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

Joseph, Bellal; Khan, Muhammad; Truitt, Michael S.; Jehan, Faisal; Kulvatunyou, Narong; Azim, Asad; Jain, Arpana; Zeeshan, Muhammad; Tang, Andrew; OʼKeeffe, Terence

doi:10.1007/s00268-018-4674-y

Cited by 32 publications

(41 citation statements)

References 39 publications

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“…The median hospital LOS among survivors was 13 days, [6][7][8][9][10][11][12][14][15][16][17][18][19][20][21][22][23][24] and the ICU stay was 7 days. 3,4,[6][7][8][9][10][11] Patients in the 4-PCC-WB group had shorter ICU LOS (5 days vs. 8 days, p = 0.03). There was no difference in overall hospital LOS among the two groups (13 days vs. 14 days, p = 0.72).…”

Section: Resultsmentioning

confidence: 99%

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

Khurrum

Ditillo

Obaid

et al. 2021

J Trauma Acute Care Surg

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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.

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Section: Resultsmentioning

confidence: 99%

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

Khurrum

Ditillo

Obaid

et al. 2021

J Trauma Acute Care Surg

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“…The first iteration of FAIT indicates that its predictions for MT are excellent, reaching an AUROC of 0.89, compared with 0.80 to 0.89 in the development cohorts of conventional prediction models requiring laboratory tests and/or ultrasonography. 16,20,21,23,27 Of note, the simple FAIT model, which requires only the anatomical location of GSWs, vital signs and age, achieved an AUROC of 0.88. Moreover, FAIT outperformed serial evaluation of the SI, the only other tool validated to predict transfusion requirement and requires exclusively in-field information (AUROC, 0.89 vs. 0.71).…”

Section: Discussionmentioning

confidence: 97%

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

Nederpelt¹,

Mokhtari²,

Alser³

et al. 2021

J Trauma Acute Care Surg

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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.

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“…To our knowledge, six different grading recommendations are currently available, among which, two represent level IV evidence and three utilize a database to develop their score [22-25, 37, 38]. Other recent publications also utilize massive transfusion as the main predictor for complications, but they do not provide treatment recommendations [22,39].…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2020

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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

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

Abstract: Replacement of hypotension and tachycardia with a SI > 1.0 and inclusion of pelvic fracture enhanced discrimination of ABC score for predicting the need for MT. The current ABC score would benefit from revision to more appropriately identify patients requiring MT.

Cited by 32 publications

References 39 publications

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

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

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

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

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