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

Outcomes and Its Associated Factors among Patients with Abdominal Trauma Requiring Laparotomy at Asella Referral and Teaching Hospital, South Central Ethiopia: A Retrospective Cross-Sectional Study

Trauma is a serious public health problem, and abdominal injuries are among the leading causes of hospitalization after trauma. Therefore, this study aimed to determine the outcome of abdominal trauma and its predictors in patients who underwent laparotomy at Asella Referral and Teaching Hospital (ARTH), South Central Ethiopia. We conducted a retrospective institutional based cross-sectional study of patients who underwent laparotomy for abdominal trauma at ARTH from October 1, 2015, to September 30, 2020. Bivariate and multivariate logistic regressions were used to determine associations between independent factors and mortality due to abdominal trauma, and a P value of <0.05 indicated statistical significance. Out of 139 patients, 110 (79.1%) were males and 88 (63.3%) aged <30 years old, with a mean age of 29 ± 15.73 years. The most common mechanism of injury was penetrating trauma, which accounted for 94 (67.6%) patients. The mortality rate was 21 (15.1%). Factors such as blunt mechanism of injury (95% CI: AOR: 3.36, 1.24-9.09), SBP < 90 mmHg at presentation (95% CI: AOR = 9.37, 3.28-26.80), time >6 hours from trauma to admission (95% CI: AOR: 5.44, 1.78-16.63), unstable intraoperative patient condition (95% CI: AOR = 8.82, 3.05-25.52), and patients who need blood transfusion (95% CI: AOR: 6.63, 1.92-22.91) were significantly associated with mortality. The mortality rate of abdominal trauma patients who underwent laparotomy was high. Therefore, healthcare providers should provide priority for traumatic patients as prolonged waiting time to get healthcare results in poor outcomes for the patients.

Reverse Shock Index multiplied by Glasgow Coma Scale score as a point-of-care severity assessment for initial trauma management: A nationwide cohort study

BACKGROUND

Severe trauma patients often require emergent interventions, such as massive transfusion, resuscitative procedures, and surgical procedures, and consume considerable human and medical resources. However, few practical indices can be easily used for emergent interventions. In recent years, it has become clear that rSIG (Reverse Shock Index multiplied by Glasgow Coma Scale [GCS] score), which can be easily calculated from vital signs, is a promising predictor of mortality. However, it is unclear whether rSIG is useful for emergent interventions.

METHODS

Data collected by the Japan Trauma Data Bank for adult patients admitted directly from the scene of trauma between April 2019 and December 2020 were analysed. The outcomes were massive transfusion, resuscitative procedures, surgical procedures and emergent interventions. Emergent interventions were defined as the composite outcome of massive transfusion, resuscitative procedures, and surgical procedures. The ability of rSIG to predict massive transfusion was compared with that of the ABC score and FASILA score by receiver-operating characteristic curve analysis. The ability of rSIG to predict resuscitative and surgical procedures was compared with that of the Shock Index (SI), GCS, Triage Revised Trauma score (T-RTS), and Previous Simple Prediction (PSP) score. The ability of rSIG to predict emergent interventions was compared with that of T-RTS, PSP, ABC, and FASILA. In addition to rSIG, rSIM (Reverse Shock Index multiplied by best motor response score) was also analysed as a supplement.

RESULTS

The study included 32,201 patients, 6,371 of whom required emergent interventions. The area under the receiver-operating characteristic curve (AUROC) for massive transfusion was highest for rSIG (0.846 [95 % confidence interval 0.832-0.859]) and significantly higher for rSIG than for rSIM, ABC and FASILA (all p < 0.0001). AUROCs for resuscitative and surgical procedures were highest for rSIG (0.777 [0.769-0.785] and 0.731 [0.720-0.741], respectively) and significantly higher than those for rSIM, SI, GCS, T-RTS, and PSP (all p < 0.0001). The AUROC for emergent interventions was highest for rSIG (0.760 [0.753-0.768]) and significantly higher for rSIG than for rSIM, T-RTS, PSP, ABC, or FASILA (all p < 0.0001).

CONCLUSIONS

rSIG is a simple and effective point-of-care predictor of emergent interventions during initial management of trauma.

Acute Changes in Body Muscle Mass and Fat Depletion in Hospitalized Young Trauma Patients: A Descriptive Retrospective Study

Background: Loss of muscle mass, and its strength, is associated with adverse outcomes in many medical and surgical conditions. Trauma patients may get malnourished during their hospital course due to many interrelated contributing factors. However, there is insufficient knowledge on the acute muscle and fat changes in young trauma patients in the early days post-admission. Objective: to explore the diagnosis, feeding status, and outcome of muscle mass loss among young abdominal polytrauma patients. Methods: It was a retrospective study including hospitalized abdominal trauma patients who underwent an abdominal computerized tomographic (CT) examination initially and a follow-up one week later. CT scan-based automatic and manual analysis of the muscles and fat of the abdominal region was calculated and compared. Also, we evaluated the feeding and nutritional values to explore the adequacy of the provided calories and proteins and the potential influence of enteral feeding on the CT-based parameters for muscle loss and fat depletion. Results: There were 138 eligible subjects with a mean age of 32.8 ± 13.5 years; of them, 92% were males. Operative interventions were performed on two-thirds of the patients, including abdominal surgery (43%), orthopedic surgeries (34%), and neurosurgical procedures (8.1%). On admission, 56% received oral feeding, and this rate slightly increased to 58.4% after the first week. Enteral feed was prescribed for the remaining, except for two patients. The percentage of change in the total psoas muscle area was significantly reduced after one week of admission in patients on enteral feed as compared to those in the oral feeding group (p = 0.001). There were no statistically significant differences in the percentages of changes in the CT scan findings except for the total psoas muscle area (p = 0.001) and para-spinal muscle area (p = 0.02), which reduced significantly in the those who underwent laparotomy as compared to those who did not need laparotomy. Trauma patients who underwent emergency abdominal surgery lost muscle and fat over time. Conclusions: Loss of muscle mass and body fat is not uncommon among young trauma patients. Patients who underwent laparotomy are more likely to be affected. Further larger studies are needed to assess the specific features in the younger trauma population and how far this can be influenced by the nutrition status and its impact on the clinical outcomes. It could be early or impending stages of sarcopenia linked to trauma patients, or just acute changes in the muscle and fat, that need further investigation and follow-up after hospital discharge.

Predisposing Factors and Outcome of Acute Kidney Injury After Blunt Trauma: A 10-Year Study

INTRODUCTION

Acute kidney injury (AKI) indicates an impairment of the renal function following blunt trauma. It is multifactorial and associated with an increased risk of morbidity and mortality. The incidence and risk factors of AKI in young patients with trauma are not well-described. This study aimed to evaluate the incidence, clinical characteristics, and outcomes of post-traumatic AKI. We hypothesized that AKI is associated with worse outcomes in patients with trauma.

METHODS

This was a retrospective study of all adult trauma patients admitted to a level 1 trauma center between 2011 and 2021. AKI was diagnosed on the basis of the Kidney Disease Improving Global Outcomes criteria. Data were collected and analyzed for patients with and without AKI using chi-square test and Student's t-test. Multivariate logistic regression analysis and Kaplan-Meier curves were performed.

RESULTS

A total of 17,341 patients with trauma were evaluated, of which 140 (0.8%) developed AKI. Patients with AKI were older (40 ± 20 versus 32 ± 16 y), had more comorbidities, and had a higher injury severity score (ISS) and in-hospital mortality (65% versus 3.2%) than non-AKI patients. Direct trauma to the kidney was reported in only nine (6.4%) patients in the AKI group. Among patients with AKI, nonsurvivors had a higher ISS and were more likely to have hypotension, elevated serum lactate, positive troponin, and a lower platelet-to-lymphocyte ratio than survivors. Multiple logistic regression analyses showed that age, ISS, acute respiratory distress syndrome, blood transfusion, diabetes mellitus, onadmission Glasgow coma scale score, and shock index were predictors of AKI in trauma patients, whereas ISS (odds ratio (OR) = 1.05; 95% confidence interval (CI):1.003-1.100; P = 0.03), serum lactate level (OR = 1.25; 95% CI: 1.019-1.533; P = 0.03), and hypotension (OR = 3.22; 95% CI: 1.044-9.945; P = 0.04) were independent predictors of mortality in patients with posttraumatic AKI. Kaplan-Meier survival analysis showed significant differences in mortality among the three stages of AKI (P = 0.03), with the worst outcome in stage III. However, after adjusting for age, hypotension, and ISS, the Cox regression model showed that only stage I had better survival than stages II and III, whereas no survival difference was noted between stages II and III (P = 0.06).

CONCLUSIONS

AKI in young trauma patients is uncommon and associated with a prolonged hospital course and higher mortality. This study identified factors that independently predicted the development of AKI and its outcomes in patients with trauma. However, further prospective and multicenter studies are required to minimize the incidence and complications of posttraumatic AKI.

Shock Index for the Prediction of Interventions and Mortality in Patients With Blunt Thoracic Trauma

INTRODUCTION

Shock index (SI) is a bedside simple scoring tool; however, it has not yet been tested in blunt thorax trauma (BTT). We sought to evaluate the prognostic value of SI for chest interventions (thoracostomy tube or thoracotomy), blood transfusion, and mortality in patients with BTT. We hypothesized that high SI is associated with worse outcomes in patients with BTT.

METHODS

We conducted a retrospective analysis of all BTT patients (chest Abbreviated Injury Score [AIS] > 1) hospitalized in a level 1 trauma center between 2011 and 2020. Patients with AIS >1 for head or abdominal injuries and patients undergoing open reduction and internal fixation surgery or penetrating injuries were excluded. Patients were categorized into two groups (low SI <0.80 versus high SI ≥0.80) based on the receiver operating characteristic curve analysis. Multivariable regression analysis was performed to identify the predictors of mortality.

RESULTS

A total of 1645 patients were admitted with BTT; of them, 24.5% had high SI. The mean age was 39.2 ± 15.2 y, and most were males (91%). Patients with high SI were younger, had sustained severer injuries, and required more chest interventions (P = 0.001), blood transfusion (P = 0.001), and massive transfusion protocol activation (P = 0.001) compared with low SI group. The overall in-hospital mortality rate was 2.6%, which was more in the high SI group (8.2% versus 0.8%; P = 0.001). SI significantly correlated with age (r = -0.281), injury severity score (r = 0.418), Glasgow Come Score on arrival (r = -0.377), Trauma and Injury Severity Score (r = -0.144), Revised Trauma Score (r = -0.219), serum lactate (r = 0.434), blood transfusion units (r = 0.418), and chest AIS (r = 0.066). SI was an independent predictor of mortality (odds ratio 3.506; 95% confidence interval 1.389-8.848; P = 0.008), and this effect persisted after adjustment for chest intervention (odds ratio 2.923; 95% confidence interval 1.146-7.455; P = 0.02).

CONCLUSIONS

The present study highlights the prognostic value of SI as a rapid bedside tool to predict the use of interventions and the risk of mortality in patients with BTT. The study findings help the emergency physicians for early and appropriate risk stratification and triaging of patients with BTT.

Early lactate clearance for predicting outcomes in patients with gastrointestinal bleeding

BACKGROUND

Acute gastrointestinal bleeding (GI bleeding) can range from mild symptoms to life-threatening conditions that require emergency intervention. Therefore, it is important to first identify the high-risk and low-risk patients in the emergency department (ED).

AIMS

This study aimed to investigate the usefulness of a three-hourly interval for determining the lactate clearance, which is shorter than the time interval in previous studies, in order to predict the prognosis early in patients with GI bleeding.

METHODS

This retrospective study involved patients who visited for complaining of GI bleeding symptoms. Initial lactate levels were measured upon arrival at the ED and measured again 3 h later after performing initial resuscitation. And 3-h lactate clearance was calculated. Lactate and 3-h lactate clearance for predicting outcomes were evaluated by the area under the receiver operating characteristic (AUROC) curve.

RESULTS

A total of 104 patients were enrolled and 21 patients (20.2%) died in the hospital. Multivariate logistic regression showed that 3-h lactate clearance was a significant predictor of in-hospital mortality. The AUROC of 3-h lactate clearance for predicting in-hospital mortality was 0.756. The sensitivity and specificity were 66.67% and 75.90%. On combining lactate clearance, total bilirubin, and PTT, the AUROC was 0.899 for predicting in-hospital mortality.

CONCLUSIONS

This study validated that lactate clearance at three-hourly intervals is useful for early prediction of mortality and prognosis in patients with GI bleeding. It is important to perform not only an initial lactate measurement, but also a follow-up lactate measurement after initial resuscitation to check the lactate clearance.

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.

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.

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.