Sage Journals: Discover world-class research

Abstract

Background

Definitions of massive transfusion following injury help identify patients at the greatest risk of death. However, these definitions primarily use blood component therapy. The use of whole blood (WB) transfusion protocols has seen a resurgence, with evidence of improved outcomes compared to component therapy. Therefore, our aim was to define and stratify patients into low, intermediate, and high risk for death based on volume of blood products transfused utilizing a WB-first resuscitation strategy.

Methods

Patients that received at least 1 unit of whole blood following injury between January 2016 and November 2021 were identified. Receiver operating characteristic (ROC) curves to predict death based on volume of blood products transfused were constructed. Patients were stratified to low, intermediate, and high risk of death based on positive likelihood ratios.

Results

There were 785 patients identified to have received at least 1 unit of WB following injury during the study period. Based on ROC curve analysis, the best predictor of death was volume of whole blood plus packed red blood cells (PRBC) in the first hour (AUC 0.66, P < 0.001). Low risk of mortality was defined as WB + PRBC volume <3400 cc in the first hour (14.9% mortality), intermediate risk 3400-5100 cc in the first hour (39.1% mortality), and high risk >5100 mL in the first hour (66.7% mortality).

Discussion

The combination of WB + PRBC volume within the first hour following injury is the best predictor of death. Further, volumes of WB + PRBC transfused within the first hour can be used to stratify patients’ risk of death.

Level of Evidence

Level IV.

Study Type

Prognostic and Epidemiological.

Keywords

massive transfusion whole blood hemorrhage

Key Takeaways

This is the first study to have identified thresholds that differentiate patients at high, intermediate, and low risk of death based on a whole blood first approach to massive transfusion in trauma.

Volume of whole blood plus packed red blood cells given in the first hour after arrival was most predictive of mortality.

Patients that received greater than 5100 mL of combined product had the highest risk of death within 24 hours and 28 days.

Introduction

One of the most common causes of preventable death following trauma is uncontrolled hemorrhage.^1-3 As such, significant research has focused on mitigating the deleterious effects of trauma-induced coagulopathy (TIC),⁴ while also developing optimal resuscitation strategies to improve mortality and utilize fewer blood products.^5-8 Much of this work has focused on resuscitation strategies using blood components; however, more recent work has evaluated the use of whole blood (WB) as the primary resuscitative blood product. This work has shown a survival benefit compared to component therapy.^9-14 Furthermore, there has been recent work demonstrating an association between earlier WB resuscitation and increased survival in hemorrhagic shock.^15,16

Massive transfusion protocols (MTPs) offer a proven benefit in resuscitation of patients in hemorrhagic shock. Traditional massive transfusion definitions have included the quantity of packed red blood cell (PRBC) units over a span of time to identify patients at greatest risk of death.^17,18 However, these models of massive transfusion take several hours to define. The traditional definition of 10 U PRBC transfused within a 24-hour period is plagued with bias and limitations and is not a clinically relevant surrogate measurement for transfusion needs and early mortality from hemorrhage.^19-22 Incorporating WB into MTP, specifically a higher whole blood ratio, is associated with a decreased probability of mortality in trauma patients.²³ Further, several rapid prediction models have been developed and evaluated to help identify patients at the highest risk of death from hemorrhage, as early as within the first hour.^20,24-26 To date, only a few of these predictive models have stratified patients at variable risk of death based on volumes of blood products transfused, and none of them have utilized WB within their prediction model.^20,24

Most definitions of massive transfusion and predictors of death following hemorrhage have been created using blood components. Currently, there is no accepted definition of massive transfusion incorporating WB as the first or primary resuscitative blood product. As the utilization of WB resuscitation protocols become more common, newer definitions of massive transfusion or risk of death from hemorrhage are needed to help identify and study patients at the greatest risk of death. Utilizing outdated massive transfusion definitions has not considered the rapid evolution and changes in transfusion practices over the past several years with increased use of WB and as a result, what constitutes massive transfusion in patients receiving WB remains undefined. Several models exist that incorporate earlier time intervals with certain transfusion thresholds and quantifying risk of death in support of newer massive transfusion definitions; however, much of this is based on blood component resuscitation. Therefore, our objective is to begin to re-define massive transfusion using a WB-first resuscitation protocol by correlating volumes of product transfused with risk of death.

Methods

This is a retrospective cohort study of a prospectively collected database. Data was collected in consecutive trauma patients that received WB as part of their resuscitation from January 2016 to November 2021 at Atrium Health Wake Forest Baptist Hospital, a tertiary referral center affiliated with Wake Forest School of Medicine. Prior to 2018, our institutional resuscitation practice was component based using a ratio of 1:1:1 (plasma:red blood cells: platelets); however, as plans to transition to a WB-first strategy evolved, patients prior to 2018 occasionally received WB dependent on supply availability. Starting in 2018, our institutional massive transfusion resuscitation protocol was formally transitioned to WB-first where patients >16 years old and females not of childbearing age would receive at least 2 units WB prior to transitioning to component therapy. Our protocol started including women of childbearing age in 2022; however, this was after our data collection period. All whole blood is leukocyte reduced low-titer (1:200) type “O.” Our lab uses a 26-day shelf life, but to prevent waste, whole blood is converted to components on prior to expiration if it remains unused. The average volume of blood components at our institution is as follows: Whole blood is 500 mL, PRBC is 300 mL, plasma is 300 mL, an apheresis pack of platelets is 325 mL, and a 5-unit bag of cryoprecipitate is 90 mL. This study was approved by the institutional review board (IRB) #00058468.

Clinical data was abstracted from the trauma registry and blood bank registry. Demographic and physiologic data collected included age, sex, Glasgow Coma Scale (GCS) on arrival, systolic blood pressure (SBP) in the emergency department, heart rate (HR) in the emergency department, mechanism of injury, traumatic brain injury (TBI), Injury Severity Score (ISS), and volume of blood products administered at 1, 6, and 24 hours from time of arrival. Comparisons between patients with and without severe TBI (sTBI) were also performed.

As there are differences between patients with and without sTBI, ROC curves were constructed for volumes of blood product transfused, considering the presence or absence of sTBI.^10,24,27 Severe TBI was defined as a Head Abbreviated Injury Scale (AIS) greater than or equal to 3. Several models were tested to determine the best predictor of early mortality and were evaluated with and without the presence of sTBI to avoid confounder from death due to traumatic brain injury. Receiver operating characteristic (ROC) curves to predict death based on volume of blood products transfused (within 1, 6, and 24 h from time of arrival) were constructed. Interval likelihood ratios are defined as the slope of the ROC curve between any 2 points on the ROC curve (points A and B)²⁸ and calculated as (Sensitivity of Point A – Sensitivity of Point B)/(Specificity of Point B -Specificity of Point A). The positive likelihood ratio (+LHR) in this setting modifies the pretest probability of death, and a + LHR >1 increases the post-test probability of death, with a greater + LHR increasing the post-test probability.²⁹ We used the +LHR to stratify patients into groups. A high risk of death was defined as the lowest volume of least number of the combination of WB + PRBC volume that corresponded to a + LHR for death of >10x.^24,29 An intermediate zone was defined a + LHR for death of 5x (or as close to 5x as could be obtained). The low-risk group was the cohort receiving fewer WB + PRBC volumes than the intermediate risk group.

IBM SPSS Statistics version 27 (IBM; Armonk, NY) and GraphPad Prism version 10.0.2 (GraphPad Software, Inc; La Jolla, CA) were used for statistical analysis. Data is presented as calculated medians with interquartile ranges. All tests were two-tailed with significance set at P < 0.05. The Mann-Whitney test was used for continuous variables. The Chi-squared test was used for categorical variables.

Results

Between January 2016 and November 2021, 785 patients were identified to have received at least 1 unit of WB following injury. Demographic characteristics are shown in Table 1. Most patients were male with a predominance of blunt traumatic mechanism. The 28-day mortality rate was 30.6%. Mortality in patients that received WB with sTBI was significantly higher than in patients without. A demographic comparison between patients with and without a TBI is also shown in Table 1. There are significant differences in INR, lactate, NISS, and initial GCS between groups (P < 0.05 for all). Total volume of blood products transfused at individual time points is demonstrated in Table 2. Regarding blood products transfused, patients without sTBI received higher volumes of PRBC, plasma, and platelets within the first hour. In hour 6, the only difference between groups was the volume of platelets transfused (P = 0.04). However, the percentage of patients that received more than 1 unit of platelets was not statistically different between patients with and without sTBI. By 24 hours, there was no significant difference in volume transfused for any product between patients with or without sTBI. The previous mentioned transfusion volumes between patients with and without sTBI are shown in Table 2.

Table 1.

Characteristics of all Trauma Patients and Comparison of all Patients With and Without Severe TBI Who Received Whole Blood as Part of Their Resuscitation. SBP = Systolic Blood Pressure; HR = Heart Rate; GCS = Glasgow Coma Scale; TBI = Traumatic Brain Injury; INR = International Normalized Ratio; NISS = New Injury Severity Score; ICU = Intensive Care Unit; LOS = Length of Stay

Demographics	All patients (n = 785)	No severe TBI (n = 687)	Severe TBI (n = 98)	P-value
Age	50 (32-67)	51 (32-66)	44 (31-67)	0.510
Male sex	78.90%	78.20%	83.70%	0.236
Blunt mechanism	75.30%	74.10%	84.70%	0.024
Initial SBP (mmHg)	100 (80-120)	100 (81-120)	101 (80-125)	0.737
Initial HR (bpm)	94 (75-116)	94 (76-115)	98 (70-119)	0.495
Initial GCS	14 (3-15)	15 (4-15)	3 (3-13)	<0.001
Severe TBI	12.50%
Hematocrit (%)	35.2 (22.9-40.3)	35 (21-57)	36 (31-41)	0.048
INR	1.05 (0.96-1.16)	1.05 (0.95-1.15)	1.13 (1.04-1.28)	<0.001
Lactate (mmol/L)	2.7 (1.4-4.7)	2.7 (1.2-4.6)	3.6 (2.2-5.5)	0.001
NISS	27 (17-43)	27 (17-41)	48 (34-66)	<0.001
Ventilatory days	1 (0-3)	0 (0-2)	2 (1-7)	<0.001
ICU LOS (days)	2 (0-6)	2 (0-5)	3 (1-8)	<0.001
Hospital LOS (days)	6 (2-14)	6 (2-13)	6 (1-21)	0.650
30-Day mortality	30.60%	27.2%%	54.10%	<0.0001

Table 2.

Volume of Blood Products Received at Set Time Intervals Among all Patients as Well as Those With and Without a Severe TBI

Volume blood products received
After 1 hour
	All patients (n = 785)	No severe TBI (n = 687)	Severe TBI (n = 98)	P-value
Whole blood (mL)	500 (500-1000)	500 (500-1000)	500 (500-1000)	0.664
PRBC (mL)	0 (0-600)	0 (0-600)	0 (0-0)	0.001
>300 mL plasma	205 (26.1%)	194 (28.2%)	11 (11.2%)	<0.001
>325 mL platelets	64 (8.2%)	64 (9.3%)	0 (0%)	<0.001
>90 mL cryoprecipitate	2 (0.2%)	2 (0.3%)	0 (0%)	>0.999
After 6 hours
Whole blood (mL)	500 (500-1000)	500 (500-1000)	761 (500-1000)	0.292
PRBC (mL)	0 (0-900)	271 (0-900)	0 (0-660)	0.053
>300 mL plasma	290 (36.9%)	260 (37.8%)	30 (30.6%)	0.180
>325 mL platelets	107 (13.6%)	99 (14.4%)	8 (8.1%)	0.114
>90 mL cryoprecipitate	39 (5.0%)	36 (5.2%)	3 (3.1%)	0.388
After 24 hours
Whole blood (mL)	500 (500-1000)	500 (500-1000)	761 (500-1000)	0.427
PRBC (mL)	300 (0-1119)	300 (0-1157)	0 (0-900)	0.145
>300 mL plasma	306 (39.0%)	274 (39.9%)	32 (32.7%)	0.185
>325 mL platelets	107 (13.6%)	99 (14.4%)	8 (8.1%)	0.114
>90 mL cryoprecipitate	53 (6.8%)	49 (7.1%)	4 (4.1%)	0.388

The ability of blood product transfusion volumes to predict mortality was evaluated using ROC curves. Because of differences between patients with and without sTBI, ROC curves were constructed for volumes of blood product transfused, considering the presence or absence of sTBI. Table 3 shows the area under the ROC (AUROC) curve for the ability of blood product volumes to predict 24-hour mortality with and without sTBI. The best predictor of mortality based on AUC at the 24-hour mark was the volume of WB and PRBCs given within the first hour (AUC 0.66, P < 0.001).

Table 3.

Area Under the Receiver Operating Curve (AUROC) for Various Blood Volume Transfusions Within Hours 1, 6, and 24 Evaluating a Primary Outcome of 24-Hour Mortality. Area Under the Curve (AUC) was Determined for Patients With Inclusion and Exclusion of Traumatic Brain Injury (TBI)

Includes severe TBI	AUC	P	Excludes severe TBI	AUC	P
Volume of WB + PRBC in first hour	0.65	<0.001	Volume of WB + PRBC in first hour	0.66	<0.001
Volume of all blood products in first hour	0.64	<0.001	Volume of all blood products in first hour	0.65	<0.001
Volume of WB + PRBC in first 6 hours	0.61	<0.001	Volume of WB + PRBC in first 6 hours	0.64	<0.001
Volume of all blood products in first 6 hours	0.59	0.005	Volume of all blood products in first 6 hours	0.62	<0.001
Volume of WB + PRBC in first 24 hours	0.59	0.005	Volume of WB + PRBC in first 24 hours	0.62	<0.001
Volume of all blood products in first 24 hours	0.58	0.003	Volume of all blood products in first 24 hours	0.61	<0.001

Since excluding patients with severe TBI provided a small improvement of the performance of WB + PRBC volume to predict death, we calculated the intermediate-risk and high-risk (MTx) ranges after excluding this group (Table 4). High risk of death at 24 hours was defined as >5.1 L of WB + PRBC in the first hour. The intermediate risk for death was defined as more than 3.4 L of WB + PRBC in the first hour but less than 5.1 L. The low-risk group was those that received <3.4 L of WB + PRBC. Further, cut points were identified and used as a predictor of 24-hour death to estimate 28-day mortality (Table 4). Following construction of the trichotomized risk of death profiles, 9 patients fell into the high risk of death, 22 patients fell in to the intermediate risk of death, and the remainder of patients were considered low risk. Table 5 shows median volumes of products transfused for patients following stratification into their defined risk categories (low, intermediate, and high risk).

Table 4.

Definition of Low, Intermediate, and High Risk of Death Groups With Positive Likelihood Ratios (Pos LHR) and Mortality, Excluding TBI Patients

	Low risk		Intermediated risk		High risk (massive transfusion)
	Cut-off	Mortality	Cut-off	Pos LHR (Mortality)	Cut-off	Pos LHR (mortality)
24-hour mortality	<3400 mL	14.89%	3400 mL	4.404 (39.13%)	>5100 mL	9.981 (66.66%)
28-day mortality		29.2%		50%		77.80%

Table 5.

Median Volume of Products Transfused Following Stratification of Patients in Low, Intermediate, and High-Risk Categories

Volume blood products received after 1 hour
	Low risk	Intermediate risk	High risk
Whole blood + PRBC (mL)	500 (500-1374)	3710 (3400-4095	6945 (5678-7848)
Plasma (mL)	0 (0-325)	2554 (2510-3000)	4671 (3966-5411)
Platelets (mL)	0 (0-0)	626 (574-649)	1189 (856-1351)
Cryoprecipitate (mL)	0 (0-0)	0 (0-0)	0 (0-0)

Discussion

In this study, patients were stratified based on volume of WB and PRBC transfused at different time intervals to identify patients at high, intermediate, and low risk of death. These thresholds provide the ability to identify patients at greatest risk of death within the first hour of presentation in order to help define MTP utilizing an upfront WB resuscitation protocol. Further analysis of these thresholds was used to determine 28-day mortality (Table 4). Massive transfusion following traumatic injury carries a high mortality rate and has been demonstrated within the literature from 60 to 80%.^24,26 Previous work has largely evaluated the use of individual component therapy in defining massive transfusion. Incorporating a patient’s risk of death based on volume of product transfused can help further quantify what the meaning of massive transfusion is with whole blood resuscitation strategies. The identification of such thresholds has shown utility in predicting risk of death and may be utilized as tools to help inform care decisions, guide goals of care discussions, as well as provide a definition for future research endeavors.

Goal-directed therapy and ratio-based transfusion protocols have led to improvements in patient outcomes following trauma.^5,7,8,18 These have primarily focused on transfusion or resuscitation protocols based on individual blood component therapy. However, there has been a resurgence in the use of WB over the last several years that first began with utilization of WB during the conflicts in Iraq and Afghanistan.^30-33 Further, there are several differences in the military vs civilian application of WB, primarily the fact that the military use of WB may consist of fresh warm WB from a “walking blood bank” compared to cold-stored WB in the civilian sector.^33,34 Recently, several civilian trauma centers have evaluated outcomes in patients who received WB instead of strict blood component therapy with positive outcomes.^9-16,23

Prior to recent studies illustrating the benefits of WB, massive transfusion was primarily goal-directed or ratio-based.^5-8,18 Using blood components, several models have been developed for early prediction and quantifying risk of death from hemorrhage.^20,24-26 These models have effectively replaced historic massive transfusion definitions, as these historic definitions take several hours to define and are often plagued with bias.^5,16,19-22 In 2008, the Denver group re-defined massive transfusion as >10 units of PRBC or death within the first 6 hours.¹⁸ This definition removed the limitation of survivor bias.¹⁸ Other, more recent, studies have evaluated risk of death over a shorter time. Nunns et al stratified risk of death from hemorrhage into low, intermediate, and high risk (massive transfusion) based on one-hour PRBC transfusion requirements.²⁴ They found a transfusion of >4 units of PRBC within the first hour was associated with a high need for concomitant platelet and cryoprecipitate transfusion as well as a 51% mortality.²⁴ Redefining MTP within the one-hour time frame with the use of WB may prove beneficial for resource allocation and identifying patients earlier who are at a high risk of death.

Two other models have been developed to identify patients at risk of death following injury, the Resuscitation Intensity (RI) and Critical Administration Threshold (CAT). The RI was defined as total products in the first 30 minutes (PRBC, plasma, and crystalloid) while the CAT score was positive if the patient received a ≥3 U RBC during any one-hour period in the first 24 hours arrival.^25,26 Both RI and CAT are more applicable than traditional definitions of massive transfusion at predicting risk for early mortality.²⁵ The limitation of all these models is that they define risk of death using blood components therapy only and were not developed using WB resuscitation protocols. Resuscitation strategies have rapidly evolved with utilization of WB and even these newer prediction models may be outdated as they do not consider WB in their definition. Further, a recent evaluation of massive transfusion in patients that received WB defined a WB massive transfusion score as a predictor of poor outcomes.³¹ To our knowledge, our model, which identifies low, intermediate, and high risk of mortality, is the first to stratify risk of death using transfused WB volumes.

Several models were tested to determine the best predictor of early mortality (Table 3). Further, these models were evaluated with and without the presence of sTBI, given that patients with sTBI had a significantly higher risk of mortality but also received less blood products (Table 1). Removal of TBI from the model allowed for a small improvement in the performance with an AUROC to 0.66. AUROC curves were also developed for total volumes of all blood products, including platelets, plasma, and cryoprecipitate. However, the performance of volume of WB + PRBC was more predictive of mortality compared with other components. We were able to define patients at the lowest risk of death as those that received less than 3.4 L of WB + PRBC within the first hour. The patients with high risk of death were those that received more than 5.1 L of WB + PRBC.

The retrospective nature of this study is a limitation, and as such, data is only as accurate as the trauma registry and blood bank collection. Prospective analysis is needed to validate our definitions to a larger population. Transfusion practices across institutions differ, and these definitions may not apply to facilities without access to a WB-first approach. Similarly, while some emergency medical services began to have the capability of providing pre-hospital blood products, we were unable to collect this data to include in this study but it remains an area of future study. Unfortunately, changes in the blood bank collection software have prevented us from accessing blood product utilization data prior to 2016. Similarly, as the blood bank collection software transitioned as well as migration of our medical system, this has led challenges in acquiring and capturing data from more recent patients. During the study period, transfusion practices also began to evolve at our institution, whereas women of childbearing age were initially excluded from receiving WB, in 2022, our resuscitation practice included this patient population; however, this was after our data collection period. This may introduce the possibility of selection bias within our study population. Within the study population, all patients receiving WB were included, which introduces a risk of survivorship bias. Furthermore, the AUC for predicting death was only 0.66 and this is far from an excellent predictor of mortality. However, as the use of WB becomes more common, it is an important starting point for further research on MTP in the WB era.

In conclusion, this is the first study to have identified thresholds that differentiate patients at high, intermediate, and low risk of death based on a WB-first approach to MTP. These thresholds provide the ability to identify patients at greatest risk of death within the first hour of presentation and further define what massive transfusion means in the WB era of resuscitation. Further research is needed to validate these thresholds over a broad range of facilities that implement a WB-based resuscitation protocol for injured patients.

Footnotes

ORCID iDs

Jeff Conner

Andrew M. Nunn

Author Contributions

Literature search: JC, AMN, and GRS

Study design: JC, AMN, HC, CG, MAM, NM, JH, and GRS

Data collection: AMN and GRS

Data analysis: JC, AMN, and GRS

Data interpretation: JC, AMN, and GRS

Writing: JC, AMN, and GRS

Critical revision: JC, AMN, MA, HC, CG, MAM, NM, JH, and GRS.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

Eastridge

Hardin

Cantrell

, et al. Died of wounds on the battlefield: causation and implications for improving combat casualty care. J Trauma. 2011;71(1 Suppl):S4-S8. doi:10.1097/TA.0b013e318221147b

Kashuk

Moore

Sawyer

, et al. Postinjury coagulopathy management: goal directed resuscitation via POC thrombelastography. Ann Surg. 2010;251(4):604-614. doi:10.1097/SLA.0b013e3181d3599c

Tisherman

Schmicker

Brasel

, et al. Detailed description of all deaths in both the shock and traumatic brain injury hypertonic saline trials of the resuscitation outcomes consortium. Ann Surg. 2015;261(3):586-590. doi:10.1097/SLA.0000000000000837

Brohi

Singh

Heron

Coats

. Acute traumatic coagulopathy. J Trauma. 2003;54(6):1127-1130. doi:10.1097/01.TA.0000069184.82147.06

Cotton

Reddy

Hatch

, et al. Damage control resuscitation is associated with a reduction in resuscitation volumes and improvement in survival in 390 damage control laparotomy patients. Ann Surg. 2011;254(4):598-605. doi:10.1097/SLA.0b013e318230089e

Gonzalez

Moore

, et al. Goal-directed hemostatic resuscitation of trauma-induced coagulopathy: a pragmatic randomized clinical trial comparing a viscoelastic assay to conventional coagulation assays. Ann Surg. 2016;263(6):1051-1059. doi:10.1097/SLA.0000000000001608

Holcomb

del Junco

Fox

, et al. The prospective, observational, multicenter, major trauma transfusion (PROMMTT) study: comparative effectiveness of a time-varying treatment with competing risks. JAMA Surg. 2013;148(2):127-136. doi:10.1001/2013.jamasurg.387

Holcomb

Tilley

Baraniuk

, et al. Transfusion of plasma, platelets, and red blood cells in a 1:1:1 vs a 1:1:2 ratio and mortality in patients with severe trauma: the PROPPR randomized clinical trial. JAMA. 2015;313(5):471-482. doi:10.1001/jama.2015.12

Brill

Mueck

Tang

, et al.

Is low-titer group O whole blood truly a universal blood product?

J Am Coll Surg. 2023;236(3):506-513. doi:10.1097/XCS.0000000000000489

10.

Brill

Tang

Hatton

, et al. Impact of incorporating whole blood into hemorrhagic shock resuscitation: analysis of 1,377 consecutive trauma patients receiving emergency-release uncrossmatched blood products. J Am Coll Surg. 2022;234(4):408-418. doi:10.1097/XCS.0000000000000086

11.

Hatton

Brill

Tang

, et al. Patients with both traumatic brain injury and hemorrhagic shock benefit from resuscitation with whole blood. J Trauma Acute Care Surg. 2023;95:918-924. doi:10.1097/TA.0000000000004110

12.

McCoy

Brenner

Duchesne

, et al. Back to the future: whole blood resuscitation of the severely injured trauma patient. Shock. 2021;56(1S):9-15. doi:10.1097/SHK.0000000000001685

13.

Sperry

Cotton

Luther

, et al. Whole blood resuscitation and association with survival in injured patients with an elevated probability of mortality. J Am Coll Surg. 2023;237(2):206-219. doi:10.1097/XCS.0000000000000708

14.

Williams

Merutka

Meyer

, et al. Safety profile and impact of low-titer group O whole blood for emergency use in trauma. J Trauma Acute Care Surg. 2020;88(1):87-93. doi:10.1097/TA.0000000000002498

15.

Lammers

Rokayak

, et al. Preferential whole blood transfusion during the early resuscitation period is associated with decreased mortality and transfusion requirements in traumatically injured patients. Trauma Surg Acute Care Open. 2024;9(1):e001358. doi:10.1136/tsaco-2023-001358

16.

Torres

Kenzik

Saillant

, et al. Timing to first whole blood transfusion and survival following severe hemorrhage in trauma patients. JAMA Surg. 2024;159(4):374-381. doi:10.1001/jamasurg.2023.7178

17.

Cotton

Dossett

Haut

, et al. Multicenter validation of a simplified score to predict massive transfusion in trauma. J Trauma. 2010;69(Suppl 1):S33-S39. doi:10.1097/TA.0b013e3181e42411

18.

Kashuk

Moore

Johnson

, et al.

Postinjury life threatening coagulopathy: is 1:1 fresh frozen plasma:packed red blood cells the answer?

J Trauma. 2008;65(2):261-270. doi:10.1097/TA.0b013e31817de3e1

19.

Massive transfusion in surgery and trauma . Proceedings of the XIVth annual scientific symposium of the American red cross. Washington, DC, may 6-7, 1982. Prog Clin Biol Res. 1982;108:1-319.

20.

Meyer

Cotton

Fox

, et al. A comparison of resuscitation intensity and critical administration threshold in predicting early mortality among bleeding patients: a multicenter validation in 680 major transfusion patients. J Trauma Acute Care Surg. 2018;85(4):691-696. doi:10.1097/TA.0000000000002020

21.

Ulin

Gollub

Winchell

Ehrlich

. Hemorrhage and massive transfusion. J Am Med Assoc. 1958;168(15):1971-1973. doi:10.1001/jama.1958.03000150013003

22.

Wilson

Mammen

Walt

. Eight years of experience with massive blood transfusions. J Trauma. 1971;11(4):275-285. doi:10.1097/00005373-197104000-00001

23.

Aoki

Abe

Komori

Katsura

Matsushima

. Association between whole blood ratio and risk of mortality in massively transfused trauma patients: retrospective cohort study. Crit Care. 2024;28(1):253. doi:10.1186/s13054-024-05041-8

24.

Nunns

Moore

Stettler

, et al. Empiric transfusion strategies during life-threatening hemorrhage. Surgery. 2018;164(2):306-311. doi:10.1016/j.surg.2018.02.024

25.

Rahbar

Fox

del Junco

, et al. Early resuscitation intensity as a surrogate for bleeding severity and early mortality in the PROMMTT study. J Trauma Acute Care Surg. 2013;75(1 Suppl 1):S16-S23. doi:10.1097/TA.0b013e31828fa535

26.

Savage

Zarzaur

Croce

Fabian

. Redefining massive transfusion when every second counts. J Trauma Acute Care Surg. 2013;74(2):396-400. doi:10.1097/TA.0b013e31827a3639

27.

Cotton

Podbielski

Camp

, et al. A randomized controlled pilot trial of modified whole blood versus component therapy in severely injured patients requiring large volume transfusions. Ann Surg. 2013;258(4):527-532. doi:10.1097/SLA.0b013e3182a4ffa0

28.

Brown

Reeves

. Evidence-based emergency medicine/skills for evidence-based emergency care. Interval likelihood ratios: another advantage for the evidence-based diagnostician. Ann Emerg Med. 2003;42(2):292-297. doi:10.1067/mem.2003.274

29.

Ray

Le Manach

Riou

Houle

. Statistical evaluation of a biomarker. Anesthesiology. 2010;112(4):1023-1040. doi:10.1097/ALN.0b013e3181d47604

30.

Beckett

Callum

da Luz

, et al. Fresh whole blood transfusion capability for special operations forces. Can J Surg. 2015;58(3 Suppl 3):S153-S156. doi:10.1503/cjs.012614

31.

Uhlich

Black

Jansen

Kerby

Holcomb

. A new definition for massive transfusion in the modern era of whole blood resuscitation. Transfusion. 2021;61:S252-S263.

32.

Shackelford

Gurney

Taylor

, et al. Joint trauma system, defense committee on trauma, and armed services blood program consensus statement on whole blood. Transfusion. 2021;61(Suppl 1):S333-S335. doi:10.1111/trf.16454

33.

Naumann

Boulton

Sandhu

, et al. Fresh whole blood from walking blood banks for patients with traumatic hemorrhagic shock: a systematic review and meta-analysis. J Trauma Acute Care Surg. 2020;89(4):792-800. doi:10.1097/TA.0000000000002840

34.

Fisher

Miles

Broussard

, et al. Low titer group O whole blood resuscitation: military experience from the point of injury. J Trauma Acute Care Surg. 2020;89(4):834-841. doi:10.1097/TA.0000000000002863

Stratifying Early Risk of Death From Hemorrhage in the Era of Whole Blood

Abstract

Background

Methods

Results

Discussion

Level of Evidence

Study Type

Keywords

Key Takeaways

Introduction

Methods

Results

Discussion

Footnotes

ORCID iDs

Author Contributions

Funding

Declaration of Conflicting Interests

References