Massive Transfusion: The Revised Assessment of Bleeding and Transfusion (RABT) Score

A novel scoring system for early prediction of massive transfusion requirement in trauma patients

Early resuscitation using blood products is critical for patients with severe hemorrhagic shock. We aimed to develop and validate a new scoring system, hemorrhagic shock transfusion prediction (HSTP) score, to predict the need for massive transfusion (MT) in these patients, compared to the widely used Assessment of Blood Consumption (ABC) score. Trauma patients admitted to Emtiaz Hospital in Iran from 2017 to 2021 were retrospectively included. Patients assigned a code 1 or 2 according to the Emergency severity index (ESI) triage system have been divided into MT and non-MT groups. MT was defined as receiving ≥ 10 units of packed cells (PCs) in 24 h. Demographic information, admission vital signs, and lab results available within 15 min were compared between the groups. A new predictive score was developed using logistic regression of statistically significant parameters. Out of 1029 patients, 651 (63.3%) required MT. An arrival, diastolic blood pressure < 79.5 mm Hg, absolute lymphocyte count > 1850/μL, base excess < - 4.25, and blood glucose > 156 mg/dL were independent predictors included in the HSTP score. The sensitivity and specificity were 74.36% and 53.87% for the HSTP score, compared to 31.03% and 76.16% for the ABC score. Moreover, the positive and negative predictive values were 77.88% and 49.03% for the HSTP score, versus 74.15% and 33.66% for ABC. The new scoring system demonstrated higher sensitivity and improved positive and negative predictive values compared to the ABC score. This score can assist physicians in making accurate transfusion decisions quickly, but further prospective studies are warranted to validate its clinical utility.

Emergency Department Shock Index Outperforms Prehospital and Delta Shock Indices in Predicting Outcomes of Trauma Patients

INTRODUCTION

Multiple shock indices (SIs), including prehospital, emergency department (ED), and delta (ED SI - Prehospital SI) have been developed to predict outcomes among trauma patients. This study aims to compare the predictive abilities of these SIs for outcomes of polytrauma patients on a national level.

METHODS

This was a retrospective analysis of the American College of Surgeons Trauma Quality Improvement Program (2017-2018). We included adult (≥18 y) trauma patients and excluded patients who were transferred, had missing vital signs, and those with severe head injuries (Head-Abbreviated Injury Scale>3). Outcome measures were 24-h and in-hospital mortality, 24-h packed red blood cells transfusions, and intensive care unit and hospital length of stay. Predictive performances of these SIs were evaluated by the Area Under the Receiver Operating Characteristics for the entire study cohort and across all injury severities.

RESULTS

A total of 750,407 patients were identified. Meanstandard deviation age and lowest systolic blood pressure were 53 ± 21 y, and 81 ± 32 mmHg, respectively. Overall, 24-h and in-hospital mortality were 1.2% and 2.5%, respectively. On multivariable analysis, all three SIs were independently associated with higher rates of 24-h and in-hospital mortality, blood product requirements, intensive care unit and hospital length of stay (P < 0.001). ED SI was superior to prehospital and delta SIs (P < 0.001) for all outcomes. On subanalysis of patients with moderate injuries, severe injuries, and positive delta SI, the results remained the same.

CONCLUSIONS

ED SI outperformed both prehospital and delta SIs across all injury severities. Trauma triage guidelines should prioritize ED SI in the risk stratification of trauma patients who may benefit from earlier and more intense trauma activations.

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

BACKGROUND

Accurately 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).

METHODS

The 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).

RESULTS

A 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).

CONCLUSIONS

Our 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.

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

Objective

Develop a novel machine learning (ML) model to rapidly identify trauma patients with severe hemorrhage at risk of early mortality.

Background

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.

Methods

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.

Results

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.

Conclusions

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.

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

BACKGROUND

Early 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.

METHODS

A 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).

RESULTS

We 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]).

CONCLUSION

The 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.

Predictors of transfusion in trauma and their utility in the prehospital environment: a scoping review

Background: Hemorrhage is a leading cause of preventable mortality from trauma, necessitating resuscitation through blood product transfusions. Early and accurate identification of patients requiring transfusions in the prehospital setting may reduce delays in time to transfusion upon arrival to hospital, reducing mortality. The purpose of this study is to characterize existing literature on predictors of transfusion and analyze their utility in the prehospital context.Objectives: The objectives of this study are to characterize the existing quantity and quality of literature regarding predictor scores for transfusion in injured patients, and to analyse the utility of predictor scores for massive transfusions in the prehospital setting and identify prehospital predictor scores for future research.Methods: A search strategy was developed in consultation with information specialists. A literature search of OVID MEDLINE from 1946 to present was conducted for primary studies evaluating the predictive ability of scoring systems or single variables in predicting transfusion in all trauma settings.Results: Of the 5824 studies were identified, 5784 studies underwent title and abstract screening, 94 studies underwent full text review, and 72 studies were included in the final review. We identified 16 single variables and 52 scoring systems for predicting transfusion. Amongst single predictor variables, fluids administered and systolic blood pressure had the highest reported sensitivity (100%) and specificity (89%) for massive transfusion protocol (MTP) activation respectively. Amongst scoring systems for transfusion, the Shock Index and Modified Shock Index had the highest reported sensitivity (96%), while the Pre-arrival Model had the highest reported specificity (95%) for MTP activation. Overall, 20 scores were identified as being applicable to the prehospital setting, 25 scores were identified as being potentially applicable, and seven scores were identified as being not applicable.Conclusions: We identified an extensive list of predictive single variables, validated scoring systems, and derived models for massive transfusion, presented their properties, and identified those with potential utility in the prehospital setting. By further validating applicable scoring tools in the prehospital setting, we may begin to administer more timely transfusions in the trauma population.

Shock index as a predictor for mortality in trauma patients: a systematic review and meta-analysis

PURPOSE

The primary aim was to determine whether a shock index (SI) ≥ 1 in adult trauma patients was associated with increased in-hospital mortality compared to an SI < 1.

METHODS

This systematic review including a meta-analysis was performed in accordance with the PRISMA guidelines. EMBASE, MEDLINE, and Cochrane Library were searched, and two authors independently screened articles, performed the data extraction, and assessed risk of bias. Studies were included if they reported in-hospital, 30-day, or 48-h mortality, length of stay, massive blood transfusion or ICU admission in trauma patients with SI recorded at arrival in the emergency department or trauma center. Risk of bias was assessed using the Newcastle-Ottawa Scale, and the strength and quality of the body of evidence according to GRADE. Data were pooled using a random effects model. Inter-rater reliability was assessed with Cohen's kappa.

RESULTS

We screened 1350 citations with an inter-rater reliability of 0.90. Thirty-eight cohort studies were included of which 14 reported the primary outcome. All studies reported a significant higher in-hospital mortality in adult trauma patients with an SI ≥ 1 compared to those having an SI < 1. Twelve studies involving a total of 348,687 participants were included in the meta-analysis. The pooled risk ratio (RR) of in-hospital mortality was 4.15 (95% CI 2.96-5.83). The overall quality of evidence was low.

CONCLUSIONS

This systematic review found a fourfold increased risk of in-hospital mortality in adult trauma patients with an initial SI ≥ 1 in the emergency department or trauma center.

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

BACKGROUND

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.

OBJECTIVE

To compare SI with the ABC score for association with transfusion requirement, need for emergency hemorrhage interventions, and early mortality.

METHODS

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.

RESULTS

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).

CONCLUSION

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.

Machine Learning for Military Trauma: Novel Massive Transfusion Predictive Models in Combat Zones

BACKGROUND

Damage control resuscitation has become the standard of care in military and civilian trauma. Early identification of blood product requirements may aid in optimizing the clinical decision-making process while improving trauma related outcomes. This study aimed to assess and compare multiple machine learning models for predicting patients at highest risk for massive transfusion on the battlefield.

METHODS

Supervised machine learning approaches using logistic regression, support vector machine, neural network, and random forest techniques were used to create predictive models for massive transfusion using standard prehospital and arrival data points from the Department of Defense Trauma Registry, 2008-2016. Seventy percent of the population was used for model development and performance was validated using the remaining 30%. Models were tested for accuracy and compared by standard performance statistics.

RESULTS

A total of 22,158 patients (97% male, 58% penetrating injury, median age 25-29 y/o, average Injury Severity Score 9, with an overall mortality of 3%) were included in the analysis. Massive transfusion was required by 7.4% of patients. Overall accuracy was found to be above 90% in all models tested. Following cross validation and model training, the random forest model outperformed the alternatively tested models for precision, recall, and area under the curve.

CONCLUSION

Machine learning techniques may allow for more optimal and rapid identification of combat trauma patients at highest risk for massive transfusion. These powerful approaches may uncover novel correlations and help improve triage, activation of massive transfusion resources, and trauma-related outcomes. Further research seeking to optimize and apply these algorithms to trauma-centered research should be pursued.

Blunt Trauma Massive Transfusion (B-MaT) Score: A Novel Scoring Tool

BACKGROUND

Multiple tools predicting massive transfusion (MT) in trauma have been developed but utilize variables that are not immediately available. Additionally, they only differentiate blunt from penetrating trauma and do not account for the large range of blunt mechanisms and their difference in force. We aimed to develop a Blunt trauma Massive Transfusion (B-MaT) score that accounts for high-risk blunt mechanisms and predicts MT needs in blunt trauma patients (BTPs) prior to arrival.

MATERIALS AND METHODS

The adult 2017 Trauma Quality Improvement Program database was used to identify BTPs who were divided into 2 sets at random (derivation/validation). First, multiple logistic regression models were created to determine risk factors of MT (≥6 units of PRBCs within 4-hours or ≥10 units within 24-hours). Next, the weighted average and relative impact of each independent predictor was used to derive a B-MaT score. Finally, the area under the receiver-operating curve (AROC) was calculated.

RESULTS

Of 172,423 patients in the derivation-set, 1,160 (0.7%) required MT. Heart rate ≥ 120bpm, systolic blood pressure ≤ 90mmHg, and high-risk blunt mechanisms were identified as independent predictors for MT. B-MaT scores were derived ranging from 0 -9, with scores of 6, 7, and 9 yielding a MT rate of 11.7%, 19.4%, and 32.4%, respectively. The AROC was 0.86. The validation-set had an AROC of 0.85.

CONCLUSIONS

B-MaT is a novel scoring tool that predicts need for MT in BTPs and can be calculated prior to arrival. B-MaT warrants prospective validation to confirm its accuracy and assess its ability to improve patient outcomes and blood product allocation.

Four-factor prothrombin complex concentrate in adjunct to whole blood in trauma-related hemorrhage: Does whole blood replace the need for factors?

BACKGROUND

The use of whole blood (WB) for the treatment of hemorrhagic shock and coagulopathy is increasing in civilian trauma patients. Four-factor prothrombin complex concentrate (4-PCC) in adjunct to component therapy showed improved outcomes in trauma patients. Our study aims to evaluate the outcomes of trauma patients who received 4-PCC and WB (4-PCC-WB) compared with WB alone.

METHODS

We performed a 3-year (2015-2017) analysis of the American College of Surgeons-Trauma Quality Improvement Program database. All adult (age, ≥18 years) trauma patients who received WB were included. We excluded patients who were on preinjury anticoagulants. Patients were stratified into two groups, 4-PCC-WB versus WB alone, and matched in a 1:2 ratio using propensity score matching. Outcome measures were packed red blood cells, plasma, platelets, and cryoprecipitate transfused, in-hospital complications, hospital and intensive care unit (ICU) length of stay (LOS) among survivors, and mortality.

RESULTS

A total of 252 patients (4-PCC-WB, 84; WB alone, 168) were matched. The mean ± SD age was 47 ± 21 years, 63% were males, median Injury Severity Score was 30 (21-40), and 87% had blunt injuries. Patients who received 4-PCC-WB had decreased requirement for packed red blood cell (8 U vs. 10 U, p = 0.04) and fresh frozen plasma (6 U vs. 8 U, p = 0.01) transfusion, lower rates of acute kidney injury (p = 0.03), and ICU LOS (5 days vs. 8 days, p = 0.01) compared with WB alone. There was no difference in the platelet transfusion (p = 0.19), cryoprecipitate transfusion (p = 0.37), hospital LOS (p = 0.72), and in-hospital mortality (p = 0.72) between the two groups.

CONCLUSION

Our study demonstrates that the use of 4-PCC as an adjunct to WB is associated with a reduction in transfusion requirements and ICU LOS compared with WB alone in the resuscitation of trauma patients. Further studies are required to evaluate the role of PCC with WB in the resuscitation of trauma patients.

LEVEL OF EVIDENCE

Therapeutic, level III.

Development of a field artificial intelligence triage tool: Confidence in the prediction of shock, transfusion, and definitive surgical therapy in patients with truncal gunshot wounds

BACKGROUND

In-field triage tools for trauma patients are limited by availability of information, linear risk classification, and a lack of confidence reporting. We therefore set out to develop and test a machine learning algorithm that can overcome these limitations by accurately and confidently making predictions to support in-field triage in the first hours after traumatic injury.

METHODS

Using an American College of Surgeons Trauma Quality Improvement Program-derived database of truncal and junctional gunshot wound (GSW) patients (aged 16-60 years), we trained an information-aware Dirichlet deep neural network (field artificial intelligence triage). Using supervised training, field artificial intelligence triage was trained to predict shock and the need for major hemorrhage control procedures or early massive transfusion (MT) using GSW anatomical locations, vital signs, and patient information available in the field. In parallel, a confidence model was developed to predict the true-class probability (scale of 0-1), indicating the likelihood that the prediction made was correct, based on the values and interconnectivity of input variables.

RESULTS

A total of 29,816 patients met all the inclusion criteria. Shock, major surgery, and early MT were identified in 13.0%, 22.4%, and 6.3% of the included patients, respectively. Field artificial intelligence triage achieved mean areas under the receiver operating characteristic curve of 0.89, 0.86, and 0.82 for prediction of shock, early MT, and major surgery, respectively, for 80/20 train-test splits over 1,000 epochs. Mean predicted true-class probability for errors/correct predictions was 0.25/0.87 for shock, 0.30/0.81 for MT, and 0.24/0.69 for major surgery.

CONCLUSION

Field artificial intelligence triage accurately identifies potential shock in truncal GSW patients and predicts their need for MT and major surgery, with a high degree of certainty. The presented model is an important proof of concept. Future iterations will use an expansion of databases to refine and validate the model, further adding to its potential to improve triage in the field, both in civilian and military settings.

LEVEL OF EVIDENCE

Prognostic, Level III.

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

BACKGROUND

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.

METHODS

We performed a (2015-2017) analysis of adult (age ≥ 18 year) 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 24 h). 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.

RESULTS

We analyzed 1018 patients: 216 (facility I), 363 (facility II), and 439 (facility III). The mean age was 41 ± 19 year, 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.

CONCLUSION

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.

Angioembolization in intra-abdominal solid organ injury: Does delay in angioembolization affect outcomes?

INTRODUCTION

Angioembolization (AE) is an integral component in multidisciplinary algorithms for achieving hemostasis in patients with trauma. The American College of Surgeons Committee on Trauma recommends that interventional radiologists be available within 30 minutes to perform emergent AE. However, the impact of the timing of AE on patient outcomes is still not well known. We hypothesized that a delay in AE would be associated with increased mortality and higher blood transfusion requirements in patients with blunt intra-abdominal solid organ injury.

METHODS

A 4-year (2013-2016) retrospective review of the ACS Trauma Quality Improvement Program database was performed. We included adult patients (age, ≥18 years) with blunt intra-abdominal solid organ injury who underwent AE within 4 hours of hospital admission. Patients who underwent operative intervention before AE were excluded. The primary outcome was 24-hour mortality. The secondary outcome was blood product transfusions. Patients were grouped into four 1-hour intervals according to their time from admission to AE. Multivariate regression analysis was performed to accommodate patient differences.

RESULTS

We analyzed 1,009,922 trauma patients, of which 924 (1 hour, 76; 1-2 hours, 224; 2-3 hours, 350; 3-4 hours, 274) were deemed eligible. The mean ± SD age was 44 ± 19 years, and 66% were male. The mean ± SD time to AE was 144 ± 54 minutes, and 92% of patients underwent AE more than 1 hour after admission. Overall 24-hour mortality was 5.2%. On univariate analysis, patients receiving earlier AE had decreased 24-hour mortality (p = 0.016), but no decrease in blood products transfused. On regression analysis, every hour delay in AE was significantly associated with increased 24-hour mortality (p < 0.05).

CONCLUSION

Delayed AE for hemorrhagic control in blunt trauma patients with an intra-abdominal solid organ injury is associated with increased 24-hour mortality. Trauma centers should ensure timeliness of interventional radiologist availability to prevent a delay in vital AE, and it should be a focus of quality improvement projects.

LEVEL OF EVIDENCE

Prognostic, level III.

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

Background

Early 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).

Methods

Patients 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.

Results

In 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.

Conclusions

The novel FASILA score performs well in patients with abdominal trauma and offers advantages over other scores.

Electronic supplementary material

The online version of this article (10.1007/s00268-019-05289-0) contains supplementary material, which is available to authorized users.

Delta Shock Index Predicts Outcomes in Pediatric Trauma Patients Regardless of Age

INTRODUCTION

Changes in the shock index (ΔSI) can be a predictive tool but is not established among pediatric trauma patients. The aim of our study was to assess the impact of ΔSI on mortality in pediatric trauma patients.

METHODS

We performed a 2017 analysis of all pediatric trauma patients (age 0-16 y) from the ACS-TQIP. SI was defined as heart rate(HR)/systolic blood pressure(SBP). We abstracted the SI in the field (EMS), SI in the emergency department (ED) and calculated the change in SI (ΔSI = ED SI-EMS SI). Patients were divided into four age groups: 0-3 y, 4-6 y, 7-12 y, and 13-16 y and substratified into two groups based on the value of the age-group-specific ΔSI cutoff obtained with receiver operating characteristic ROC analysis; +ΔSI and -ΔSI. Our outcome measure was mortality. Multivariable logistic and Cox regression analyses were performed.

RESULTS

We included 31,490 patients. Mean age was 10.6 ± 4.6 y, and 65.8% were male. The overall mortality rate was 1.4%. In the age group 0-3 y the cutoff point for ΔSI was 0.29 with an area under the curve (AUC) 0.70 [0.62-0.79], ΔSI cutoff 4-6 y was 0.41 AUC 0.81 [0.70-0.92], ΔSI cutoff 7-12 y was 0.05 AUC 0.83 [0.76-0.90], and ΔSI cutoff 13-16 y was 0.13 AUC 0.75 [0.69-0.81]. On the Cox regression analysis, +ΔSI was independently associated with increased in-hospital mortality and 24-h mortality (P ≤ 0.01).

CONCLUSIONS

Vital signs vary by age group in children, but ΔSI inherently accounts for this variation. ΔSI predicts mortality and may be utilized as a predictor to help guide triage of pediatric trauma patients.

LEVEL OF EVIDENCE

Level III Prognostic.

The role of cryoprecipitate in massively transfused patients: Results from the Trauma Quality Improvement Program database may change your mind

BACKGROUND

Cryoprecipitate was developed for the treatment of inherited and acquired coagulopathies. The role of cryoprecipitate in hemorrhaging trauma patients is still speculative. The aim of our study was to assess the role of cryoprecipitate as an adjunct to transfusion in trauma patients.

METHODS

We performed a 2-year (2015-2016) analysis of the American College of Surgeons-Trauma Quality Improvement Program data set and included all adult trauma patients who received 4 or greater packed red blood cells (pRBCs)/4 hours. Patients were stratified based on receipt of cryoprecipitate within the first 24 hours (cryoprecipitate vs. no-cryoprecipitate). Outcomes were blood products transfused, in-hospital complications, and mortality. Regression analyses were performed.

RESULTS

A total of 19,643 (cryoprecipitate, 4,945; no-cryoprecipitate, 14,698) were included. Mean age was 40 ± 22 years, median Injury Severity Score was 27 [18-40], and Glasgow Coma Scale score was 9 [3-14]. The overall complication rate was 45%, mortality was 47%, and 29% of the patients died in the first 24 hours. Patients in the cryoprecipitate group received a lower volume of plasma (p < 0.01), and pRBCs (p < 0.01). Additionally, patients who received cryoprecipitate had lower rates of 24-hour mortality (p < 0.01) and in-hospital mortality (p < 0.01). However, there was no difference between the two groups regarding complications (p = 0.36) or volume of platelet transfused (p = 0.22). On multivariate logistic regression, the use of cryoprecipitate was associated with decreased (odds ratio [OR], 0.78 [0.63-0.84]; p = 0.02), in-hospital mortality (OR, 0.79 [0.77-0.87]; p = 0.01), but had no association with in-hospital complications (OR, 1.48 [0.71-1.99]; p = 0.31). On linear regression analysis, the use of cryoprecipitate was not associated with 24-hour pRBCs (β = -0.12 [-0.28 to 0.27], p = 0.47), 24-hour plasma (β = -0.06 [-0.21 to 0.43], p = 0.29), and 24-hour platelets (β = -0.24 [-0.09 to 0.33], p = 0.17) transfusion requirements.

CONCLUSION

The adjunctive use of cryoprecipitate in hemorrhaging trauma patients may reduce mortality without affecting in-hospital complications and transfusion requirements. Further studies are needed to better understand its potentially beneficial effects.

LEVEL OF EVIDENCE

Therapeutic, level IV.

Massive transfusion protocols in nontrauma patients: A systematic review and meta-analysis

BACKGROUND

Massive bleeding is a major cause of death both in trauma and nontrauma patients. In trauma patients, the implementation of massive transfusion protocols (MTP) led to improved outcomes. However, the majority of patients with massive bleeding are nontrauma patients.

OBJECTIVES

To assess if the implementation of MTP in nontrauma patients with massive bleeding leads to improved survival.

DATA SOURCES

National Library of Medicine's Medline database (PubMed).

STUDY ELIGIBILITY CRITERIA

Original research articles in English language investigating MTP in nontrauma patients.

PARTICIPANTS

Nontrauma patients with massive bleeding 18 years or older.

INTERVENTION

Transfusion according to MTP versus off-protocol.

STUDY APPRAISAL AND SYNTHESIS METHODS

Systematic literature review using PubMed. Outcomes assessed were mortality and transfused blood products. Studies that compared mortality of MTP and non-MTP groups were included in meta-analysis using Mantel-Haenszel random effect models.

RESULTS

A total of 252 abstracts were screened. Of these, 12 studies published 2007 to 2017 were found to be relevant to the topic, including 2,475 patients. All studies were retrospective and comprised different patient populations. Most frequent indications for massive transfusion were perioperative, obstetrical and gastrointestinal bleeding, as well as vascular emergencies. Four of the five studies that compared the number of transfused blood products in MTP and non-MTP groups revealed no significant difference. Meta-analysis revealed no significant effect of MTP on the 24-hour mortality (odds ratio 0.42; 95% confidence interval 0.01-16.62; p = 0.65) and a trend toward lower 1-month mortality (odds ratio 0.56; 95% confidence interval 0.30-1.07; p = 0.08).

LIMITATIONS

Heterogeneous patient populations and MTP in the studies included.

CONCLUSION

There is limited evidence that the implementation of MTP may be associated with decreased mortality in nontrauma patients. However, patient characteristics, as well as the indication and definition of MTP were highly heterogeneous in the available studies. Further prospective investigation into this topic is warranted.

LEVEL OF EVIDENCE

Systematic review and meta-analysis, level III.

Review of massive transfusion protocols in the injured, bleeding patient

PURPOSE OF REVIEW

Massive haemorrhage is a significant cause of mortality and morbidity in a variety of clinical settings, although most research has been related to trauma patients. Military studies from recent conflicts found that higher ratios of plasma to red blood cells (RBCs) were associated with increased survival in injured soldiers, and subsequent trials in civilian populations showed similar decreased mortality. Over the last decade, massive transfusion protocols (MTPs) have become an important component in the treatment of the massively bleeding patient. This review is intended to summarize the more recent findings and trends in massive transfusion.

RECENT FINDINGS

There have been several observational studies suggesting that higher ratios of plasma to RBC and platelets to RBC are associated with improved survival but there is a paucity of randomized studies relating to specific ratios, dosages, timing, and guidance. Other studies have developed and assessed scoring systems used to initiate MTPs and specific tests used to guide MTPs. Finally, the specific blood components and adjuncts that constitute a MTP are the subject of further ongoing research.

SUMMARY

The absence of a universal definition of massive bleeding or massive transfusion, heterogeneity in patients suffering from massive bleeding, and the difficulty in predicting which patients will require a massive transfusion all contribute to the difficulty of studying massive transfusion. However, there is evidence that higher plasma : RBC ratios correlate with improved survival, and that adjuncts to transfusion play a key role. Furthermore, recent validations of massive haemorrhage scoring systems should allow more consistent and appropriate triggering of massive transfusions.

How to detect a polytrauma patient at risk of complications: A validation and database analysis of four published scales

Introduction

Early accurate assessment of the clinical status of severely injured patients is crucial for guiding the surgical treatment strategy. Several scales are available to differentiate between risk categories. They vary between expert recommendations and scores developed on the basis of patient data (level II). We compared four established scoring systems in regard to their predictive abilities for early (e.g., hemorrhage-induced mortality) versus late (Multiple Organ Failure (MOF), sepsis, late death) in-hospital complications.

Methods

A database from a level I trauma center was used. The inclusion criteria implied an injury severity score (ISS) of ≥16 points, primary admission, and a complete data set from admission to hospital-day 21. The following four scales were tested: the clinical grading scale (CGS; covers acidosis, shock, coagulation, and soft tissue injuries), the modified clinical grading scale (mCGS; covers CGS with modifications), the polytrauma grading score (PTGS; covers shock, coagulation, and ISS), and the early appropriate care protocol (EAC; covers acid–base changes). Admission values were selected from each scale and the following endpoints were compared: mortality, pneumonia, sepsis, death from hemorrhagic shock, and multiple organ failure.

Statistics

Shapiro-Wilk test for normal distribution, Pearson Chi square, odds ratios (OR) for all endpoints, 95% confidence intervals. Fitted, generalized linear models were used for prediction analysis. Krippendorff was used for comparison of CGS and mCGS. Alpha set at 0.05.

Results

In total, 3668 severely injured patients were included (mean age, 45.8±20 years; mean ISS, 28.2±15.1 points; incidence of pneumonia, 19.0%; incidence of sepsis, 14.9%; death from hem. shock, 4.1%; death from multiple organ failure (MOF), 1.9%; mortality rate, 26.8%). Our data show distinct differences in the prediction of complications, including mortality, for these scores (OR ranging from 0.5 to 9.1). The PTGS demonstrated the highest predictive value for any late complication (OR = 2.0), sepsis (OR = 2.6, p = 0.05), or pneumonia (OR = 2.0, p = 0.2). The EAC demonstrated good prediction for hemorrhage-induced early mortality (OR = 7.1, p<0.0001), but did not predict late complications (sepsis, OR = 0.8 and p = 0.52; pneumonia, OR = 1.1 and p = 0.7) CGS and mCGS are not comparable and should not be used interchangeably (Krippendorff α = 0.045).

Conclusion

Our data show that prediction of complications is more precise after using values that covers different physiological systems (coagulation, hemorrhage, acid–base changes, and soft tissue damage) when compared with using values of only one physiological system (e.g., acidosis). When acid–base changes alone were tested in terms of complications, they were predictive of complications within 72 hours but failed to predict late complications. These findings should be considered when performing early assessment of trauma patients or for the development of new scores.

Prognostic Role of Shock Index in Traumatic Pelvic Fracture: A Retrospective Analysis

BACKGROUND

We aimed to validate the utility of shock index (SI) in predicting the need of blood transfusion and outcomes in patients with traumatic pelvic fracture (TPF).

MATERIALS AND METHODS

We conducted a retrospective analysis for patients who sustained TPF between 2012 and 2016 in a level 1 trauma center. Patients were categorized into patients with low versus high SI based on the cutoff obtained from the receiver operating characteristic curves to predict mortality.

RESULTS

A total of 966 patients sustained TPF (28.5% had SI ≥ 0.9 based on receiver operating characteristic curves) with a median age of 33 (IQR 25-47) y. Type B and C pelvic fractures significantly had higher SI. The frequency of blood transfusion use was greater in patients with high SI (P = 0.001). SI correlated significantly with Injury Severity Score (r = 0.32), Revised Trauma Score (r = -0.40), and transfused blood units (r = 0.35). Patients with high SI had prolonged hospital length of stay and higher mortality (P = 0.001). SI ≥ 0.9 showed high sensitivity and negative predictive value to identify the need of massive blood transfusion (77% and 86%, respectively) and mortality (73.5% and 98.1%, respectively). For hospital mortality, high SI had a sensitivity of 73.5%, specificity 74%, negative predictive value 98%, and negative likelihood ratio of 0.36. After adjustment for age, sex, Injury Severity Score, Glasgow Coma Scale, pelvis Abbreviated Injury Scale, blood transfusion, and Tile classification, the multivariate analysis models showed that high SI was an independent predictor of blood transfusion (odd ratio 5.6) and mortality (odd ratio 3.63).

CONCLUSIONS

SI is a potentially useful instant tool for the prediction of massive transfusion and mortality in patients with TPF. Further prospective studies are warranted to support our findings.

Shock index increase from the field to the emergency room is associated with higher odds of massive transfusion in trauma patients with stable blood pressure: A cross-sectional analysis

Background

The shock index (SI) is defined as the ratio of heart rate/systolic blood pressure. This study aimed to determine the performance of delta shock index (ΔSI), a difference between SI upon arrival at the emergency room (ER) and that in the field, in predicting the need for massive transfusion (MT) among adult trauma patients with stable blood pressure.

Methods

This study included registered data from all trauma patients aged 20 years and above who were hospitalized from January 1, 2009 to December 31, 2016. Only patients who were transferred by emergency medical service from the accident site with a systolic blood pressure ≥ 90 mm Hg at the ER were included. The 7,957 enrolled trauma patients were divided into 2 groups, those who had received blood transfusion ≥ 10 U (MT, n = 82) and those who had not (non-MT, n = 7,875). The odds ratios with 95% confidence intervals for the need for MT by a given ΔSI were measured. The plot of specific receiver operating characteristic (ROC) curves was used to evaluate the best cutoff point of ΔSI that could predict the patient’s probability of receiving MT.

Results

ROC curve analysis showed that a ΔSI of 0.06 as the cutoff point had the highest AUC of 0.61, with a sensitivity of 0.415 and specificity of 0.841. Patients with a ΔSI ≥ 0.00 had a significant 1.8-fold increase in need for MT than those patients with a ΔSI less than 0.00 (1.4% vs. 0.8%, p = 0.01). The larger the ΔSI, the higher the odds of need for an MT. Using the cutoff point of ΔSI of 0.06, patients with a ΔSI ≥ 0.06 had a significant 3.7-fold increase in need for MT than those patients with a ΔSI less than 0.06 (2.7% vs. 0.7%, p < 0.001).

Conclusions

This study indicated that, in trauma patients with stable blood pressure at the ER, the accuracy of prediction of the requirement for MT by ΔSI is low. However, the size of the delta is significantly associated with need for MT and a lack of improvement in the patient’s SI at the ER compared to that in the field significantly increases the odds of a need for MT.