of ECS protocol in major trauma patients. The present data give more strength to the results of the related research article confirming a reduction in the average blood product consumption associated with the application of ECS protocol. cohort) and were enrolled in the study [1]. The stratified analysis is re-ported in Table 1 and Table 2, raw data are re-ported in Sup-plementary ma-terial (Table S1).  unit stay (LOS-ICU) was recorded. A significant reduction in the LOS-ICU was also observed in older (>65 years) and in more severe patients (!3 inclusion criteria) treated with ECS protocol. Table 2 shows no statistically differences in 28-day mortality between pre-ECS and ECS groups. The 24-h mortality rate was higher in patients with severe traumatic brain injury (AIS head ! 4; RR ¼ 1.64) than in patients without traumatic brain injury (RR ¼ 0.98). Patients disposition and baseline characteristics of propensity-score matched patients are reported in Fig. 1 and Table 3. The propensity-score matched analysis is reported in Table 4 and shows a significantly lower use of pRBC, FFP, PLTs in patients treated with ECS protocol. Furthermore, in the ECS group were recorded a significant increase in LOS-ICU, and a decrease in LOS-hospital and mortality at day-zero. Raw data are reported in Supplementary material (Table S2).

Experimental design, materials, and methods
Data of adult major trauma patients with, or at risk of, active bleeding, who were managed according to the massive transfusion protocol e MTP (years 2011e2012) or the ECS protocol (2013e2014) and were considered at risk of multiple transfusions, were retrospective collected with the aim to determine blood product consumption, length of stay, and in-hospital mortality.
A stratified analysis was performed in order to investigate whether differences in resource use and mortality between ECS and pre-ECS were related to patient demographic and clinical features at presentation, including age (18e40, 40e64, !65 years), severity of traumatic brain injury (head AIS <4 vs. ! 4), and major trauma severity (according to inclusion criteria). Stratified analyses were performed including a study period patients' feature interaction in separated Poisson models and by formally testing the null hypothesis of equal efficacy of the ECS protocol among categories of patients through an F test.
We defined "multiple transfused patients" as those experiencing four or more pRBC units during the first 24-h. The cut-off of four pRBC units represented the sample 75th percentile. We estimated the mean difference in transfused units and length of stay between ECS and pre-ECS from unadjusted Poisson models, using the delta methods to estimate the 95% CI for the mean difference. Findings were reinforced by replacing the Poisson model with a negative binomial distribution. In addition, we investigated the association between clinical features and the probability of multiple transfusion by means of univariate and multivariate logistic regression models. Table 4 Mean difference in resources absorption and relative risk of in-hospital mortality for propensity-score matched cohort between the ECS and the pre-ECS study periods.  To further control for any residual difference in clinical features between pre-ECS and ECS, we compared resource consumption, the probability of multiple transfusions and the mortality outcomes among propensity-score matched patients. The propensity score included the following variables: age, sex, ISS, AIS head, abnormal systolic blood pressure, blood base excess, lactate, haemoglobin, and platelets at hospital admission. The propensity score matching was performed using a standard macro.
All statistical analyses were performed using SAS 9.4 (SAS Institute, Cary NC).