Assessment Of Blood Consumption Score Research Articles

Outcomes of patients enrolled in a prospective and randomized trial on basis of gestalt assessment or ABC score.

The Pragmatic Randomized Optimal Platelet and Plasma Ratios (PROPPR) trial rapidly enrolled patients based on an Assessment of Blood Consumption (ABC) ≥ 2 score, or physician gestalt (PG) when ABC score was <2. The objective of this study was to describe what patients were enrolled by the two methods and whether patient outcomes differed based on these enrollments. We hypothesized that there would be no differences in outcomes based on whether patients were enrolled via ABC score or PG. Patients were enrolled with an ABC ≥ 2 or by PG when ABC was <2 by the attending trauma surgeon. We compared 1-hour, 3-hour, 6-hour, 12-hour, 18-hour, and 24-hour mortality, 30-day mortality, time to hemostasis, emergent surgical or interventional radiology procedure and the proportion of patients who required either >10 units of blood in 24 hours or >3 units in 1 hour. Of 680 patients, 438 (64%) were enrolled on the basis of an ABC score ≥2 and 242 (36% by PG when the ABC score was <2). Patients enrolled by PG were older (median, 44; interquartile range [IQR], 28-59; p < 0.001), more likely to be White (70.3% vs. 60.3%, p = 0.014), and more likely to have been injured by blunt mechanisms (77.3% vs. 37.2%, p < 0.001). They were also less hypotensive and less tachycardic than patients enrolled by ABC score (both p < 0.001). The groups had similar Injury Severity Scores in the ABC ≥ 2 and PG groups (26 and 27, respectively) and were equally represented (49.1% and 50.8%, respectively) in the 1:1:1 treatment arm. There were no significant differences between the ABC score and PG groups for mortality at any point. Time to hemostasis (108 for patients enrolled on basis of Gestalt, vs. 100 minutes for patients enrolled on basis of ABC score), and the proportion of patients requiring a massive transfusion (>10 units/24 hours) (44.2% vs. 47.3%), or meeting the critical administration threshold (>3 unit/1 hour) (84.7% vs. 89.5%) were similar ( p = 0.071). Early identification of trauma patients likely to require a massive transfusion is important for clinical care, resource use, and selection of patients for clinical trials. Patients enrolled in the PROPPR trial based on PG when the ABC score was <2 represented 36% of the patients and had identical outcomes to those enrolled on the basis of an ABC score of ≥2. Prognostic and Epidemiological; Level III.

Abstract 373: Traumatic Bleeding Severity Score: An External Validation Study for the Predictive Accuracy of the Need for Massive Transfusion

Background: The Traumatic Bleeding Severity Score (TBSS) was developed to predict the need for massive transfusion (MT). The aim of this study was to conduct the first external validation study about the TBSS in Japan, and to compare its prediction value to other pre-existing MT prediction scores. Methods: A multicenter retrospective observational study was conducted in Japan (Japanese observational study for coagulation and Thrombolysis in Early Trauma 2 : J-OCTET 2). Twenty-five tertiary critical care centers in Japan participated in this study, and severe trauma patients (Injury Severity Score : ISS ≥ 16) admitted from 2018 to 2019 were enrolled. At the analysis of the TBSS external validation, patients with isolated head injuries were excluded from the analysis. In this study, MT was defined as 10 units or more of red blood cells transfusion within 24 hours from injuries. The TBSS on admission was retrospectively calculated and its accuracy in predicting MT was analyzed by the area under the receiver operating characteristic curve (AUROC). To compare the predictive value between the TBSS and the pre-existing scores, the Trauma Associated Severe Hemorrhage score (TASH score) and the Assessment of Blood Consumption score (ABC score) on admission was similarly calculated, and the ROC comparison analysis was performed. Results: Totally, 1202 severely injured trauma patients were enrolled in the J-OCTET 2 study, and 889 patients were analyzed after the matching of the exclusion criteria. The median age was 66 years (IQR: 47-77), 71.4 % was male, 97.9% was blunt trauma, median ISS was 22 (IQR:16-29), and 13.8% received MT. The AUROC of the TBSS for was 0.848 (95% CI:0.81-0.88). According to the ROC comparison, the AUROC of the TASH score was 0.848 (95% CI: 0.81-0.88) and there was no significant difference between both prediction scores. (Bonferroni adjusted p=1.00). The AUROC of the ABC score was 0.751(95% CI: 0.70-0.80), which was significantly lower to TBSS’s (Bonferroni adjusted p&lt;0.01). Conclusion: This TBSS external validation study showed that the accuracy of TBSS in the MT prediction was moderate accuracy. The predictive value of the TBSS was comparable to that of the TASH score and superior to the ABC score.

Early Prediction of Massive Transfusion for Patients With Traumatic Hemorrhage: Development of a Multivariable Machine Learning Model.

Develop a novel machine learning (ML) model to rapidly identify trauma patients with severe hemorrhage at risk of early mortality. The critical administration threshold (CAT, 3 or more units of red blood cells in a 60-minute period) indicates severe hemorrhage and predicts mortality, whereas early identification of such patients improves survival. Patients from the PRospective, Observational, Multicenter, Major Trauma Transfusion and Pragmatic, Randomized Optimal Platelet, and Plasma Ratio studies were identified as either CAT+ or CAT-. Candidate variables were separated into 4 tiers based on the anticipated time of availability during the patient's assessment. ML models were created with the stepwise addition of variables and compared with the baseline performance of the assessment of blood consumption (ABC) score for CAT+ prediction using a cross-validated training set and a hold-out validation test set. Of 1245 PRospective, Observational, Multicenter, Major Trauma Transfusion and 680 Pragmatic, Randomized Optimal Platelet and Plasma Ratio study patients, 1312 were included in this analysis, including 862 CAT+ and 450 CAT-. A CatBoost gradient-boosted decision tree model performed best. Using only variables available prehospital or on initial assessment (Tier 1), the ML model performed superior to the ABC score in predicting CAT+ patients [area under the receiver-operator curve (AUC = 0.71 vs 0.62)]. Model discrimination increased with the addition of Tier 2 (AUC = 0.75), Tier 3 (AUC = 0.77), and Tier 4 (AUC = 0.81) variables. A dynamic ML model reliably identified CAT+ trauma patients with data available within minutes of trauma center arrival, and the quality of the prediction improved as more patient-level data became available. Such an approach can optimize the accuracy and timeliness of massive transfusion protocol activation.

Assessment of Machine Learning Methods to Predict Massive Blood Transfusion in Trauma

BackgroundAccurately predicting which patients are most likely to benefit from massive transfusion protocol (MTP) activation may help patients while saving blood products and limiting cost. The purpose of this study is to explore the use of modern machine learning (ML) methods to develop and validate a model that can accurately predict the need for massive blood transfusion (MBT).MethodsThe institutional trauma registry was used to identify all trauma team activation cases between June 2015 and August 2019. We used an ML framework to explore multiple ML methods including logistic regression with forward and backward selection, logistic regression with lasso and ridge regularization, support vector machines (SVM), decision tree, random forest, naive Bayes, XGBoost, AdaBoost, and neural networks. Each model was then assessed using sensitivity, specificity, positive predictive value, and negative predictive value. Model performance was compared to that of existing scores including the Assessment of Blood Consumption (ABC) and the Revised Assessment of Bleeding and Transfusion (RABT).ResultsA total of 2438 patients were included in the study, with 4.9% receiving MBT. All models besides decision tree and SVM attained an area under the curve (AUC) of above 0.75 (range: 0.75–0.83). Most of the ML models have higher sensitivity (0.55–0.83) than the ABC and RABT score (0.36 and 0.55, respectively) while maintaining comparable specificity (0.75–0.81; ABC 0.80 and RABT 0.83).ConclusionsOur ML models performed better than existing scores. Implementing an ML model in mobile computing devices or electronic health record has the potential to improve the usability.

Air Medical Blood Transfusion as a Trigger of Massive Transfusion Protocol

Air medical services can improve access to blood products at the point of injury. Studies have shown that early activation of mass transfusion protocols (MTPs) can improve the survival of trauma patients by up to 25%. There are several scoring systems to guide early activation, but the use of a single criterion has been elusive. Our study sought to determine if air medical administration of blood products was a risk factor for massive transfusion activation and utilization of prehospital vital signs for calculation of the shock index. In our retrospective study, we evaluated adult trauma patients transfused by helicopter emergency medical services (HEMS) and as a control all patients in our institution receiving the MTP. Our study found HEMS blood transfusion was not a reliable trigger for MTP, although the sample size may have limited our findings. We found that HEMS care resulted in an overall reduction in the volume of transfusion and an improvement in hemodynamic parameters upon trauma center arrival. HEMS transfusion and a higher rate of tranexamic acid administration may have contributed to these findings. Of note, the assessment of blood consumption score and shock index were nonspecific in the study populations.

Prehospital Validation of the Assessment of Blood Consumption (ABC) Score

Introduction The Assessment of Blood Consumption (ABC) score is a previously validated scoring system designed to predict which severely injured trauma patients will require massive transfusion. When the ABC score is used in the prehospital setting to activate massive transfusion at the receiving hospital, a 23% decrease in mortality has been demonstrated. However, the ABC score was developed and validated using hospital data from the emergency department (ED). The sensitivity and specificity of the ABC score when calculated using data from the prehospital setting are unknown. We hypothesized that the sensitivity and specificity of the prehospital ABC score will be similar to the sensitivity and specificity of the ED ABC score. Methods A 5-year retrospective analysis (2015–2019) of highest-activation adult trauma patients arriving to a quaternary Level I trauma center by hospital-based helicopter air medical service (HEMS) was performed. Demographic, prehospital, ED triage, and blood product utilization data were collected. Prehospital ABC score was calculated using the highest heart rate, lowest systolic blood pressure, and focused assessment with sonography for trauma (FAST) exam results obtained prior to arrival at the trauma center. ED ABC score was calculated using ED triage vital signs and ED FAST results. Sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristics (AUROC) curve were calculated for each ABC score. Results 2,067 patients met inclusion criteria. Mean age 39 (±17) years, 76% male, 22% penetrating mechanism. Of these, 128 patients (6%) received massive transfusion using the definition from the original study. Prehospital ABC score at a cutoff of 2 was 51% sensitive and 85% specific for predicting massive transfusion, with 83% correctly classified and an AUROC = 0.73. ED ABC score at the same cutoff was 60% sensitive and 84% specific, with 83% correctly classified and an AUROC = 0.81. By logistic regression, the odds of massive transfusion increased by 2.76 for every 1-point increase in prehospital ABC score (95%CI 2.25–3.37, p < 0.001). Conclusions The ABC score is a useful prehospital tool for identifying who will require massive transfusion. Future studies to evaluate the effect of the prehospital ABC score on clinical care and mortality are necessary.

S689 Utilization of Risk Stratification Scores to Triage Patients With GI Bleed: A Retrospective Cohort Analysis

Introduction: Gastrointestinal (GI) bleeding affects 30-40 per 100,000 hospitalized patients annually. Many of these patients can have severe bleeding with hemodynamic instability and rapid clinical deterioration, often requiring higher levels of care such as intermediate units (IU) or intensive care units (ICU). This study aimed to compare various risk stratification tools with patient outcomes to find which tools can best help providers triage patients most appropriately on admission. Methods: This is a single-center retrospective cohort analysis of patients admitted to IU or ICU with GI bleeding as their primary diagnosis from March, 2015 - March, 2021. Medical records of patients above 18 years of age were reviewed for baseline characteristics, lab values, 30-day mortality, and 90-day readmission. Charlson comorbidity index (CCI), Glasgow-Blatchford Bleeding Score (GBS), AIMS 65, Assessment of Blood Consumption (ABC), quick Sequential Organ Failure Assessment (qSOFA) scores on admission were calculated. Patients were compared according to the level of care. Pearson Chi-square and Mann Whitney U were applied to compare groups. (Figure) Results: Out of 299 patients admitted with GI bleeding, 195 (65.2%) were admitted to IU and 104 (34.8%) to ICU. Baseline characteristics are illustrated in Table. As for treatment, antibiotics (28.8% ICU vs. 10.3% IU; p< 0.01) and PRBC transfusions (median: 3.0 ICU vs. 2.0 IU; p< 0.01) were more frequently utilized in ICU. Outcome variables assessed included need for endoscopic intervention, time to scope, and 90-day readmission rates; no significant difference was seen between groups. Patients admitted to the IU had lower 30-day mortality (p=0.02). Out of the five scores assessed, GBS, AIM-65, and qSOFA were noted to be statistically significant with score being higher in patients admitted to ICU: median (interquartile range (IQR))– GBS: 12 (9, 14.75) vs. 11.00 (8, 13); p< 0.05; AIM-65: 1 (1,2) vs. 1(0,2); p< 0.01, and qSOFA: 0(0,1) vs. 0(0,1); p< 0.01.No significant difference was noted between the median (IQR) CCI and ABC scores between ICU vs. IU: CCI: 5(3,7) vs. IU: 5 (3,7); p >0.05 and ABC: 0 (0,1) vs. IU: 0 (0,1); p >0.05. Conclusion: Our study highlights the utility of scoring tools including GBS, qSOFA, and AIM-65 to assist with triaging GI bleed patients to an appropriate level of care. The scores should be calculated at the time of admission for GI bleed patients and those with elevated scores may benefit from closer monitoring in the ICU. Table 1. - Illustrating the comparison of baseline characteristics, medical history, end organ damage (troponin leak and AKI), 30-day mortality, and 90-day readmission rates, between the patients admitted to intensive care unit and intermediate level of care ICU, n (%) = 104 (34.8%)IU n, (%) = 195 (65.2 p-value Age, mean ± SD (median, IQR) 65.56 ±14.64 (65.50, 55.25-77.00) 68.75±15.71 (71.00, 57.00-80.00) 0.078 GenderMaleFemale 57 (54.8%)47 (45.2%) 113 (57.9%)82 (42.1%) 0.601 RaceCaucasianBlackHispanicOther including data unavailable 69 (66.3%)11 (10.6%)7 (6.7%)17 (16.4%) 126 (64.6%)32 (16.4%)16 (8.2%)21 (10.8%) 0.476 History of HTN 56 (53.8%) 125 (64.1%) 0.155 History of DM 29 (27.9%) 51 (26.2%) 0.747 History of CAD 25 (24%) 78 (40%) 0.006 History of HF 32 (30.8%) 49 (25.1%) 0.296 History of CKD 27 (26%) 53 (27.2%) 0.821 History of Liver disease 23 (22.1%) 35 (17.9%) 0.482 History of DVT/PE 5 (4.8%) 23 (11.9%) 0.047 Personal history of GI tract cancer 10 (9.6%) 24 (12.3%) 0.593 Family history of GI tract cancer 5 (4.8%) 14 (7.2%) 0.625 Use of NSAIDs 17 (16.7%) 23 (12.1%) 0.280 Use of anticoagulants 40 (39.2%) 61 (31.8%) 0.201 Use of antiplatelets 30 (29.4%) 60 (31.1%) 0.766 Use of PPI at home 30 (29.4%) 69 (36.1%) 0.377 Troponin leak 12 (11.5%) 11 (5.6%) 0.172 AKI 48 (46.2%) 46 (23.6%) < 0.001 Antibiotics 30 (28.8%) 20 (10.3%) < 0.001 No. of PRBCs, mean ± SD (median, IQR) 3.29 ±2.64 (3.0, 2-4) 2.13 ±2.61 (2.0, 0-3) < 0.01 Endoscopic intervention 41 (39.4%) 59 (30.3%) 0.110 Time to scope, mean ± SD (median, IQR) 1.35±1.78 (1.0, 0.75-2.00) 1.72±1.46 (1.0, 1-2) 0.051 Alive at 30 days 81 (77.9%) 171 (88.1%) 0.020 90-day readmission due to GI Bleed 17 (16.3%) 41 (21%) 0.330 ICU – Intensive Care Unit; HTN – Hypertension; DM – Diabetes mellitus; CAD – coronary artery disease; HF – Heart Failure; AF – Atrial Fibrillation; CKD – Chronic Kidney Disease; DVT – Deep venous thrombosis; PE – Pulmonary embolism; NSAIDs – Non steroidal anti-inflammatory drugs; PPI – Proton Pump Inhibitors; AKI – Acute Kidney Injury; PRBC – Packed Red Blood Cells.

Prediction of massive transfusion with the Revised Assessment of Bleeding and Transfusion (RABT) score at Canadian level I trauma centers

BackgroundEarly damage control resuscitation and massive transfusion (MT) protocol activations improve outcomes in trauma patients with hemorrhagic shock, where scores to guide MT prediction are used including: the Assessment of Blood Consumption (ABC), Shock Index (SI), and Revised Assessment of Bleeding and Transfusion (RABT) scores. Our aim was to validate the RABT score in patients from two level I trauma centers in Canada. MethodsA retrospective review of adult patients meeting trauma team activation criteria receiving >1 unit of red blood cells (RBCs) within 24 h of admission, from 2015 to 2020, was conducted. A RABT score ≥ 2, ABC score ≥ 2, and Shock Index (SI) ≥ 1 was used to predict MT using both research (≥10 RBCs in 24 h) and clinical (≥3 RBCs in 3 h) definitions. Scores were assessed and compared using sensitivity, specificity, and the area under the receiver operating characteristic (AUROC). ResultsWe analyzed 514 patients with a mean age of 44.4 (19.2) years and a median injury severity score of 29 [18–38]. For both MT definitions, the RABT score trended towards higher sensitivity and lower specificity compared to ABC score and SI. For both research and clinical definitions of MT, the AUROC for the RABT score was not significantly higher (Research - RABT: 0.673 [0.610–0.735], ABC: 0.642 [0.551–0.734], SI 0.691 [0.625–0.757]; Clinical - RABT: 0.653 [0.608–0.698], ABC: 0.646 [0.600–0.691], SI 0.610 [0.559–0.660]). ConclusionThe RABT score is a valid tool for predicting the need for MTPs, performing similarly with a trend towards higher sensitivity when compared to the ABC score and SI.

Comparison of Shock Index With the Assessment of Blood Consumption Score for Association With Massive Transfusion During Hemorrhage Control for Trauma.

Hemorrhage is a leading cause of early mortality following trauma. A massive transfusion protocol (MTP) to guide resuscitation while bleeding is definitively controlled may improve outcomes. Prompts to initiate massive transfusion (MT) include shock index (SI) and the Assessment of Blood Consumption (ABC) score. To compare SI with the ABC score for association with transfusion requirement, need for emergency hemorrhage interventions, and early mortality. A retrospective cohort analysis of trauma MTP activations at our Level I trauma center was conducted from January 1, 2012, to December 31, 2016. The study data were obtained from the Trauma Registry and the blood bank. An SI cutoff of 1.0 was chosen for comparison with the positive ABC score. The study cohort included 146 patients. Shock index ≥ 1 had significant association with MT requirement (p = .002) whereas a positive ABC score did not (p = .65). More patients with SI ≥ 1 required bleeding control interventions (67% surgery, 47% interventional radiology) than patients having a positive ABC score (49% surgery, 29% interventional radiology). For geriatric patients who received MT, 65% had SI ≥ 1 but only 30% had a positive ABC score. Three-hour mortality following emergency department arrival was similar (60% SI ≥ 1, 62% positive ABC score). Shock index ≥ 1 outperformed a positive ABC score for association with MT requirement. Shock index is a simple tool registered nurses can independently utilize to anticipate MT.

Comparison of Shock Index With the Assessment of Blood Consumption Score for Association With Massive Transfusion During Hemorrhage Control for Trauma.

Comparison of Shock Index With the Assessment of Blood Consumption Score for Association With Massive Transfusion During Hemorrhage Control for Trauma.

Early packed red blood cell transfusion in major trauma patients: Evaluation and comparison of different prediction scores for massive transfusion.

Our study sought to evaluate and compare different prediction scores for massive transfusion in-hospital packed red blood cell (PRBC) transfusions. Between January 2013 and December 2018, 1843 trauma patients were enrolled in the registry of a level-1 trauma centre. All prehospital and in-hospital variables needed to calculate the Shock Index and RED FLAG, Assessment of Blood Consumption (ABC) and Trauma Associated Severe Hemorrhage (TASH) scores were prospectively collected in the registry. The primary endpoint was the initiation of transfusion within the first hour of the patient's arrival at the hospital. A total of 1767 patients were included for analysis with a mean age of 43 years (±19) and a mean Injury Severity Score of 15 (±14). The in-hospital TASH score had the highest predictive performance overall (area under the curve [AUC]=0.925, 95% confidence interval [CI] [0.904-0.946]), while the RED FLAG score (AUC=0.881, 95% CI [0.854-0.908]) had the greatest prehospital predictive performance compared to the ABC score (AUC=0.798, 95% CI [0.759-0.837]) and Shock Index (AUC=0.795, 95% CI [0.752-0.837]). Using their standard thresholds, the RED FLAG score was the most efficient in predicting early transfusion (sensitivity: 87%, specificity: 76%, positive predictive value: 25%, negative predictive value: 99%, Youden index: 0.63). The RED FLAG score appears to outperform both the ABC score and the Shock Index in predicting early in-hospital transfusion in trauma patients managed by pre-hospital teams. If adopted, this score could be used to give advance warning to trauma centres or even to initiate early transfusion during pre-hospital care.

Prehospital ABC Score Accurately Forecasts Patients Who Will Require Immediate Resource Utilization.

Scoring systems, such as the Assessment of Blood Consumption (ABC) Score, are used to identify patients at risk for massive transfusion (MT, ≥10 U red blood cells in 24 hours). Our aeromedical transport helicopter uses ultrasound to perform the Focused Assessment with Sonography for Trauma (FAST) examination. Our objective was to evaluate the ability of the Prehospital ABC (PhABC) Score to predict blood transfusions and the need for emergent laparotomy. Post hoc analysis of a prospective observational study of trauma patients who underwent an in-flight FAST during aeromedical transport during a 7-month period. PhABC Score was positive if ≥2 of the following were present in flight: penetrating trauma, heart rate >120 bpm, systolic blood pressure <90 mm Hg, or a positive abdominal FAST. The PhABC Score was evaluated by area under the receiver operating characteristic (AUROC) curves and logistic regression. A total of 291 trauma patients met inclusion criteria, 23 underwent emergent laparotomy, and 12 received an MT. A positive PhABC Score predicted emergent laparotomy, with a positive predictive value of 48% and a negative predictive value of 95% (sensitivity 46%, specificity 96%, AUROC curve 0.83). A positive PhABC Score also predicted receipt of an MT with a positive predictive value of 28% and a negative predictive value of 94% (sensitivity 33%, specificity 93%, AUROC curve 0.77). Multiple logistic regression identified FAST as the most powerful contributor of the PhABC Score to the prediction of both emergent laparotomy (odds ratio 8.5, P < 0.001) and MT (odds ratio 5.9, P < 0.001). The PhABC Score effectively predicts in-hospital resource utilization. It provides an outstanding undertriage rate from the prehospital setting, and it is helpful to improve trauma team activation, mobilize blood products, and prepare the operating room.

Assessment of blood consumption score for pediatrics predicts transfusion requirements for children with trauma.

Although transfusion is a primary life-saving technique, the assessment of transfusion requirements in children with trauma at an early stage is challenging. We aimed to develop a scoring system for predicting transfusion requirements in children with trauma.This was a case–control study that employed a nationwide registry of patients with trauma (Japan Trauma Data Bank) and included patients aged <16 years with blunt trauma between 2004 and 2015. An assessment of blood consumption score for pediatrics (ped-ABC score) was developed based on previous literatures and clinical relevance. One point was assigned for each of the following criteria: systolic blood pressure ≤90 mm Hg, heart rate ≥120/min, Glasgow coma scale (GCS) score <15, and positive focused assessment with sonography for trauma (FAST) scan. For sensitivity analysis, we assessed age-adjusted ped-ABC scores using cutoff points for different ages.Among 5943 pediatric patients with trauma, 540 patients had transfusion within 24 hours after trauma. The in-hospital mortality rate was 2.6% (145/5615). The transfusion rate increased from 7.6% (430/5631) to 35.3% (110/312) in patients with systolic blood pressure ≤90 mm Hg (1 point), from 6.1% (276/4504) to 18.3% (264/1439) in patients with heart rate ≥120/min (1 point), from 4.1% (130/3198) to 14.9% (410/2745) in patients with disturbance of consciousness with GCS score <15 (1 point), and from 7.4% (400/5380) to 24.9% (140/563) in patients with positive FAST scan (1 point). Ped-ABC scores of 0, 1, 2, 3, and 4 points were associated with transfusion rates of 2.2% (48/2210), 7.5% (198/2628), 19.8% (181/912), 53.3% (88/165), and 89.3% (25/28), respectively. After age adjustment, c-statistic was 0.76 (95% confidence interval, 0.74–0.78).The ped-ABC score using vital signs and FAST scan may be helpful in predicting the requirement for transfusion within 24 hours in children with trauma.

Accuracy of CHULA (Class-4 Hemorrhage Unresponsive to Lactated Ringer’s) Criteria for Massive Transfusion Protocol Activation in Trauma Patients

Background: In massive bleeding trauma patients, the use of massive transfusion protocol (MTP) has been shown to improve the outcome. However, the triggers for MTP activation vary among institutions. One of the most commonly used scoring systems to predict massive transfusion (MT) is the assessment of blood consumption (ABC) score. The authors’ institution has used a simple clinical criterion, the Class-4 Hemorrhage Unresponsive to Lactated Ringer’s (CHULA criteria), as a trigger for MTP activation. Objective: To identify the accuracy of CHULA criteria for MTP activation in trauma patients. Materials and Methods: Between April 2013 and April 2016, the authors retrospectively collected the data of trauma patients receiving blood transfusion in the first 24 hours at King Chulalongkorn Memorial Hospital, including demographic data, trauma scores, amount of blood transfusion, and mortality. The detail of CHULA criteria included 1) a patient with clinical signs of Class-4 hemorrhage, 2) not responding to one to two liters of Lactated Ringer’s bolus, and 3) had suspected ongoing bleeding. MT was defined as 1) packed red blood cells (PRC) transfusion of equal to or greater than 10 units in 24 hours, or 2) PRC transfusion of more than four units in the first hour. The accuracy of CHULA criteria for MTP activation was analyzed. Comparison between CHULA criteria and ABC score (of equal to or greater than 2) was also performed. Results: Three hundred fifty-eight patients were included in the present study, 292 males and 66 females. The mechanisms of injury were 68% blunt and 32% penetrating, with an average injury severity score of 21. MTP was activated by CHULA criteria in 100 patients and 73 received MT. Of the 258 patients who did not meet CHULA criteria, five received MT. As a trigger for MT activation, CHULA criteria had sensitivity, specificity, and accuracy of 93.6%, 90.4%, and 91%, respectively; while ABC score had sensitivity, specificity, and accuracy of 62.8%, 78.9%, and 75.4%, respectively. Conclusion: CHULA criteria can predict MT in trauma patients with 91% accuracy. When compared with ABC score, CHULA criteria were not inferior to ABC score in predicting MT. Keywords: Massive transfusion, CHULA criteria, ABC score

Process measure aimed at reducing time to haemorrhage control: outcomes associated with Code Crimson activation in exsanguinating truncal trauma.

Major trauma activation is a process that mobilizes personnel and resources required to care for severely injured patients. Exsanguinating truncal trauma patients require an additional response beyond major trauma activation aimed at expediting haemorrhage control. To address this requirement, 'Code Crimson' (CC) activation was developed. Our aim was to examine the performance of CC activation as a process measure in the identification and management of patients with exsanguinating truncal trauma. Retrospective cohort study (2010-2015) of all adult patients who underwent operative intervention within 6 h of arrival for truncal trauma was performed. Patients were classified into: (i) major haemorrhage (assessment of blood consumption score ≥2, base deficit ≥5 and/or transfusion ≥5 U of red blood cells pre-/intra-operatively), or (ii) no major haemorrhage. We evaluated the proportion of patients with/without major haemorrhage in which a CC was activated as well as time to operating theatre across groups. A total of 210 patients were included with a median Injury Severity Score of 20 (interquartile range (IQR) 9-29) and overall mortality of 13%. Eighty-nine patients were classified as major haemorrhage and 61 patients underwent CC activation. The majority of CC activations (92%) fulfilled major haemorrhage criteria (sensitivity 63%, specificity 96%). Time to theatre was lower in those with CC activation with median time of 23 min (IQR 15-39.5) versus non-CC with median of 95 min (IQR 43-180, P < 0.001). CC was primarily activated in patients with major haemorrhage and led to a decrease in time to theatre for patients with operative truncal trauma.

Multicenter Validation of the Revised Assessment of Bleeding and Transfusion (RABT) Score for Predicting Massive Transfusion.

Massive transfusion (MT) is a lifesaving treatment for hemorrhaging patients. Predicting the need for MT is crucial to improve survival. The aim of our study was to validate the Revised Assessment of Bleeding and Transfusion (RABT) score to predict MT in a multicenter cohort of trauma patients. We performed a (2015-2017) analysis of adult (age ≥ 18year) trauma patients who had a high-level trauma team activation at three Level I trauma centers. The RABT was calculated using the 4-point score [blunt (0)/penetrating trauma (1), shock index ≥ 1 (1), pelvic fracture (1), and FAST positive (1)]. A RABT score of ≥ 2 was used to predict MT (≥ 10 units of packed red blood cells within 24h). The area under the receiver operating characteristic curve (AUROC) was calculated to assess the score's predictive power compared to the Assessment of Blood Consumption(ABC) score. We analyzed 1018 patients: 216 (facility I), 363 (facility II), and 439 (facility III). The mean age was 41 ± 19year, and the injury severity score (ISS) was 29 [22-36]. The overall MT rate was 19%. The overall AUROC of RABT ≥ 2 was 0.89. The sensitivity of the RABT ≥ 2 was 78%, and the specificity was 91%. The RABT score had a higher sensitivity (78% vs. 69%) and specificity (91% vs. 82%) than the ABC score. The RABT score is a valid tool to predict MT in severely injured trauma patients. It is an objective score that aids clinicians in predicting the need for MT to mobilize blood products and minimize the waste of resources.

Estudio piloto sobre escalas predictivas de transfusión masiva: ¿iguales en el paciente traumático que en el médico?

Introduction and objectivesMassive bleeding and associated coagulation disorders are one of the main causes of mortality in critically ill patients. Current studies claim that the majority of massive bleeding is due to traumatic injury, but there is a lack of data about predictive scales and massive transfusion (MT) protocols in non-trauma patients. The objective of this study is to assess the applicability of using the massive transfusion prediction scores of trauma patients in non-trauma patients. MethodsA retrospective exploratory cohort study was conducted between January-December 2017 that included patients older than 18 years admitted to a multidisciplinary ICU of a tertiary hospital for non-traumatic diseases that required MT. An analysis was performed on the relationship between haemodynamic variables (blood pressure and heart rate), biochemistry (lactate, base excess, urea, creatinine, prothrombin activity, thromboplastin activity, INR), as well as the diagnostic group on admission and its association with MT. ResultsA total of 72 patients were included, of which 50 (69.44%) were male. The mean age was 64.33 years. No statistical significance was found in the analysis between the risk factors considered: age, gender, and cardiology history. The mortality was 82%. No statistical significance was found between mortality and haemodynamic variables, biochemical analytical results, or with the TASH (Trauma Associated Severe Haemorrhage score) and the ABC (Assessment of Blood Consumption) score. ConclusionsThe predictive scales used in the trauma scenario are not valid for non-trauma scenarios and would need to be modified. The association of MT with a mortality increase is confirmed.

The Extremity/Mechanism/Shock Index/GCS (EMS-G) score: A novel pre-hospital scoring system for early and appropriate MTP activation

BackgroundNumerous in-hospital scoring systems to activate massive transfusion protocols (MTP) have been proposed; however, to date, pre-hospital scoring systems have not been robustly validated. Many trauma centers do not have blood or pre-thawed plasma available in the trauma bay, leading to delays in balanced transfusion. This study aims to assess pre-hospital injury and physiologic parameters to develop a pre-hospital scoring system predictive of need for massive transfusion (MT) prior to patient arrival. MethodsA retrospective review of all adult full and partial trauma team activations from July 2014–July 2018 from an urban level 2 trauma center was performed utilizing our trauma registry. Stepwise logistic regression analysis was performed to develop a new scoring system, with point totals assigned proportional to the odds ratios of requiring MT for each variable. Internal validation of the EMS-G score was performed using a subset of the data which was not utilized for development of the scoring system, and sensitivity and specificity were compared to previously validated in-hospital scoring systems applied in the pre-hospital setting. Results763 patients were included with 94 patients (12.3%) receiving early MT, defined as 4 units pRBC in 4 h or ED death. In-hospital models for predicting MT such as Assessment of Blood Consumption (ABC) or Shock Index (SI) have sensitivities and specificities of 46/85% and 94/79% respectively for early MTP utilization based on pre-hospital data. Pre-hospital variables found to be predictive of MT were used to develop the EMS-G (Extremity, Mechanism, Shock Index, GCS) score. This system assigns obvious extremity injury–1-point, penetrating mechanism −2 points, shock index ≥0.9–2 points, GCS ≤8–3 points. A score of 3 or greater was chosen to maximize sensitivity and specificity for pre-hospital MT activation. EMS-G score based on pre-hospital report is 89% sensitive, 84% specific, with a PPV of 44% and NPV of 98% for early MT. Using this system, 25% of full and partial trauma team activations met criteria for pre-hospital MTP activation. ConclusionThe EMS-G Score has increased sensitivity and specificity compared to the ABC Score in the pre-hospital setting and appears more appropriate than shock index alone at predicting massive transfusion. This scoring system allows trauma centers to activate MTP prior to patient arrival to ensure early and appropriate blood product administration without blood product wastage.

Systematic reviews of scores and predictors to trigger activation of massive transfusion protocols.

The use of massive transfusion protocols (MTPs) in the resuscitation of hemorrhaging trauma patients ensures rapid delivery of blood products to improve outcomes, where the decision to trigger MTPs early is important. Scores and tools to predict the need for MTP activation have been developed for use to aid with clinical judgment. We performed a systematic review to assess (1) the scores and tools available to predict MTP in trauma patients, (2) their clinical value and diagnostic accuracies, and (3) additional predictors of MTP. MEDLINE, EMBASE, and CENTRAL were searched from inception to June 2017. All studies that utilized scores or predictors of MTP activation in adult (age, ≥18 years) trauma patients were included. Data collection for scores and tools included reported sensitivities and specificities and accuracy as defined by the area under the curve of the receiver operating characteristic. Forty-five articles were eligible for analysis, with 11 validated and four unvalidated scores and tools assessed. Of four scores using clinical assessment, laboratory values, and ultrasound assessment the modified Traumatic Bleeding Severity Score had the best performance. Of those scores, the Trauma Associated Severe Hemorrhage score is most well validated and has higher area under the curve of the receiver operating characteristic than the Assessment of Blood Consumption and Prince of Wales scores. Without laboratory results, the Assessment of Blood Consumption score balances accuracy with ease of use. Without ultrasound use, the Vandromme and Schreiber scores have the highest accuracy and sensitivity respectively. The Shock Index uses clinical assessment only with fair performance. Other clinical variables, laboratory values, and use of point-of-care testing results were identified predictors of MTP activation. The use of scores or tools to predict MTP need to be individualized to hospital resources and skill set to aid clinical judgment. Future studies for triggering nontrauma MTP activations are needed. Systematic review, level III.

Prediction of massive bleeding in a prehospital setting: Validation of six scoring systems

ObjectiveTo validate the diagnostic ability of six different scores to predict massive bleeding in a prehospital setting. DesignRetrospective cohort. SettingPrehospital attention of patients with severe trauma. SubjectsSubjects with more than 15 years, a history of severe trauma (defined by code 15 criteria), that were initially assisted in a prehospital setting by the emergency services between January 2010 and December 2015 and were then transferred to a level one trauma center in Madrid. VariablesTo validate: 1. Trauma Associated Severe Haemorrhage Score. 2. Assessment of Blood Consumption Score. 3. Emergency Transfusión Score. 4. Índice de Shock. 5. Prince of Wales Hospital/Rainer Score. 6. Larson Score. Results548 subjects were studied, 76.8% (420) were male, median age was 38 (interquartile range [IQR]: 27–50). Injury Severity Score was 18 (IQR: 9–29). Blunt trauma represented 82.5% (452) of the cases. Overall, frequency of MB was 9.2% (48), median intensive care unit admission days was 2.1 (IQR: 0.8–6.2) and hospital mortality rate was 11.2% (59). Emergency Transfusión Score had the highest precisions (AUC 0.85), followed by Trauma Associated Severe Haemorrhage score and Prince of Wales Hospital/Rainer Score (AUC 0.82); Assessment of Blood Consumption Score was the less precise (AUC 0.68). ConclusionIn the prehospital setting the application of any of the six scoring systems predicts the presence of massive hemorrhage and allows the activation of massive transfusion protocols while the patient is transferred to a hospital.