Review of Existing Scoring Systems for Massive Blood Transfusion in Trauma Patients: Where Do We Stand?

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

INTRODUCTION

The 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.

METHODS

This 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).

RESULTS

Of 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 %.

CONCLUSION

The 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 EVIDENCE

Level III, Prognostic.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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).

CONCLUSION

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.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level III.

Blood lactate after pre-hospital blood transfusion for major trauma by helicopter emergency medical services

BACKGROUND AND OBJECTIVES

The appropriate use of blood components is essential for ethical use of a precious, donated product. The aim of this study was to report in-hospital red blood cell (RBC) transfusion after pre-hospital transfusion by helicopter emergency medical service paramedics. A secondary aim was to assess the potential for venous blood lactate to predict ongoing transfusion.

MATERIALS AND METHODS

All patients who received RBC in air ambulance were transported to a single adult major trauma centre, had venous blood lactate measured on arrival and did not die before ability to transfuse RBC were included. The association of venous blood lactate with ongoing RBC transfusion was assessed using multi-variable logistic regression analysis and reported using adjusted odds ratios (aOR). The discriminative ability of venous blood lactate was assessed using area under receiver operating characteristics curve (AUROC).

RESULTS

From 1 January 2016 to 15 May 2019, there were 165 eligible patients, and 128 patients were included. In-hospital transfusion occurred in 97 (75.8%) of patients. Blood lactate was associated with ongoing RBC transfusion (aOR: 2.00; 95% confidence interval [CI]: 1.36-2.94). Blood lactate provided acceptable discriminative ability for ongoing transfusion (AUROC: 0.78; 95% CI: 0.70-0.86).

CONCLUSIONS

After excluding patients with early deaths, a quarter of those who had prehospital RBC transfusion had no further transfusion in hospital. Venous blood lactate appears to provide value in identifying such patients. Lactate levels after pre-hospital transfusion could be used as a biomarker for transfusion requirement after trauma.

Consensus of the Brazilian association of hematology, hemotherapy and cellular therapy on patient blood management: Management of critical bleeding

The management of major bleeding is a critical aspect of modern healthcare and it is imperative to emphasize the importance of applying Patient Blood Management (PBM) principles. Although transfusion support remains a vital component of bleeding control, treating severe bleeding goes beyond simply replacing lost blood. A more comprehensive, multidisciplinary approach is essential to optimize patient outcomes and minimize the risks associated with excessive transfusions.

When is enough enough? Odds of survival by unit transfused

BACKGROUND

Balanced transfusion is lifesaving for hemorrhagic shock. The American Red Cross critical blood shortage in 2022 threatened the immediate availability of blood. To eliminate waste, we reviewed the utility of transfusions per unit to define expected mortality at various levels of balanced transfusion.

METHODS

A retrospective study of 296 patients receiving massive transfusion on presentation at a level 1 trauma center was performed from January 2018 to December 2021. Units of packed red blood cells (PRBCs), fresh frozen plasma (FFP), and platelets received in the first 4 hours were recorded. Patients were excluded if they died in the emergency department, died on arrival, received <2 U PRBCs or FFP, or received PRBC/FFP >2:1. Primary outcomes were mortality and odds of survival to discharge. Subgroups were defined as transfused if receiving 2 to 9 U PRBCs, massive transfusion for 10 to 19 U PRBCs, and ultramassive transfusion for ≥20 U PRBCs.

RESULTS

A total of 207 patients were included (median age, 32 years; median Injury Severity Score, 25; 67% with penetrating mechanism). Mortality was 29% (61 of 207 patients). Odds of survival is equal to odds of mortality at 11 U PRBCs (odds ratio [OR], 0.95; 95% confidence interval [CI], 0.50-1.79). Beyond 16 U PRBCs, odds of mortality exceed survival (OR, 0.36; 95% CI, 0.16-0.82). Survival approaches zero >36 U PRBCs (OR, 0.09; 95% CI, 0.00-0.56). Subgroup mortality rates increased with unit transfused (16% transfused vs. 36% massive transfusion, p = 0.003; 36% massive transfusion vs. 67% ultramassive transfusion, p = 0.006).

CONCLUSION

Mortality increases with each unit balanced transfusion. Surgeons should view efforts heroic beyond 16 U PRBCs/4 hours and near futile beyond 36 U PRBCs/4 hours. While extreme outliers can survive, consider cessation of resuscitation beyond 36 U PRBCs. This is especially true if hemostasis has not been achieved or blood supplies are limited.

LEVEL OF EVIDENCE

Prognostic and Epidemiologic; Level IV.

Prediction of pre-hospital blood transfusion in trauma patients based on scoring systems

BACKGROUND

Pre-hospital blood transfusion (PHBT) is a safe and gradually expanding procedure applied to trauma patients. A proper decision to activate PHBT with the presently limited diagnostic options at the site of an incident poses a challenge for pre-hospital crews. The purpose of this study was to compare the selected scoring systems and to determine whether they can be used as valid tools in identifying patients with PHBT requirements.

METHODS

A retrospective single-center study was conducted between June 2018 and December 2020. Overall, 385 patients (aged [median; IQR]: 44; 24-60; 73% males) were included in this study. The values of five selected scoring systems were calculated in all patients. To determine the accuracy of each score for the prediction of PHBT, the Receiver Operating Characteristic (ROC) analysis was used and to measure the association, the odds ratio with 95% confidence intervals was counted (Fig. 1).

RESULTS

Regarding the proper indication of PHBT, shock index (SI) and pulse pressure (PP) revealed the highest value of AUC and sensitivity/specificity ratio (SI: AUC 0.88; 95% CI 0.82-0.93; PP: AUC 0.85 with 95% CI 0.79-0.91).

CONCLUSION

Shock index and pulse pressure are suitable tools for predicting PHBT in trauma patients.

Predictors of Massive Transfusion Protocol Initiation Among Trauma Patients Transported From the Scene Via Flight Emergency Management Services

OBJECTIVE

Early identification of the subset of trauma patients with acute hemorrhage who require resuscitation via massive transfusion protocol (MTP) initiation is vital because such identification can ensure the availability of resuscitation products immediately upon hospital arrival and result in improved clinical outcomes, including reduced mortality. However, there are currently few studies on the predictors of MTP in the unique setting of flight transport.

METHODS

This was a retrospective study of adult trauma patients transported from the scene via flight to 6 trauma centers between March 1, 2019, and January 21, 2021. Patients were included if they had emergency medical service vitals documented. The variables collected included demographics, comorbidities, cause of injury, body regions injured, in-flight treatments, and transport vitals. The primary outcome was MTP initiated by the receiving hospital.

RESULTS

A total of 212 patients were included, of whom 16 (8%) had MTP initiated. During flight transport, 24 (11%) received whole blood, 9 (4%) received packed red blood cells, 11 (5%) had a tourniquet placed, and 5 (2%) received tranexamic acid. In adjusted analyses, receiving whole blood during transport (odds ratio [OR] = 8.52, P < .01), systolic blood pressure ≤ 90 mm Hg (OR = 8.07, P < .01), and a Glasgow Coma Scale score < 13 (OR = 8.38, P < .01) were independently associated with MTP.

CONCLUSIONS

This retrospective cohort study showed that 3 factors readily available in the flight setting-receipt of whole blood, systolic blood pressure, and Glasgow Coma Scale score-are strong predictors of MTP at the receiving facility, particularly when considered in aggregate.

Development and Validation of a Prediction Model for Need for Massive Transfusion During Surgery Using Intraoperative Hemodynamic Monitoring Data

Importance

Massive transfusion is essential to prevent complications during uncontrolled intraoperative hemorrhage. As massive transfusion requires time for blood product preparation and additional medical personnel for a team-based approach, early prediction of massive transfusion is crucial for appropriate management.

Objective

To evaluate a real-time prediction model for massive transfusion during surgery based on the incorporation of preoperative data and intraoperative hemodynamic monitoring data.

Design, Setting, and Participants

This prognostic study used data sets from patients who underwent surgery with invasive blood pressure monitoring at Seoul National University Hospital (SNUH) from 2016 to 2019 and Boramae Medical Center (BMC) from 2020 to 2021. SNUH represented the development and internal validation data sets (n = 17 986 patients), and BMC represented the external validation data sets (n = 494 patients). Data were analyzed from November 2020 to December 2021.

Exposures

A deep learning-based real-time prediction model for massive transfusion.

Main Outcomes and Measures

Massive transfusion was defined as a transfusion of 3 or more units of red blood cells over an hour. A preoperative prediction model for massive transfusion was developed using preoperative variables. Subsequently, a real-time prediction model using preoperative and intraoperative parameters was constructed to predict massive transfusion 10 minutes in advance. A prediction model, the massive transfusion index, calculated the risk of massive transfusion in real time.

Results

Among 17 986 patients at SNUH (mean [SD] age, 58.65 [14.81] years; 9036 [50.2%] female), 416 patients (2.3%) underwent massive transfusion during the operation (mean [SD] duration of operation, 170.99 [105.03] minutes). The real-time prediction model constructed with the use of preoperative and intraoperative parameters significantly outperformed the preoperative prediction model (area under the receiver characteristic curve [AUROC], 0.972; 95% CI, 0.968-0.976 vs AUROC, 0.824; 95% CI, 0.813-0.834 in the SNUH internal validation data set; P < .001). Patients with the highest massive transfusion index (ie, >90th percentile) had a 47.5-fold increased risk for a massive transfusion compared with those with a lower massive transfusion index (ie, <80th percentile). The real-time prediction model also showed excellent performance in the external validation data set (AUROC of 0.943 [95% CI, 0.919-0.961] in BMC).

Conclusions and Relevance

The findings of this prognostic study suggest that the real-time prediction model for massive transfusion showed high accuracy of prediction performance, enabling early intervention for high-risk patients. It suggests strong confidence in artificial intelligence-assisted clinical decision support systems in the operating field.

Development and Validation of a Dynamic Prediction Model for Massive Hemorrhage in Trauma

Objectives

Early warning prediction of massive hemorrhages can greatly reduce mortality in trauma patients. This study aimed to develop and validate dynamic prediction models for massive hemorrhage in trauma patients.

Methods

Based on vital signs (e.g., heart rate, respiratory rate, pulse pressure, and peripheral oxygen saturation) time-series data and the gated recurrent unit algorithm, we characterized a group of models to flexibly and dynamically predict the occurrence of massive hemorrhages in the subsequent T hours (where T = 1, 2, and 3). Models were evaluated in terms of accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and the area under the curve (AUC).

Results

Results show that of the 2205 trauma patients selected for model development, a total of 265 (12.02%) had a massive hemorrhage. The AUCs of the model in the 1-h-group, 2-h-group, and 3-h-group were 0.763 (95% CI: 0.708-0.820), 0.775 (95% CI: 0.728-0.823), and 0.756 (95% CI: 0.715-0.797), respectively. Finally, the models were used in a web calculator and information system for the hospital emergency department.

Conclusions

This study developed and validated a group of dynamic prediction models based on vital sign time-series data and a deep-learning algorithm to assist medical staff in the early diagnosis and dynamic prediction of a future massive hemorrhage in trauma.

A prediction model for massive hemorrhage in trauma: a retrospective observational study

Background

Massive hemorrhage is the main cause of preventable death after trauma. This study aimed to establish prediction models for early diagnosis of massive hemorrhage in trauma.

Methods

Using the trauma database of Chinese PLA General Hospital, two logistic regression (LR) models were fit to predict the risk of massive hemorrhage in trauma. Sixty-two potential predictive variables, including clinical symptoms, vital signs, laboratory tests, and imaging results, were included in this study. Variable selection was done using the least absolute shrinkage and selection operator (LASSO) method. The first model was constructed based on LASSO feature selection results. The second model was constructed based on the first vital sign recordings of trauma patients after admission. Finally, a web calculator was developed for clinical use.

Results

A total of 2353 patients were included in this study. There were 377 (16.02%) patients with massive hemorrhage. The selected predictive variables were heart rate (OR: 1.01; 95% CI: 1.01–1.02; P<0.001), pulse pressure (OR: 0.99; 95% CI: 0.98–0.99; P = 0.004), base excess (OR: 0.90; 95% CI: 0.87–0.93; P<0.001), hemoglobin (OR: 0.95; 95% CI: 0.95–0.96; P<0.001), displaced pelvic fracture (OR: 2.13; 95% CI: 1.48–3.06; P<0.001), and a positive computed tomography scan or positive focused assessment with sonography for trauma (OR: 1.62; 95% CI: 1.21–2.18; P = 0.001). Model 1, which was developed based on LASSO feature selection results and LR, displayed excellent discrimination (AUC: 0.894; 95% CI: 0.875–0.912), good calibration (P = 0.405), and clinical utility. In addition, the predictive power of model 1 was better than that of model 2 (AUC: 0.718; 95% CI: 0.679–0.757). Model 1 was deployed as a public web tool (http://82.156.217.249:8080/).

Conclusions

Our study developed and validated prediction models to assist medical staff in the early diagnosis of massive hemorrhage in trauma. An open web calculator was developed to facilitate the practical application of the research results.

Accuracy of risk tools to predict critical bleeding in major trauma: A systematic review with meta-analysis

BACKGROUND

Early detection of critical bleeding by accurate tools can help ensure rapid delivery of blood products to improve outcomes in major trauma patients. We conducted a systematic review to evaluate the accuracy of risk tools to predict critical bleeding in patients with major trauma.

METHODS

PubMed, Embase, and CENTRAL were searched up to February 2021 for studies investigating risk tools to predict critical bleeding for major trauma people in prehospital and emergency department. We followed the Preferred Reporting Items for Systematic Review and Meta-Analysis of Diagnostic Test Accuracy study guidelines. Two independent authors included studies, extracted data, appraised the quality using the Quality Assessment of Diagnostic Accuracy Studies 2 and assessed the certainty of evidence (CoE) using the Grading of Recommendations Assessment, Development and Evaluation methodology. Sensitivity, specificity, and the receiver operating characteristics curve for all selected triage tools.

RESULTS

Eighty-nine observational studies for adults and 12 observational studies for children met our inclusion criteria. In adults, we found 23 externally validated and 28 unvalidated tools; in children, 3 externally validated tools and 5 unvalidated. In the externally validated tools, we identified those including clinical, laboratory, and ultrasound assessments. Among tools including only a clinical assessment, the Shock Index showed high sensitivity and specificity with the CoE ranging from very low to moderate in adults, as well as Shock Index Pediatric Age adjusted with a moderate CoE. We found that tools using clinical, laboratory, and ultrasound assessments were overall more accurate than those tools without all three components.

CONCLUSION

Clinicians should consider risk tools to predict critical bleeding in a time-sensitive setting like major life-threatening trauma. The Shock Index and Shock Index Pediatric Age adjusted are easy and handy tools to predict critical bleeding in the prehospital setting. In the emergency department, however, many other tools can be used, which include laboratory and ultrasound assessments, depending on staff experience and resources.

LEVEL OF EVIDENCE

Systematic Review and Meta-Analysis; Level III.

Platelet-Lymphocyte and Neutrophil-Lymphocyte Ratio for Prediction of Hospital Outcomes in Patients with Abdominal Trauma

Background

The platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) reflect the patient inflammatory and immunity status. We investigated the role of on-admission PLR and NLR in predicting massive transfusion protocol (MTP) activation and mortality following abdominal trauma.

Methods

A 4-year retrospective analysis of all adult abdominal trauma patients was conducted. Patients were classified into survivors and nonsurvivors and low vs. high PLR. The discriminatory power for PLR and NLR to predict MTP and mortality was determined. Multivariate logistic regression analysis was performed for predictors of mortality.

Results

A total of 1199 abdominal trauma patients were included (18.7% of all the trauma admissions). Low PLR was associated with more severe injuries and greater rates of hospital complications including mortality in comparison to high PLR. On-admission PLR and NLR were higher in the survivors than in nonsurvivors (149.3 vs. 76.3 (p = 0.001) and 19.1 vs. 13.7 (p = 0.009), respectively). Only PLR significantly correlated with injury severity score, revised trauma score, TRISS, serum lactate, shock index, and FASILA score. Optimal cutoffs of PLR and NLR for predicting mortality were 98.5 and 18.5, respectively. The sensitivity and specificity of PLR were 81.3% and 61.1%, respectively, and 61.3% and 51.3%, respectively, for NLR. The AUROC for predicting MTP was 0.69 (95% CI: 0.655–0.743) for PLR and 0.55 (95% CI: 0.510–0.598) for NLR. To predict hospital mortality, the area under the curve (AUROC) for PLR was 0.77 (95% CI: 0.712–0.825) and 0.59 (95% CI: 0.529–0.650) for the NLR. On multivariate logistic regression analysis, the age, Glasgow Coma Scale, sepsis, injury severity score, and PLR were independent predictors of mortality.

Conclusion

On-admission PLR but not NLR helps early risk stratification and timely management and predicts mortality in abdominal trauma patients. Further prospective studies are required.

A prehospital scoring system for predicting the need for emergent blood product transfusion

BACKGROUND

Several tools have been proven to predict the need for massive transfusion in trauma casualties, yet tools that are easily applicable in the prehospital setting for predicting the need for any blood product transfusion in the emergency department (ED) are lacking.

METHODS

A retrospective analysis of the cross-referenced Israeli Defense Forces Trauma Registry and the Israeli National Trauma Registry databases was performed to identify predictors for any blood product transfusion in the ED. A scoring system was developed after internally validating the prediction model. Division to risk groups was performed.

RESULTS

Seven variables (systolic blood pressure, heart rate, arterial oxygen saturation, trunk involvement, mechanism of injury, chest decompression, and tourniquet application) were included in the scoring system, ranging from 0 to 11.5. Risk groups for ED transfusion included very low (0.8%), low (3.2%), intermediate (8.5%), and high (31.2%) risk.

CONCLUSION

A scoring system for predicting the need for any blood product transfusion in the ED was developed, based on information readily available in the early stages of prehospital resuscitation, allowing the receiving medical facility to prepare for that need.

Intelligent prediction of RBC demand in trauma patients using decision tree methods

BACKGROUND

The vital signs of trauma patients are complex and changeable, and the prediction of blood transfusion demand mainly depends on doctors' experience and trauma scoring system; therefore, it cannot be accurately predicted. In this study, a machine learning decision tree algorithm [classification and regression tree (CRT) and eXtreme gradient boosting (XGBoost)] was proposed for the demand prediction of traumatic blood transfusion to provide technical support for doctors.

METHODS

A total of 1371 trauma patients who were diverted to the Emergency Department of the First Medical Center of Chinese PLA General Hospital from January 2014 to January 2018 were collected from an emergency trauma database. The vital signs, laboratory examination parameters and blood transfusion volume were used as variables, and the non-invasive parameters and all (non-invasive + invasive) parameters were used to construct an intelligent prediction model for red blood cell (RBC) demand by logistic regression (LR), CRT and XGBoost. The prediction accuracy of the model was compared with the area under the curve (AUC).

RESULTS

For non-invasive parameters, the LR method was the best, with an AUC of 0.72 [95% confidence interval (CI) 0.657-0.775], which was higher than the CRT (AUC 0.69, 95% CI 0.633-0.751) and the XGBoost (AUC 0.71, 95% CI 0.654-0.756, P < 0.05). The trauma location and shock index are important prediction parameters. For all the prediction parameters, XGBoost was the best, with an AUC of 0.94 (95% CI 0.893-0.981), which was higher than the LR (AUC 0.80, 95% CI 0.744-0.850) and the CRT (AUC 0.82, 95% CI 0.779-0.853, P < 0.05). Haematocrit (Hct) is an important prediction parameter.

CONCLUSIONS

The classification performance of the intelligent prediction model of red blood cell transfusion in trauma patients constructed by the decision tree algorithm is not inferior to that of the traditional LR method. It can be used as a technical support to assist doctors to make rapid and accurate blood transfusion decisions in emergency rescue environment, so as to improve the success rate of patient treatment.

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.

Fibrin monomers and association with significant hemorrhage or mortality in severely injured trauma patients

BACKGROUND

Post-traumatic hemorrhage is still the leading cause of potentially preventable death in patients with severe trauma. Traumatic-induced coagulopathy has been described as a risk factor for significant hemorrhage and mortality in this population. Fibrin monomers (FMs) are a direct marker of thrombin action, and thus reflect coagulation activation. This study sought to determine the association of FMs levels at admission with significant hemorrhage and 28-day mortality after a severe trauma.

METHODS

We conducted a retrospective, observational study including all severe trauma patients admitted in a level-1 trauma center between January 2012 and December 2017. Patients with severe traumatic brain injury or previous anticoagulant / antiaggregant therapies were excluded. FMs measurements and standard coagulation test were taken at admission. Significant hemorrhage was defined as a hemorrhage requiring the transfusion of ≥ 4 Red Blood Cells units during the first 6 h. Multivariable analysis was applied to identify predictors of significant hemorrhage and a simple logistic regression analysis was applied to identify an association between FMs and 28-day mortality.

RESULTS

Overall, 299 patients were included. A total of 47 (16%) experienced a significant hemorrhage. The ROC curve demonstrated that FMs had a poor accuracy to predict the occurrence of significant hemorrhage with an AUC of 0.65 (0.57-0.74). The best threshold at 92.45 µg/ml had excellent sensitivity (87%) and negative predictive value (95%), but was not independently associated with significant hemorrhage (OR = 1.5; 95%CI (0.5-4.2)). The 28-day mortality rate was 5%. In simple logistic regression analysis, FMs values ≥109.5 µg/ml were significantly associated with 28-day mortality (unadjusted OR = 13.2; 95%CI (1.7-102)).

CONCLUSIONS

FMs levels at admission are not associated with the occurrence of a significant hemorrhage in patients with severe trauma. However, the excellent sensitivity and NPV of FMs could help to identify patients with a low risk of severe bleeding during hospital care. In addition, FMs levels ≥109.5 µg/ml might be predictive of 28-day mortality.

Challenges to improving patient outcome following massive transfusion in severe trauma

Introduction: Uncontrolled hemorrhage with trauma-induced coagulopathy (TIC) still represents the most common cause of preventable death after trauma. Timely diagnosis and treatment including bleeding control and hemostatic resuscitation to correct TIC are important, as death from exsanguination occurs rapidly. Recognizing who requires an early massive transfusion together with the initiation of corresponding massive transfusion protocols (MTPs) is key to outcome.Areas covered: This expert review summarizes the current state of MT including the activation and termination of MTPs, complications of MT, and strategies for refinement in the administration of blood products in order to avoid harmful over-transfusion.Expert opinion: MTPs should be initiated and continued until normal physiologic parameters are reached and definitive control of bleeding is achieved. Hospitals should develop their own MTPs, guided by evidence, and according to local infrastructure, logistics, needs and patient populations. Massive transfusion, defined as > 10 units of packed red blood cell concentrates (pRBCs) within the first 24 hours of hospital admission, can be life-saving, but is not without complications. MTPs are currently being refined through targeted and early goal-directed approaches which include functional coagulation testing assays to better guide the administration of blood products and hemostatic agents once the patient is stabilized.

Shock index in patients with traumatic solid organ injury as a predictor of massive blood transfusion protocol activation

Purpose

We aimed to assess the utility of shock index (SI) to predict the need for massive transfusion protocol (MTP) in patients with solid organ injury (SOI) in a Level 1 Trauma center.

Methods

We conducted a retrospective analysis for patients with SOI between 2011 and 2014. Patients were categorized according to on-admission SI into low (< 0.8) and high SI (≥0.8) group.

Results

A total of 4500 patients were admitted with trauma, of them 572 sustained SOIs (289 patients had SI ≥0.8). In comparison to low SI, patients with high SI were younger, had higher injury severity scores (ISS) and lower Trauma and Injury Severity Score (TRISS); (p < 0.001). The proportion of exploratory laparotomy (EXLap), blood transfusion (BT), MTP activation, sepsis and hospital mortality were significantly higher in patients with high SI. Serum lactate (r = 0.34), hematocrit (r = − 0.34), ABC score (r = 0.62), ISS (r = 0.35), and amount of transfused blood (r = 0.22) were significantly correlated with SI. On multivariable regression analysis using 9 relevant variables (age, sex, ISS, ED GCS, serum lactate, hematocrit, Abdomen AIS and Focused assessment with sonography in trauma (FAST) and SI), SI ≥ 0.8 was an independent predictor of BT (OR 2.80; 95%CI 1.56–4.95) and MTP (OR 2.81;95% CI 1.09–7.21) .

Conclusions

In patients with SOI, SI is a simple bedside predictor for BT and MTP activation. Further prospective studies are needed to support our findings.

Females fall more from heights but males survive less among a geriatric population: insights from an American level 1 trauma center

Background

Approximately one third of subjects ≥65 year old and half of subjects ≥80 years old sustain a fall injury each year. We aimed to study the outcomes of fall from a height (FFH) among older adults. We hypothesized that in an elderly population, fall-related injury and mortality are the same in both genders.

Methods

A retrospective analysis was conducted between January 2012 and December 2016 in patients who sustained fall injury at age of at least 60 years and were admitted into a Level 1 Trauma center. Patients were divided into 3 groups: Gp-I: 60–69, Gp-II: 70–79 and Gp-III: ≥80 years old. Data were analyzed and compared using Chi-square, one-way analysis of variance (ANOVA) and logistic regression analysis tests.

Results

Forty-three percent (3665/8528) of adult trauma patients had FFH and 59.5% (2181) were ≥ 60 years old and 52% were women. The risk of fall increased with age with an Odd ratio (OR) 1.52 for age 70–79 and an OR 3.40 for ≥80.

Females fell 1.2 times more (age-adjusted OR 1.24; 95% CI 1.05–1.45) and 47% of ≥80 years old suffered FFH. Two-thirds of FFH occurred at a height ≤ 1 m. Injury severity (ISS, NISS and GCS) were worse in Gp-II, lower extremities max Abbreviated Injury score (max AIS) was higher in Gp-III. Overall mortality was 8.7% (Gp-I 3.6% vs. 11.3% in Gp-II and 14% in Gp- III). Males showed higher mortality than females in the entire age groups (Gp-I: 4.6% vs 1%, Gp-II: 12.9% vs 4.2% and Gp-III: 17.3% vs 6.9% respectively). On multivariate analysis, shock index (OR 3.80; 95% CI 1.27–11.33) and male gender (OR 2.70; 95% CI 1.69–4.16) were independent predictors of mortality.

Conclusions

Fall from a height is more common in older adult female patients, but male patients have worse outcomes. Preventive measures for falls at home still are needed for the older adults of both genders.

Electronic supplementary material

The online version of this article (10.1186/s12877-019-1252-6) contains supplementary material, which is available to authorized users.