Assessment Of Blood Consumption Research Articles

Evaluating the Shock Index, Revised Assessment of Bleeding and Transfusion (RABT), Assessment of Blood Consumption (ABC) and novel PTTrauma score to predict critical transfusion threshold (CAT) in penetrating thoracic trauma

The shock index (SI) has been associated with predicting transfusion needs in trauma patients. However, its utility in penetrating thoracic trauma (PTTrauma) for predicting the Critical Administration Threshold (CAT) has not been well-studied. This study aimed to evaluate the prognostic value of SI in predicting CAT in PTTrauma patients and compare its performance with the Assessment of Blood Consumption (ABC) and Revised Assessment of Bleeding and Transfusion (RABT) scores. We conducted a prognostic type 2, single-center retrospective observational cohort study on patients with PTTrauma and an Injury Severity Score (ISS) > 9. The primary exposure was SI at admission, and the primary outcome was CAT. Logistic regression and decision curve analysis were used to assess the predictive performance of SI and the PTTrauma score, a novel model incorporating clinical variables. Of the 620 participants, 53 (8.5%) had more than one CAT. An SI > 0.9 was associated with CAT (adjusted OR 4.89, 95% CI 1.64–14.60). The PTTrauma score outperformed SI, ABC, and RABT scores in predicting CAT (AUC 0.867, 95% CI 0.826–0.908). SI is a valuable predictor of CAT in PTTrauma patients. The novel PTTrauma score demonstrates superior performance compared to existing scores, highlighting the importance of developing targeted predictive models for specific injury patterns. These findings can guide clinical decision-making and resource allocation in the management of PTTrauma.

Diagnostic performance of the ABC score in the PROPPR trial

IntroductionThe Assessment of Blood Consumption (ABC) score is used to predict massive transfusions (MT). However, its diagnostic performance has not been widely examined, especially when used as an objective tool to enroll patients in multi-center clinical trials. The purpose of this study was to evaluate the performance of the ABC score in enrolling patients in the Pragmatic Randomized Optimal Platelet and Plasma Ratios (PROPPR) trial. We hypothesized the ABC score would have a similar diagnostic performance to predict the need for massive transfusion as previous studies. MethodsThis is a retrospective analysis of the PROPPR trial. Patients were enrolled either on the basis of an ABC score ≥2, or by Physician Gestalt, when the ABC score was <2. We calculated the sensitivity, specificity, positive (PPV) and negative (NPV) predictive values and likelihood ratios of the ABC score (≥2) for predicting MT (>10 units of red blood cells/24 h or transfusion of >3 units of red blood cells within the first hour). ResultsOf the 680 patients, 438 patients (64 %) had an ABC score of ≥2 and 242 (36 %) had an ABC score of <2. An ABC score of ≥2 had 66.8 % sensitivity and 37.0 % specificity for predicting the need for MT, with a PPV of 88.2 % and NPV of 13.1 %. Similarly, an ABC≥2 had 65.6 % sensitivity and 44.6 % specificity for predicting the need for >3 units RBCs in 1 hour, with a PPV of 89.5 % and NPV of 15.3 %. ConclusionThe ABC score had lower performance than previously reported for predicting MT, when applied to PROPPR trial patients. The performance for predicting the need for a 3-unit red blood cell transfusion (or more) in the first hour was slightly higher. Level of EvidenceLevel III, Prognostic

The predictive value of four traumatic hemorrhage scores for early massive blood transfusion in trauma patients in the pre-hospital setting.

We aimed to explore the predictive value of four traumatic hemorrhage scores for early massive blood transfusion in trauma patients in the pre-hospital setting. Trauma patients admitted to Shenzhen University General Hospital from July 2018 to December 2022 were included in this study. They were divided into the massive transfusion group and the non-massive transfusion group according to the blood transfusion volume within 24h. Basic information about patients was collected. Glasgow Coma Scale (GCS), focused assessment with sonography for trauma (FAST), and injury severity score (ISS) were performed. The receiving operating characteristic (ROC) curve was used to compare the predictive value of four trauma transfusion scores for early massive blood transfusion in the pre-hospital setting. A total of 475 patients were enrolled, 43 received massive blood transfusions and 29 died within 24h. The sensitivity and specificity of the four trauma hemorrhage scores in predicting the need for massive blood transfusions in trauma patients at their recommended cutoff points were all high. Among the four scores, the area under the ROC curve was larger for the assessment of blood consumption (ABC) score (0.864) and smaller for the trauma-induced coagulopathy clinical score (TICCS) score (0.795, p > 0.05). All four pre-hospital trauma hemorrhage scores have a high predictive value in assessing massive blood transfusion in trauma patients.

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.

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.

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.

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

Validation of the mTICCS Score as a Useful Tool for the Early Prediction of a Massive Transfusion in Patients with a Traumatic Hemorrhage.

The modified Trauma-Induced Coagulopathy Clinical Score (mTICCS) presents a new scoring system for the early detection of the need for a massive transfusion (MT). While validated in a large trauma cohort, the comparison of mTICCS to established scoring systems is missing. This study therefore validated the ability of six scoring systems to stratify patients at risk for an MT at an early stage after trauma. A dataset of severely injured patients (ISS ≥ 16) derived from the database of a level I trauma center (2010–2015) was used. Scoring systems assessed were Trauma-Associated Severe Hemorrhage (TASH) score, Prince of Wales Hospital (PWH) score, Larson score, Assessment of Blood Consumption (ABC) score, Emergency Transfusion Score (ETS), and mTICCS. Demographics, diagnostic data, mechanism of injury, injury pattern (graded by AIS), and outcome (length of stay, mortality) were analyzed. Scores were calculated, and the area under the receiver operating characteristic curves (AUCs) were evaluated. From the AUCs, the cut-off point with the best relationship of sensitivity-to-specificity was used to recalculate sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV). A total of 479 patients were included; of those, blunt trauma occurred in 92.3% of patients. The mean age of patients was 49 ± 22 years with a mean ISS of 25 ± 29. The overall MT rate was 8.4% (n = 40). The TASH score had the highest overall accuracy as reflected by an AUC of 0.782 followed by the mTICCS (0.776). The ETS was the most sensitive (80%), whereas the TASH score had the highest specificity (82%) and the PWH score had the lowest (51.83%). At a cut-off > 5 points, the mTICCS score showed a sensitivity of 77.5% and a specificity of 74.03%. Compared to sophisticated systems, using a higher number of weighted variables, the newly developed mTICCS presents a useful tool to predict the need for an MT in a prehospital situation. This might accelerate the diagnosis of an MT in emergency situations. However, prospective validations are needed to improve the development process and use of scoring systems in the future.

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 FASILA Score: A Novel Bio-Clinical Score to Predict Massive Blood Transfusion in Patients with Abdominal Trauma

BackgroundEarly identification of patients who may need massive blood transfusion remains a major challenge in trauma care. This study proposed a novel and easy-to-calculate prediction score using clinical and point of care laboratory findings in patients with abdominal trauma (AT).MethodsPatients with AT admitted to a trauma center in Qatar between 2014 and 2017 were retrospectively analyzed. The FASILA score was proposed and calculated using focused assessment with sonography in trauma (0 = negative, 1 = positive), Shock Index (SI) (0 = 0.50–0.69, 1 = 0.70–0.79, 2 = 0.80–0.89, and 3 ≥ 0.90), and initial serum lactate (0 ≤ 2.0, 1 = 2.0–4.0, and 2 ≥ 4.0 mmol/l). Outcome variables included mortality, laparotomy, and massive blood transfusion (MT). FASILA was compared to other prediction scores using receiver operating characteristics and areas under the curves. Bootstrap procedure was employed for internal validation.ResultsIn 1199 patients with a mean age of 31 ± 13.5 years, MT, MT protocol (MTP) activation, exploratory laparotomy (ExLap), and hospital mortality were related linearly with the FASILA score, Injury Severity Score, and total length of hospital stay. Initial hemoglobin, Revised Trauma Score (RTS), and Trauma Injury Severity Score (TRISS) were inversely proportional. FASILA scores correlated significantly with the Assessment of Blood Consumption (ABC) (r = 0.65), Revised Assessment of Bleeding and Transfusion (RABT) (r = 0.63), SI (r = 0.72), RTS (r = − 0.34), and Glasgow Coma Scale (r = − 0.32) and outperformed other predictive systems (RABT, ABC, and SI) in predicting MT, MTP, ExLap, and mortality.ConclusionsThe novel FASILA score performs well in patients with abdominal trauma and offers advantages over other scores.

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.

Evaluation of Prince of Wales Hospital score in predicting massive blood transfusion in trauma

Objective To evaluate the performance of Prince of Wales Hospital score (PWH score) in predicting the need for massive transfusion (MT) and comparing its performance with Assessment of Blood Consumption (ABC) score and the Trauma-associated Severe Hemorrhage (TASH) score. Background Because of the great risk of massive bleeding that may be life-threatening especially if uncontrolled, early prediction of ongoing bleeding and the need for MT reduce mortality of polytraumatized patients. PWH score was developed for the purpose of early prediction of need of MT. Patients and methods This is a prospective comparative study done on 61 polytraumatized patients, with Injury Severity Score more than or equal to 16, who presented to the Emergency Department of Menoufia University Hospital during the period from September 2017 to September 2018. PWH score was applied to assess its performance and comparing it with ABC and TASH scores. Results PWH, TASH, and ABC scores were applied on 61 patients with trauma meeting inclusion criteria to predict the need for MT. The area under the receiver operating characteristics curve was 0.92 for PWH score, 0.96 for TASH score, and 0.72 for ABC score. PWH was better in performance than ABC score, and TASH score was the most accurate and specific. Conclusion The results of this study support that TASH score has greater area under the (receiver operating characteristics) curve than PWH and ABC scores and is more accurate than both of them at cutoff point of more than or equal to 13.5. PWH performs better than ABC score at cutoff point of more than or equal to 4.5 for PWH and cutoff point of more than or equal to 1.5 for ABC score.

Massive transfusion protocol: the reason it is necessary

Objective. The purpose of this study is to identify problems of emergency transfu-sion at the bedside and to determine need for massive transfusion protocol. Methods. We included patients who met the criteria for “trauma team activation” and were admitted to division of trauma. The amount of blood product transfused in each unit was investigated for balanced transfusion. We also investigated the com-pliance with assessment of blood con-sumption score. The correlation between the time elapsed from patient visit to first transfusion order and time elapsed from first transfusion order to transfusion start was analyzed. Finally, we investigated vari-ous factors which serve to influence the decision-making process regarding early transfusion order.&nbsp;Results. Ratio of packed Red blood cells (pRBC): Fresh frozen plasma (FFP) was well-balanced, but platelet transfusion done was much lower than pRBC and FFP in emergency room. The application of emergency blood release did not match the criteria of assessment of blood consump-tion (ABC) score. The time from the first transfusion order to the transfusion start was found to be constant irrespective of time from patient visit to first transfusion order. And, the time from the first transfu-sion order to transfusion start did not dif-fer significantly among patients with early transfusion order and delayed transfusion order. Only systolic blood pressure of &lt; 90 mmHg was identified as a major predictor for early transfusion order.&nbsp;Conclusion. Balanced transfusion is not easy and emergency transfusion could be delayed at the bedside. Integrated and sys-tematic structures for massive transfusion protocol would be invaluable and indis-pensable.

Effect of Pre-Hospital Use of the Assessment of Blood Consumption Score and Pre-Thawed Fresh Frozen Plasma on Resuscitation and Trauma Mortality

Early blood product resuscitation reduces trauma patient mortality from hemorrhage. This mortality benefit depends on a system that can rapidly identify actively bleeding patients, initiate massive transfusion protocol (MTP), and mobilize resources to the bedside. We hypothesized that process improvement efforts that identify patients early and mobilize appropriate blood products to the bedside for immediate use would improve mortality. Pre-implementation, MTP activation was at the discretion of the trauma surgeon, and only PRBCs were immediately available. In June 2016, the Assessment of Blood Consumption (ABC) score was incorporated in our pre-hospital triage process, and a process for thawed plasma to be available was developed. We performed a retrospective review of patients who were hypotensive on arrival or had MTP activated. We compared mortality and MTP component ratios 15 months pre- vs 15 months post-implementation. Activations of MTP increased 6-fold, while the specificity of the process remained the same. In patients receiving MTP, appropriate blood product transfusion ratios increased 44%. Overall and penetrating trauma mortality improved by 23% and 41%, respectively. When divided by the Injury Severity Score (ISS), penetrating trauma mortality decreased by 65% for the ISS subgroup 15 to 24 and by 38% for ISS subgroup ≥ 25. Length of stay, ICU length of stay, and readmission rates were not significantly different. Delivery of balanced blood product resuscitation is essential to confer mortality benefits. Process improvement directed at early recognition of the hemorrhagic patient, immediate product availability, and product delivery to the bedside for transfusion allows for mortality reduction without increased resource use.