The clinical utility of shock index to predict the need for blood transfusion and outcomes in trauma

Determining the Correlation Between Blood Loss and Clinical Findings Among Patients with Postpartum Hemorrhage

Background

There is a need for signs that will help the midwives or the health care providers attending deliveries to prevent the patient from going into hypovolemic shock, especially when immediate testing is not possible. The study aims to find the correlation between the clinical symptoms and blood loss in women with postpartum hemorrhage.

Methods

It is a descriptive observational study conducted at the Department of Obstetrics and Gynecology, Maternity Hospitals. Women treated with either Misoprostol or Ergometrine during delivery were included in the study. Data were collected for Packed Cell Volume (PCV), Hemoglobin (Hb%), etc.; other investigations include general clinical condition, presence or absence of PPH, and amount of blood loss using laboratory reports.

Results

The study has reported clinical findings and blood loss to identify the correlation between them. Only 4% of women suffered blood loss of more than 500 mL, i.e., postpartum hemorrhage (PPH) occurred among them. The change in Hb% among the majority of the women was ranging between 0-0.5 gm% (71.5%). Most cases (72.72%) had tachycardia followed by palpitation (10.90%). Blood loss exceeding 1500 mL was correlated with hypotension, restlessness, and oliguria.

Conclusions

Extra vigilance is needed to identify women at risk and facilitate early intervention and treatment of PPH.

Impact of shock index (SI), modified SI, and age-derivative indices on acute heart failure prognosis; A systematic review and meta-analysis

BACKGROUND

Heart failure (HF) is still associated with quite considerable mortality rates and usage of simple tools for prognosis is pivotal. We aimed to evaluate the effect of shock index (SI) and its derivatives (age SI (ASI), modified SI (MSI), and age MSI (AMSI)) on acute HF (AHF) clinical outcomes.

METHODS

PubMed/Medline, Scopus and Web of science databases were screened with no time and language limitations till February 2024. We recruited relevant records assessed SI, ASI, MSI or AMSI with AHF clinical outcomes.

RESULTS

Eight records were selected (age: 69.44±15.05 years). Mean SI in those records reported mortality (either in-hospital or long-term death) was 0.67 (95% confidence interval (CI):0.63-0.72)). In-hospital and follow-up mortality rates in seven(n = 12955) and three(n = 5253) enrolled records were 6.18% and 10.14% with mean SI of 0.68(95%CI:0.63-0.73) and 0.72(95%CI:0.62-0.81), respectively. Deceased versus survived patients had higher SI difference (0.30, 95%CI:0.06-0.53, P = 0.012). Increased SI was associated with higher chances of in-hospital death (odds ratio (OR): 1.93, 95%CI:1.30-2.85, P = 0.001).The optimal SI cut-off point was found to be 0.79 (sensitivity: 57.6%, specificity: 62.1%). In-hospital mortality based on ASI was 6.12% (mean ASI: 47.49, 95%CI: 44.73-50.25) and significant difference was found between death and alive subgroups (0.48, 95%CI:0.39-0.57, P<0.001). Also, ASI was found to be independent in-hospital mortality predictor (OR: 2.54, 95%CI:2.04-3.16, P<0.001)). The optimal ASI cut-off point was found to be 49.6 (sensitivity: 66.3%, specificity: 58.6%). In terms of MSI (mean: 0.93, 95%CI:0.88-0.98)), significant difference was found specified by death/survival status (0.34, 95%CI:0.05-0.63, P = 0.021). AMSI data synthesis was not possible due to presence of a single record.

CONCLUSIONS

SI, ASI, and MSI are practical available tools for AHF prognosis assessment in clinical settings to prioritize high risk patients.

Delta shock index predicts injury severity, interventions, and outcomes in trauma patients: A 10-year retrospective observational study

BACKGROUND

Most trauma occurs among young male subjects in Qatar. We examined the predictive values of the delta shock index (DSI), defined as the change in the shock index (SI) value from the scene to the initial reading in the emergency unit (i.e., subtracting the calculated SI at admission from SI at the scene), at a Level 1 trauma center.

AIM

To explore whether high DSI is associated with severe injuries, more interventions, and worse outcomes [i.e., blood transfusion, exploratory laparotomy, ventilator-associated pneumonia, hospital length of stay (HLOS), and in-hospital mortality] in trauma patients.

METHODS

A retrospective analysis was conducted after data were extracted from the National Trauma Registry between 2011 and 2021. Patients were grouped based on DSI as low (≤ 0.1) or high (> 0.1). Data were analyzed and compared using χ 2 and Student's t-tests. Correlations between DSI and injury severity score (ISS), revised trauma score (RTS), abbreviated injury scale (AIS), Glasgow coma scale (GCS), trauma score-ISS (TRISS), HLOS, and number of transfused blood units (NTBU), were assessed using correlation coefficient analysis. The diagnostic testing accuracy for predicting mortality was determined using the validity measures of the DSI. Logistic regression analysis was performed to identify predictors of mortality.

RESULTS

This analysis included 13212 patients with a mean age of 33 ± 14 years, and 24% had a high DSI. Males accounted for 91% of the study population. The trauma activation level was higher in patients with a high DSI (38% vs 15%, P = 0.001). DSI correlated with RTS (r = -0.30), TRISS (r = -0.30), NTBU (r = 0.20), GCS (r = -0.24), ISS (r = 0.22), and HLOS (r = 0.14) (P = 0.001 for all). High DSI was associated with significantly higher rates of intubation, laparotomy, ventilator-associated pneumonia, massive transfusion activation, and mortality than low DSI. For mortality prediction, a high DSI had better specificity, negative predictive value, and negative likelihood ratio (77%, 99%, and 0.49%, respectively). After adjusting for age, emergency medical services time, GCS score, and ISS, multivariable regression analysis showed that DSI was an independent predictor of mortality (odds ratio = 1.9; 95% confidence interval: 1.35-2.76).

CONCLUSION

In addition to sex-biased observations, almost one-quarter of the study cohort had a higher DSI and were mostly young. High DSI correlated significantly with the other injury severity scores, which require more time and imaging to be ready to use. Therefore, DSI is a practical, simple bedside tool for triaging and prognosis in young patients with trauma.

Prehospital Delta Shock Index Predicts Mortality and Need for Life Saving Interventions in Trauma Patients

OBJECTIVES

The delta shock index (ΔSI), defined as the change in shock index (SI) over time, is associated with hospital morbidity and mortality, but prehospital studies about ΔSI are limited. We investigate the association of prehospital ΔSI with mortality and resource utilization, hypothesizing that increases in SI among field trauma patients are associated with increased mortality and blood product transfusion.

METHODS

We performed a multicenter, retrospective, observational study from the Linking Investigators in Trauma and Emergency Services (LITES) network. We obtained data from January 2017 to June 2021. We fit logistic regression models to evaluate the association between an increase ΔSI > 0.1 and 28-day mortality and blood product transfusion within 4 h of emergency department (ED) arrival. We used negative binomial models to evaluate the association between ΔSI > 0.1 and days in hospital, intensive care unit (ICU), and on ventilator (up to 28 days).

RESULTS

We identified 33,219 prehospital patients. We excluded burn patients and those without documented prehospital or ED heart rate or blood pressure, resulting in 30,511 cases for analysis. In adjusted analysis for the primary outcome of 28-day mortality, patients who had a ΔSI > 0.1 based on initial vital signs were 31% more likely to die (adjusted odds ratio (AOR) of 1.31, 95% CI 1.21-1.41) compared to those patients who had a ΔSI ≤0.1. These patients also spent 16% more days in hospital (adjusted incident rate ratio (AIRR) 1.16, 95% CI 1.14-1.19), 34% more days in ICU (AIRR 1.34, 95% CI 1.28-1.41), and 61% more days on ventilator (ARR 1.61, 95% CI 1.47-1.75). Additionally, patients with a ΔSI > 0.1 had higher odds of receiving blood products (AOR 2.00, 95% CI 1.88-2.12) within 4 h of ED arrival. Models fit excluding hypotensive patients performed similarly.

CONCLUSIONS

An increase of greater than 0.1 in the ΔSI was associated with increased 28-day mortality; increased days in hospital, in ICU, and on ventilator; and increased need for blood product transfusion within 4 h of ED arrival. This association held true for initially normotensive patients. Validation and implementation are needed to incorporate ΔSI into prehospital and ED triage.

Decoding cardiogenic shock: assessing shock index and its variants as prognostic indicators for in-hospital mortality

BACKGROUND

Cardiogenic shock (CS) is associated with high in-hospital mortality. Objective assessment of its severity and prognosis is paramount for timely therapeutic interventions. This study aimed to evaluate the efficacy of the shock index (SI) and its variants as prognostic indicators for in-hospital mortality.

METHODS

A retrospective study involving 1282 CS patients were evaluated. Baseline patient characteristics, clinical trajectory, hospital outcomes, and shock indices were collected and analysed. Receiver operating characteristic (ROC) curves were employed to determine the predictive accuracy of shock indices in predicting in-hospital mortality.

RESULTS

Of those evaluated, 866 (67.6%) survived until discharge. Non-survivors were older (66.0 ± 13.7 vs. 57.4 ± 16.2, P < 0.001), had a higher incidence of cardiac risk factors, and were more likely to present with acute coronary syndrome (33.4% vs. 16.1%, P < 0.001) and out-of-hospital cardiac arrest (11.3% vs. 5.3%, P < 0.001). All mean shock indices were significantly higher in non-survivors compared with survivors. ROC curves demonstrated that adjusted shock index (ASI), age-modified shock index (AMSI), and shock index-C (SIC) had the highest predictive accuracy for in-hospital mortality, with AUC values of 0.654, 0.667, and 0.659, respectively. Subgroup analysis revealed that SIC had good predictive ability in patients with STEMI (AUC: 0.714) and ACS (AUC: 0.696) while AMSI and ASI were notably predictive in the OHCA group (AUC: 0.707 and 0.701, respectively).

CONCLUSIONS

Shock index and its variants, especially ASI, AMSI, and SIC, may be helpful in predicting in-hospital mortality in CS patients. Their application could guide clinicians in upfront risk stratification. SIC, ASI, and AMSI show potential in predicting in-hospital mortality in specific CS subsets (STEMI and OHCA). This is the first study to evaluate SI and its variants in CS patients.

Shock index to predict outcomes in patients with trauma following traffic collisions: a retrospective cohort study

PURPOSE

Taiwan, which has a rate of high vehicle ownership, faces significant challenges in managing trauma caused by traffic collisions. In Taiwan, traffic collisions contribute significantly to morbidity and mortality, with a high incidence of severe bleeding trauma. The shock index (SI) and the modified shock index (MSI) have been proposed as early indicators of hemodynamic instability. In this study, we aimed to assess the efficacy of SI and MSI in predicting adverse outcomes in patients with trauma following traffic collisions.

METHODS

This retrospective cohort study was conducted at Chi Mei Hospital from January 2015 to December 2020. The comprehensive analysis included 662 patients, with data collected on vital signs and outcomes such as mortality, blood transfusion, emergent surgical intervention (ESI), transarterial embolization (TAE), and intensive care unit (ICU) admission. Optimal cutoff points for SI and MSI were identified by calculating the Youden index. Logistic regression analysis was used to assess outcomes, adjusting for demographic and injury severity variables.

RESULTS

An SI threshold of 1.11 was associated with an increased risk of mortality, while an SI of 0.84 predicted the need for blood transfusion in the context of traffic collisions. Both SI and MSI demonstrated high predictive power for mortality and blood transfusion, with acceptable accuracy for TAE, ESI, and ICU admission. Logistic regression analyses confirmed the independence of SI and MSI as risk factors for adverse outcomes, thus, providing valuable insights into their clinical utility.

CONCLUSIONS

SI and MSI are valuable tools for predicting mortality and blood transfusion needs in patients with trauma due to traffic collisions. These findings advance the quality of care for patients with trauma during their transition from the emergency room to the ICU, facilitating prompt and reliable decision-making processes and improving the care of patients with trauma.

Machine learning models predict triage levels, massive transfusion protocol activation, and mortality in trauma utilizing patients hemodynamics on admission

BACKGROUND

The effective management of trauma patients necessitates efficient triaging, timely activation of Massive Blood Transfusion Protocols (MTP), and accurate prediction of in-hospital outcomes. Machine learning (ML) algorithms have emerged as up-and-coming tools in the domains of optimizing triage decisions, improving intervention strategies, and predicting clinical outcomes, consistently outperforming traditional methodologies. This study aimed to develop, assess, and compare several ML models for the triaging processes, activation of MTP, and mortality prediction.

METHODS

In a 10-year retrospective study, the predictive capabilities of seven ML models for trauma patients were systematically assessed using on-admission patients' hemodynamic data. All patient's data were randomly divided into training (80 %) and test (20 %) sets. Employing Python for data preprocessing, feature scaling, and model development, we evaluated K-Nearest Neighbors (KNN), Logistic Regression (LR), Decision Tree (DT), Support Vector Machines (SVM) with RBF kernels, Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Artificial Neural Network (ANN). We employed various imputation techniques and addressed data imbalance through down-sampling, up-sampling, and synthetic minority for the over-sampling technique (SMOTE). Hyperparameter tuning, coupled with 5-fold cross-validation, was performed. The evaluation included essential metrics like sensitivity, specificity, F1 score, accuracy, Area Under the Receiver Operating Curve (AUC ROC), and Area Under the Precision recall Curve (AUC PR), ensuring robust predictive capability.

RESULT

This study included 17,390 adult trauma patients; of them, 19.5 % (3385) were triaged at a critical level, 3.8 % (664) required MTP, and 7.7 % (1335) died in the hospital. The model's performance improved using imputation and balancing techniques. The overall models demonstrated notable performance metrics for predicting triage, MTP activation, and mortality with F1 scores of 0.75, 0.42, and 0.79, sensitivities of 0.73, 0.82, and 0.9, and AUC ROC values of 0.89, 0.95 and 0.99 respectively.

CONCLUSION

Machine learning, especially RF models, effectively predicted trauma triage, MTP activation, and mortality. Featured critical hemodynamic variables include shock indices, systolic blood pressure, and mean arterial pressure. Therefore, models can do better than individual parameters for the early management and disposition of patients in the ED. Future research should focus on creating sensitive and interpretable models to enhance trauma care.

Time and Risk Factors of Trauma-Related Mortality: A 5-Year Retrospective Analysis From a National Level I Trauma Center

Background: We aimed to analyze in-hospital timing and risk factors for mortality in a level 1 trauma center. Methods: This is a retrospective analysis of all trauma-related mortality between 2013 and 2018. Patients were divided and analyzed based on the time of mortality (early (≤48 h) vs late (>48 h)), and within different age groups. Multivariate regression analysis was performed to predict in-hospital mortality. Results: 8624 trauma admissions and 677 trauma-related deaths occurred (47.7% at the scene and 52.3% in-hospital). Among in-hospital mortality, the majority were males, with a mean age of 35.8 ± 17.2 years. Most deaths occurred within 3-7 days (35%), followed by 33% after 1 week, 20% on the first day, and 12% on the second day of admission. Patients with early mortality were more likely to have a lower Glasgow coma scale, a higher shock index, a higher chest and abdominal abbreviated injury score, and frequently required exploratory laparotomy and massive blood transfusion (P < .005). The injury severity scores and proportions of head injuries were higher in the late mortality group than in the early group. The severity of injuries, blood transfusion, in-hospital complications, and length of intensive care unit stay were comparable among the age groups, whereas mortality was higher in the age group of 19 to 44. The higher proportions of early and late in-hospital deaths were evident in the age group of 24 to 29. In multivariate analysis, the shock index (OR 2.26; 95%CI 1.04-4.925; P = .04) was an independent predictor of early death, whereas head injury was a predictor of late death (OR 4.54; 95%CI 1.92-11.11; P = .001). Conclusion: One-third of trauma-related mortalities occur early after injury. The initial shock index appears to be a reliable hemodynamic indicator for predicting early mortality. Therefore, timely hemostatic resuscitation and appropriate interventions for bleeding control may prevent early mortality.

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

OBJECTIVES

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

METHODS

Trauma patients admitted to Shenzhen University General Hospital from July 2018 to December 2022 were included in this study. They were divided into the massive transfusion group and the non-massive transfusion group according to the blood transfusion volume within 24 h. Basic information about patients was collected. Glasgow Coma Scale (GCS), focused assessment with sonography for trauma (FAST), and injury severity score (ISS) were performed. The receiving operating characteristic (ROC) curve was used to compare the predictive value of four trauma transfusion scores for early massive blood transfusion in the pre-hospital setting.

RESULTS

A total of 475 patients were enrolled, 43 received massive blood transfusions and 29 died within 24 h. The sensitivity and specificity of the four trauma hemorrhage scores in predicting the need for massive blood transfusions in trauma patients at their recommended cutoff points were all high. Among the four scores, the area under the ROC curve was larger for the assessment of blood consumption (ABC) score (0.864) and smaller for the trauma-induced coagulopathy clinical score (TICCS) score (0.795, p > 0.05).

CONCLUSIONS

All four pre-hospital trauma hemorrhage scores have a high predictive value in assessing massive blood transfusion in trauma patients.

Modified physiologic criteria for the field triage scheme: Efficacy of major trauma recognition in different age groups in Asia

BACKGROUND

Major trauma is a leading cause of unexpected death globally, with increasing age-adjusted death rates for unintentional injuries. Field triage schemes (FTSs) assist emergency medical technicians in identifying appropriate medical care facilities for patients. While full FTSs may improve sensitivity, step-by-step field triage is time-consuming. A simplified FTS (sFTS) that uses only physiological and anatomical criteria may offer a more rapid decision-making process. However, evidence for this approach is limited, and its performance in identifying all age groups requiring trauma center resources in Asia remains unclear.

METHODS

We conducted a multinational retrospective cohort study involving adult trauma patients admitted to emergency departments in the included countries from 2016 to 2020. Prehospital and hospital data were reviewed from the Pan-Asia Trauma Outcomes Study database. Patients aged ≥18 years transported by emergency medical services were included. Patients lacking data regarding age, sex, physiological criteria, or injury severity scores were excluded. We examined the performance of sFTS in all age groups and fine-tuned physiological criteria to improve sFTS performance in identifying high-risk trauma patients in different age groups.

RESULTS

The sensitivity and specificity of the physiological and anatomical criteria for identifying major trauma (injury severity score ≥ 16) were 80.6% and 58.8%, respectively. The modified sFTS showed increased sensitivity and decreased specificity, with more pronounced changes in the young age group. Adding the shock index further increased sensitivity in both age groups.

CONCLUSIONS

sFTS using only physiological and anatomical criteria is suboptimal for Asian adult patients with trauma of all age groups. Adjusting the physiological criteria and adding a shock index as a triage tool can improve the sensitivity of severely injured patients, particularly in young age groups. A swift field triage process can maintain acceptable sensitivity and specificity in severely injured patients.

Shock index as predictor of massive transfusion and mortality in patients with trauma: a systematic review and meta-analysis

BACKGROUND

Management of bleeding trauma patients is still a difficult challenge. Massive transfusion (MT) requires resources to ensure the safety and timely delivery of blood products. Early prediction of MT need may be useful to shorten the time process of blood product preparation. The primary aim of this study was to assess the accuracy of shock index to predict the need for MT in adult patients with trauma. For the same population, we also assessed the accuracy of SI to predict mortality.

METHODS

This systematic review and meta-analysis was performed in accordance with the PRISMA guidelines. We performed a systematic search on MEDLINE, Scopus, and Web of Science from inception to March 2022. Studies were included if they reported MT or mortality with SI recorded at arrival in the field or the emergency department. The risk of bias was assessed using the QUADAS-2.

RESULTS

Thirty-five studies were included in the systematic review and meta-analysis, for a total of 670,728 patients. For MT the overall sensibility was 0.68 [0.57; 0.76], the overall specificity was 0.84 [0.79; 0.88] and the AUC was 0.85 [0.81; 0.88]. Positive and Negative Likelihood Ratio (LR+; LR-) were 4.24 [3.18-5.65] and 0.39 [0.29-0.52], respectively. For mortality the overall sensibility was 0.358 [0.238; 0.498] the overall specificity 0.742 [0.656; 0.813] and the AUC 0.553 (confidence region for sensitivity given specificity: [0.4014; 0.6759]; confidence region for specificity given sensitivity: [0.4799; 0.6332]). LR+ and LR- were 1.39 [1.36-1.42] and 0.87 [0.85-0.89], respectively.

CONCLUSIONS

Our study demonstrated that SI may have a limited role as the sole tool to predict the need for MT in adult trauma patients. SI is not accurate to predict mortality but may have a role to identify patients with a low risk of mortality.

The European guideline on management of major bleeding and coagulopathy following trauma: sixth edition

BACKGROUND

Severe trauma represents a major global public health burden and the management of post-traumatic bleeding continues to challenge healthcare systems around the world. Post-traumatic bleeding and associated traumatic coagulopathy remain leading causes of potentially preventable multiorgan failure and death if not diagnosed and managed in an appropriate and timely manner. This sixth edition of the European guideline on the management of major bleeding and coagulopathy following traumatic injury aims to advise clinicians who care for the bleeding trauma patient during the initial diagnostic and therapeutic phases of patient management.

METHODS

The pan-European, multidisciplinary Task Force for Advanced Bleeding Care in Trauma included representatives from six European professional societies and convened to assess and update the previous version of this guideline using a structured, evidence-based consensus approach. Structured literature searches covered the period since the last edition of the guideline, but considered evidence cited previously. The format of this edition has been adjusted to reflect the trend towards concise guideline documents that cite only the highest-quality studies and most relevant literature rather than attempting to provide a comprehensive literature review to accompany each recommendation.

RESULTS

This guideline comprises 39 clinical practice recommendations that follow an approximate temporal path for management of the bleeding trauma patient, with recommendations grouped behind key decision points. While approximately one-third of patients who have experienced severe trauma arrive in hospital in a coagulopathic state, a systematic diagnostic and therapeutic approach has been shown to reduce the number of preventable deaths attributable to traumatic injury.

CONCLUSION

A multidisciplinary approach and adherence to evidence-based guidelines are pillars of best practice in the management of severely injured trauma patients. Further improvement in outcomes will be achieved by optimising and standardising trauma care in line with the available evidence across Europe and beyond.

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.

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.

Early Mortality Risk in Acute Trauma Patients: Predictive Value of Injury Severity Score, Trauma Index, and Different Types of Shock Indices

Objective: This study aimed to explore the predictive value of the Injury Severity Score (ISS), Trauma Index (TI) and different types of shock indices (SI) on the early mortality risk of acute trauma patients. Methods: Clinical data of acute trauma patients who met the inclusion and exclusion criteria of this study and were treated in the hospital from January 2020 to December 2020 were retrospectively collected, including gender, age, trauma mechanism, severe injury site, ISS, TI, admission vital signs, different types of shock indices (SI), death within 7 days, length of hospital stay, and Glasgow Outcome Score (GOS). The predictive value of the Injury Severity Score, Trauma Index, and different types of shock indices on the risk of early mortality in patients with acute trauma were compared using relevant statistical methods. Results: A total of 283 acute trauma patients (mean age 54.0 ± 17.9 years, 30.74% female) were included, and 43 (15.19%) of the patients died during 7 days of hospitalization. The admission ISS, TI, SI, MSI, and ASI in the survival group were significantly lower than those in the death group, and the difference was statistically significant (p < 0.05). Meanwhile, different trauma assessment tools included in the study have certain predictive value for early mortality risk of trauma patients. Conclusions: The TI indicates a better capability to predict the risk of early death in patients with acute trauma. As the most sensitive predictor, the SI has the greatest reference value in predicting the risk of early death in patients with traumatic shock.

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 analyze 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 the 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 5,824 studies identified, 5,784 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. Among 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. Among scoring systems for transfusion, the Shock Index and Modified Shock Index had the highest reported sensitivity (96%), whereas the Pre-arrival Model had the highest reported specificity (95%) for MTP activation. Overall, 20 scores were identified as applicable to the prehospital setting, 25 scores were identified as potentially applicable, and 7 scores were identified as 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.

The Utility of the Shock Index for Predicting Survival, Function and Health Status Outcomes in Major Trauma Patients: A Registry-Based Cohort Study

The shock index (SI; heart rate/systolic blood pressure) has been found to predict mortality in trauma patients. The aims of this study were to establish whether the SI improved the prediction of an existing model for both mortality and longer-term outcomes in major trauma patients. In total, 29,574 adult (>15 years) major trauma patients were included from the Victorian State Trauma Registry with a date of injury from July 2009 to June 2019. Outcomes of interest were survival to hospital discharge and function and health status at 6 months post-injury. Survival and function were analysed using measures of discrimination and calibration, whereas health status was assessed with R2 and MRSE measures. The area under the receiver operating characteristic curve (AUC) of the VSTR survival model improved when the SI was added (AUC 0.797 (0.787–0.807) versus AUC 0.807 (0.797–0.816), p < 0.001). For the prediction of functional outcome 6 months post-injury, the inclusion of the SI increased the AUC marginally (AUC 0.795 (0.786–0.803) versus AUC 0.799 (0.791–0.807), p < 0.001). When predicting in-hospital mortality and health status 6 months post-injury, including the SI resulted in a slightly better fit to the registry-risk adjustment model. In the future, external validation and the exploration of other models to improve prediction outcomes are warranted.

Comparison of 4 Different Threshold Values of Shock Index in Predicting Mortality of COVID-19 Patients

OBJECTIVE

The object of this study was to examine the accuracy in prehospital shock index (SI) for predicting intensive care unit (ICU) requirement and 30-d mortality among from coronavirus disease 2019 (COVID-19) patients transported to the hospital by ambulance.

METHODS

All consecutive patients who were the age ≥18 y, transported to the emergency department (ED) by ambulance with a suspected or confirmed COVID-19 in the prehospital frame were included in the study. Four different cutoff points were compared (0.7, 0.8, 0.9, and 1.0) to examine the predictive performance of both the mortality and ICU requirement of the SI. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) was used to evaluate each cut-off value discriminatory for predicting 30-d mortality and ICU admission.

RESULTS

The total of 364 patients was included in this study. The median age in the study population was 69 y (range, 55-80 y), of which 196 were men and 168 were women. AUC values for 30-d mortality outcome were calculated as 0.672, 0.674, 0.755, and 0.626, respectively, for threshold values of 0.7, 0.8, 0.9 and 1.0. ICU admission was more likely for the patients with prehospital SI > 0.9. Similarly, the mortality rate was higher in patients with prehospital SI > 0.9.

CONCLUSIONS

Early triage of COVID-19 patients will ensure efficient use of health-care resources. The SI could be a helpful, fast, and powerful tool for predicting mortality status and ICU requirements of adult COVID-19 patients. It was concluded that the most useful threshold value for the shock index in predicting the prognosis of COVID-19 patients is 0.9.

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.

Association between prehospital field to emergency department delta shock index and in-hospital mortality in patients with torso and extremity trauma: A multinational, observational study

Hemorrhage, a main cause of mortality in patients with trauma, affects vital signs such as blood pressure and heart rate. Shock index (SI), calculated as heart rate divided by systolic blood pressure, is widely used to estimate the shock status of patients with hemorrhage. The difference in SI between the emergency department and prehospital field can indirectly reflect urgency after trauma. We aimed to determine the association between delta SI (DSI) and in-hospital mortality in patients with torso or extremity trauma. Patients with DSI >0.1 are expected to be associated with high mortality. This retrospective, observational study used data from the Pan-Asian Trauma Outcomes Study. Patients aged 18–85 years with abdomen, chest, upper extremity, lower extremity, or external injury location were included. Patients from China, Indonesia, Japan, Philippines, Thailand, and Vietnam; those who were transferred from another facility; those who were transferred without the use of emergency medical service; those with prehospital cardiac arrest; those with unknown exposure and outcomes were excluded. The exposure and primary outcome were DSI and in-hospital mortality, respectively. The secondary and tertiary outcome was intensive care unit (ICU) admission and massive transfusion, respectively. Multivariate logistic regression analysis was performed to test the association between DSI and outcome. In total, 21,534 patients were enrolled according to the inclusion and exclusion criteria. There were 3,033 patients with DSI >0.1. The in-hospital mortality rate in the DSI >0.1 and ≤0.1 groups was 2.0% and 0.8%, respectively. In multivariate logistic regression analysis, the DSI ≤0.1 group was considered the reference group. The unadjusted and adjusted odds ratios of in-hospital mortality in the DSI >0.1 group were 2.54 (95% confidence interval [CI] 1.88–3.42) and 2.82 (95% CI 2.08–3.84), respectively. The urgency of traumatic hemorrhage can be determined using DSI, which can help hospital staff to provide proper trauma management, such as early trauma surgery or embolization.

Patterns and Effects of Admission Hyperglycemia and Inflammatory Response in Trauma Patients: A Prospective Clinical Study

BACKGROUND

The constellation of the initial hyperglycemia, proinflammatory cytokines and severity of injury among trauma patients is understudied. We aimed to evaluate the patterns and effects of on-admission hyperglycemia and inflammatory response in a level 1 trauma center. We hypothesized that higher initial readings of blood glucose and cytokines are associated with severe injuries and worse in-hospital outcomes in trauma patients.

METHODS

A prospective, observational study was conducted for adult trauma patients who were admitted and tested for on-admission blood glucose, hemoglobin A1c, interleukin (IL)-6, IL-18 and hs-CRP. Patients were categorized into four groups [non-diabetic normoglycemic, diabetic normoglycemic, diabetic hyperglycemic (DH) and stress-induced hyperglycemic (SIH)]. The inflammatory markers were measured on three time points (admission, 24 h and 48 h). Generalized estimating equations (GEE) were used to account for the correlation for the inflammatory markers. Pearson's correlation test and logistic regression analysis were also performed.

RESULTS

During the study period, 250 adult trauma patients were enrolled. Almost 13% of patients presented with hyperglycemia (50% had SIH and 50% had DH). Patients with SIH were younger, had significantly higher Injury Severity Score (ISS), higher IL-6 readings, prolonged hospital length of stay and higher mortality. The SIH group had lower Revised Trauma Score (p = 0.005), lower Trauma Injury Severity Score (p = 0.01) and lower GCS (p = 0.001). Patients with hyperglycemia had higher in-hospital mortality than the normoglycemia group (12.5% vs 3.7%; p = 0.02). A significant correlation was identified between the initial blood glucose level and serum lactate, IL-6, ISS and hospital length of stay. Overall rate of change in slope 88.54 (95% CI:-143.39-33.68) points was found more in hyperglycemia than normoglycemia group (p = 0.002) for IL-6 values, whereas there was no statistical significant change in slopes of age, gender and their interaction. The initial IL-6 levels correlated with ISS (r = 0.40, p = 0.001). On-admission hyperglycemia had an adjusted odds ratio 2.42 (95% CI: 1.076-5.447, p = 0.03) for severe injury (ISS > 12) after adjusting for age, shock index and blood transfusion.

CONCLUSIONS

In trauma patients, on-admission hyperglycemia correlates well with the initial serum IL-6 level and is associated with more severe injuries. Therefore, it could be a simple marker of injury severity and useful tool for patient triage and risk assessment.

TRIAL REGISTRATION

This study was registered at the ClinicalTrials.gov (Identifier: NCT02999386), retrospectively Registered on December 21, 2016. https://clinicaltrials.gov/ct2/show/NCT02999386 .

Shock index as a prognosticator for emergent surgical intervention and mortality in trauma patients in Johannesburg: A retrospective cohort study

Introduction

Trauma is the leading cause of morbidity and mortality worldwide with exsanguination being the primary preventable cause through early surgical intervention. We assessed two popular trauma scoring systems, injury severity scores (ISS) and shock index (SI) to determine the optimal cut off values that may predict the need for emergent surgical intervention (ESI) and in-hospital mortality.

Methods

A retrospective analysis of patient records from a tertiary hospital's trauma unit for the year 2019 was done. Descriptive statistics, univariate and multivariate logistic regression analyses were performed. Receiver operator characteristic (ROC) curve analysis was conducted and area under the curve (AUC) reported for predicting the need for ESI in all study participants, as well as in patients with penetrating injuries alone, based on continuous variables of ISS, SI or a combination of ISS and SI. The Youdin Index was applied to determine the optimal ISS and SI cut off values.

Results

A total of 1964 patients’ records were included, 89.0% were male and the median age (IQR) was 30 (26–37) years. Penetrating injuries accounted for 65.9% of all injuries. ISS and SI were higher in the ESI group with median (IQR) 11 (10–17) and 0.74 (0.60–0.95), respectively. The overall mortality rate was 4.5%. The optimal cut-off values for ESI and mortality by ISS (AUC) were 9 (0.74) and 12 (0.86) (p = 0.0001), with optimal values for SI (AUC) being 0.72 (0.60), and 0.91 (0.68) (p = 0.0001), respectively.

Conclusion

ISS and SI are significant, independent prognosticators for the need of ESI and in-hospital mortality.

•

The ISS cut-off of 15 for severe trauma may underestimate the severity of trauma within our local South African population.

•

Our study reports an optimal SI cut off value of ≥0.72 for emergency surgical intervention.

•

At an optimal SI cut off of ≥0.91 for in-hospital mortality, the odds of demise were 6.7 times higher.

•

ISS was a stronger predictor than SI of both ESI and in-hospital mortality in our study.

An integrative model using flow cytometry identifies nosocomial infection after trauma

BACKGROUND

Flow cytometry (FCM) is a rapid diagnostic tool for monitoring immune cell function. We sought to determine if assessment of cell phenotypes using standardized FCM could be used to identify nosocomial infection after trauma.

METHODS

Prospective study of trauma patients at a Level I center from 2014 to 2018. Clinical and FCM data were collected within 24 hours of admission. Random forest (RF) models were developed to estimate the risk of severe sepsis (SS), organ space infection (OSI), and ventilator-associated pneumonia (VAP). Variables were selected using backward elimination and models were validated with leave-one-out.

RESULTS

One hundred and thirty-eight patients were included (median age, 30 years [23-44 years]; median Injury Severity Score, 20 (14-29); 76% (105/138) Black; 60% (83/138) gunshots). The incidence of SS was 8.7% (12/138), OSI 16.7% (23/138), and VAP 18% (25/138). The final RF SS model resulted in five variables (RBCs transfused in first 24 hours; absolute counts of CD56- CD16+ lymphocytes, CD4+ T cells, and CD56 bright natural killer [NK] cells; percentage of CD16+ CD56+ NK cells) that identified SS with an AUC of 0.89, sensitivity of 0.98, and specificity of 0.78. The final RF OSI model resulted in four variables (RBC in first 24 hours, shock index, absolute CD16+ CD56+ NK cell counts, percentage of CD56 bright NK cells) that identified OSI with an AUC of 0.76, sensitivity of 0.68, and specificity of 0.82. The RF VAP model resulted in six variables (Sequential [Sepsis-related] Organ Failure Assessment score: Injury Severity Score; CD4- CD8- T cell counts; percentages of CD16- CD56- NK cells, CD16- CD56+ NK cells, and CD19+ B lymphocytes) that identified VAP with AUC of 0.86, sensitivity of 0.86, and specificity of 0.83.

CONCLUSIONS

Combined clinical and FCM data can assist with early identification of posttraumatic infections. The presence of NK cells supports the innate immune response that occurs during acute inflammation. Further research is needed to determine the functional role of these innate cell phenotypes and their value in predictive models immediately after injury.

LEVEL OF EVIDENCE

Prognostic, level III.

A Multicentric, Randomized, Controlled Phase III Study of Centhaquine (Lyfaquin®) as a Resuscitative Agent in Hypovolemic Shock Patients

Introduction

Centhaquine (Lyfaquin^®) showed significant safety and efficacy in preclinical and clinical phase I and II studies.

Methods

A prospective, multicentric, randomized phase III study was conducted in patients with hypovolemic shock, systolic blood pressure (SBP) ≤ 90 mmHg, and blood lactate levels ≥ 2 mmol/L. Patients were randomized in a 2:1 ratio to the centhaquine group (n = 71) or the control (saline) group (n = 34). Every patient received standard of care (SOC) and was followed for 28 days. The study drug (normal saline or centhaquine 0.01 mg/kg) was administered in 100 mL of normal saline infusion over 1 h. The primary objectives were to determine changes (mean through 48 h) in SBP, diastolic blood pressure (DBP), blood lactate levels, and base deficit. The secondary objectives included the amount of fluids, blood products, and vasopressors administered in the first 48 h, duration of hospital stay, time in intensive care units, time on ventilator support, change in acute respiratory distress syndrome (ARDS), multiple organ dysfunction syndrome (MODS), and the proportion of patients with 28-day all-cause mortality.

Results

The demographics of patients and baseline vitals in both groups were comparable. The cause of hypovolemic shock was trauma in 29.4 and 47.1% of control group and centhaquine group patients, respectively, and gastroenteritis in 44.1 and 29.4%, respectively. Shock index (SI) and quick sequential organ failure assessment at baseline were similar in the two groups. An equal amount of fluids and blood products were administered in both groups during the first 48 h of resuscitation. A lesser amount of vasopressors was needed in the first 48 h of resuscitation in the centhaquine group. An increase in SBP from baseline was consistently higher up to 48 h (12.9% increase in area under the curve from 0 to 48 h [AUC_0–48]) in the centhaquine group than in the control group. A significant increase in pulse pressure (48.1% increase in AUC_0–48) in the centhaquine group compared with the control group suggests improved stroke volume due to centhaquine. The SI was significantly lower in the centhaquine group from 1 h (p = 0.032) to 4 h (p = 0.049) of resuscitation. Resuscitation with centhaquine resulted in a significantly greater number of patients with improved blood lactate (control 46.9%; centhaquine 69.3%; p = 0.03) and the base deficit (control 43.7%; centhaquine 69.8%; p = 0.01) than in the control group. ARDS and MODS improved with centhaquine, and an 8.8% absolute reduction in 28-day all-cause mortality was observed in the centhaquine group.

Conclusion

Centhaquine is an efficacious resuscitative agent for treating hypovolemic shock. The efficacy of centhaquine in distributive shock is being explored.

Trial Registration

Clinical Trials Registry, India; ctri.icmr.org.in, CTRI/2019/01/017196; clinicaltrials.gov, NCT04045327.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40265-021-01547-5.

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.

A multicentric, randomized, controlled phase III study of centhaquine (Lyfaquin ® ) as a resuscitative agent in hypovolemic shock patients

INTRODUCTION

Centhaquine (Lyfaquin ^® ) showed significant safety and efficacy in preclinical and clinical phase I and II studies.

METHODS

A prospective, multicentric, randomized phase III study was conducted in patients with hypovolemic shock having systolic blood pressure (SBP) of ≤90 mm Hg and blood lactate levels of ≥2 mmol/L. Patients were randomized in a 2:1 ratio, 71 patients to the centhaquine group and 34 patients to the control (saline) group. Every patient received standard of care (SOC) and was followed for 28 days. The study drug (normal saline or centhaquine (0.01 mg/kg)) was administered in 100 mL of normal saline infusion over 1 hour. The primary objectives were to determine changes (mean through 48 hours) in SBP, diastolic blood pressure (DBP), blood lactate levels, and base deficit. The secondary objectives included the amount of fluids, blood products, vasopressors administered in the first 48 hours, duration of hospital stay, time in ICU, time on the ventilator support, change in patient's Acute Respiratory Distress Syndrome (ARDS), Multiple Organ Dysfunction Syndrome (MODS) scores, and the proportion of patients with 28-day all-cause mortality.

RESULTS

The demographics of patients and baseline vitals in both groups were comparable. Trauma was the cause of hypovolemic shock in 29.41% of control and 47.06% of centhaquine, gastroenteritis in 44.12% of control, and 29.41% of centhaquine patients. An equal amount of fluids and blood products were administered in both groups during the first 48 hours of resuscitation. A lesser amount of vasopressors was needed in the first 48 hours of resuscitation in the centhaquine group. An increase in SBP from the baseline was consistently higher in the centhaquine group than in the control. A significant increase in pulse pressure in the centhaquine group than the control group suggests improved stroke volume due to centhaquine. The shock index was significantly lower in the centhaquine group than control from 1 hour (p=0.0320) till 4 hours (p=0.0494) of resuscitation. Resuscitation with centhaquine had a significantly greater number of patients with improved blood lactate and the base deficit than the control group. ARDS and MODS improved with centhaquine, and an 8.8% absolute reduction in 28-day all-cause mortality was observed in the centhaquine group.

CONCLUSION

Centhaquine is a highly efficacious resuscitative agent for treating hypovolemic shock. The efficacy of centhaquine in distributive shock due to sepsis and COVID-19 is being explored.

TRIAL REGISTRATION

Clinical Trials Registry, India; ctri.icmr.org.in, CTRI/2019/01/017196; clinicaltrials.gov, NCT04045327 .

KEY SUMMARY POINTS

A multicentric, randomized, controlled trial was conducted to evaluate the efficacy of centhaquine in hypovolemic shock patients.One hundred and five patients were randomized 2:1 to receive centhaquine or saline. Centhaquine was administered at a dose of 0.01 mg/kg in 100 mL saline and infused over 1 hour. The control group received 100 mL of saline over a 1-hour infusion.Centhaquine improved blood pressure, shock index, reduced blood lactate levels, and improved base deficit. Acute Respiratory Distress Syndrome (ARDS) and Multiple Organ Dysfunction Syndrome (MODS) score improved with centhaquine.An 8.8% absolute reduction in 28-day all-cause mortality was observed in the centhaquine group. There were no drug-related adverse events in the study.

A prospective cohort study of shock index as a reliable marker to predict the patient's need for blood transfusion due to postpartum hemorrhage

Objective:

This study was aimed to compare the shock index (SI) values between patients who required blood transfusion due to postpartum hemorrhage (PPH) and patients who received no blood transfusion.

Methods:

We conducted this cross-sectional study at a tertiary center between January 2019 and June 2019. A total of 2534 patients who underwent vaginal delivery were included in this study. We measured SI values upon admission, 30 minutes, 1-hour, and 2-hours after delivery. We identified women who required blood transfusion as the study group. Control patients who delivered in the same period and received no blood transfusion were identified in the medical record system and randomly selected. Age, parity, BMI, and SI values at each one prepartum and three postpartum periods of the groups were analyzed.

Results:

A total of 2534 patients were included in the study. A varying amount of blood transfusion was performed in 54 patients (2.13%). When we compared with patients who did not receive blood transfusion after delivery, patients who received any amount of blood transfusion after vaginal delivery had significantly higher SI values 30 minutes after delivery (0.99±0.20, and 085±0.11, p=0.0001), at 1-hour (1.00±0.18, and 0.85±0.11, p=0.0001), and 2-hours (1.09±0.16, and 0.87±0.11, p=0.0001).

Conclusion:

SI value could be a reliable and consistent marker to predict the requirement for any amount of blood transfusion due to PPH.

Should we change our approach to resuscitating victims of femoral fracture? A clinical experience in a busy trauma hospital in Shiraz, Iran

PURPOSE

Traumatic hemorrhagic shock is a life-threatening event worldwide. Severe brain trauma accompanying femoral fractures can trigger inflammatory responses in the body and increase pre-inflammatory cytokines such as TNF-α, IL-1. The primary treatment in these cases is hydration with crystalloids, which has both benefits and complications. The purpose of this study was to investigate the effects of fluid therapy on the hemodynamics, coagulation profiles, and blood gases in such patients.

METHODS

In this cross-sectional study, patients were divided into two groups: femoral fracture group and non-femoral group. The hemodynamic status, coagulation profile, and blood gases of patients in both groups were evaluated upon arrival at the hospital and again 2 h later. Data were analyzed by t-test and ANOVA with repeated data and paired samples t-test.

RESULTS

A total of 681 trauma patients (605 men and 76 women) participated in this study, including 69 (86.3%) men and 11 (13.8%) women in femoral fracture group and 536 men (89.2%) and 65 women (10.8%) in non-femoral group. The laboratory parameters were evaluated in response to the equal amount of crystalloid fluid given upon arrival and 2 h later. Blood gases decreased in the fracture group despite fluid therapy (p < 0.003), and the coagulation profile worsened although the change was not statistically significant.

CONCLUSION

The treatment of multiple-trauma patients with femoral bone fractures should be more concerned with the need for the infusion of vasopressors such as norepinephrine. If there is evidence of clinical shock, excessive crystalloid infusion (limited to 1 L) should be avoided, and blood and blood products should be started as soon as possible.

Dynamic trend or static variable: Shock Index Pediatric-Adjusted (SIPA) in warzone trauma

BACKGROUND

Civilian studies suggest that trending Shock-Index Pediatric Adjusted(SIPA) values can prove useful in the prediction of trauma outcomes. The purpose of this study was to evaluate the relationship between trends in SIPA and outcomes in pediatric warzone trauma.

METHODS

Retrospective review of the Department of Defense Trauma Registry from 2008 to 2015, including all patients age ≤17years. SIPA was calculated both pre-hospital and upon arrival, then classified as "normal" or "abnormal" based upon previously validated thresholds. Patients were stratified into groups based on the trend of their SIPA (1-normal to normal, 2-normal to abnormal, 3-abnormal to normal, 4-abnormal to abnormal). Key outcomes including ICU admission, severe injury, mechanical ventilation, and mortality were then compared between groups.

RESULTS

669 patients were included, mean ISS 12 ± 10. The most common mechanism of injury was blast (46.5%). Overall, 43% were stratified into Group 1, 13.9% into Group 2, 14.8% into Group 3, and 28.0% into Group 4. Those patients with a persistently abnormal SIPA (Group 4) had significantly increased incidence of severe injury, ICU admission, need for mechanical ventilation, and mortality.

CONCLUSION

Trends in SIPA may be used to predict trauma outcomes for children injured in warzones, with persistently abnormal values associated with worse outcomes overall.

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.

Shock index is associated with mortality in canine vehicular trauma patients

OBJECTIVE

To calculate and compare shock index (SI) in healthy dogs and vehicular trauma dogs (VT), determine the prognostic value of SI in VT dogs, and to assess the correlation between SI and the animal trauma triage score, modified Glasgow Coma Scale score, and lactate in VT dogs.

DESIGN

Retrospective study from April 2016 to February 2018.

SETTING

Twenty-four-hour tertiary referral level II trauma center.

ANIMALS

One hundred twenty-one dogs presented to the emergency service for VT and 60 healthy control dogs.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Heart rate and systolic blood pressure were measured on each patient and used to calculate SI. SI was significantly higher in VT dogs compared to healthy control dogs (median SI, 1.0 vs 0.75; P < 0.0001). SI was significantly higher in those that died versus those that survived to discharge (median, 1.27 vs 0.96; P = 0.017). SI positively correlated with animal trauma triage score (95% confidence interval, 0.039-0.49; P = 0.019; r = 0.26) but did not with plasma lactate level at presentation (P = 0.068; r = 0.22) or modified Glasgow Coma Scale (P = 0.85; r = -0.021, 95% confidence interval, -0.24 to 0.20).

CONCLUSIONS

SI is easy to calculate during triage of a trauma patient. Given its significant relationship with mortality, higher SIs should prompt the clinician to pursue additional monitoring, diagnostics, and intervention.

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

BACKGROUND

Uncontrolled bleeding is the main cause of the potential preventable death in trauma patients. Accordingly, we reviewed all the existing scores for massive transfusion posttraumatic hemorrhage and summarized their characteristics, thus making it easier for the reader to have a global view of these scores-how they were created, their accuracy and to which population they apply.

METHODS

A narrative review with a systematic search method to retrieve the journal articles on the predictive scores or models for massive transfusion was carried out. A literature search using PubMed, SCOPUS, and Google scholar was performed using relevant keywords in different combinations. The keywords used were "massive transfusion," "score," "model," "trauma," and "hemorrhage" in different combinations. The search was limited for full-text articles published in English language, human species and for the duration from January 1, 1998 to November 30, 2018.

RESULTS

The database search yielded 295 articles. The search was then restricted to the inclusion criteria which retrieved 241 articles. Duplicates were removed and full-texts were assessed for the eligibility to include in the review which resulted in inclusion of 24 articles. These articles identified 24 scoring systems including modified or revised scores. Different models and scores for identifying patients requiring massive transfusion in military and civilian settings have been described. Many of these scorings were complex with difficult calculation, while some were simple and easy to remember.

CONCLUSIONS

The current prevailing practice that is best described as institutional or provider centered should be supplemented with score-based protocol with auditing and monitoring tools to refine it. This review summarizes the current scoring models in predicting the need for MT in civilian and military trauma. Several questions remain open; i.e., do we need to develop new score, merge scores, modify scores, or adopt existing score for certain trauma setting?

Patterns, management, and outcomes of traumatic pelvic fracture: insights from a multicenter study

Background

Traumatic pelvic fracture (TPF) is a significant injury that results from high energy impact and has a high morbidity and mortality.

Purpose

We aimed to describe the epidemiology, incidence, patterns, management, and outcomes of TPF in multinational level 1 trauma centers.

Methods

We conducted a retrospective analysis of all patients with TPF between 2010 and 2016 at two trauma centers in Qatar and Germany.

Results

A total of 2112 patients presented with traumatic pelvic injuries, of which 1814 (85.9%) sustained TPF, males dominated (76.5%) with a mean age of 41 ± 21 years. In unstable pelvic fracture, the frequent mechanism of injury was motor vehicle crash (41%) followed by falls (35%) and pedestrian hit by vehicle (24%). Apart from both extremities, the chest (37.3%) was the most commonly associated injured region. The mean injury severity score (ISS) of 16.5 ± 13.3. Hemodynamic instability was observed in 44%. Blood transfusion was needed in one third while massive transfusion and intensive care admission were required in a tenth and a quarter of cases, respectively. Tile classification was possible in 1228 patients (type A in 60%, B in 30%, and C in 10%). Patients with type C fractures had higher rates of associated injuries, higher ISS, greater pelvis abbreviated injury score (AIS), massive transfusion protocol activation, prolonged hospital stay, complications, and mortality (p value < 0.001). Two-thirds of patients were managed conservatively while a third needed surgical fixation. The median length of hospital and intensive care stays were 15 and 5 days, respectively. The overall mortality rate was 4.7% (86 patients).

Conclusion

TPF is a common injury among polytrauma patients. It needs a careful, systematic management approach to address the associated complexities and the polytrauma nature.

Vital sign thresholds predictive of death in the combat setting

INTRODUCTION

Identifying patients at imminent risk of death is a paramount priority in combat casualty care. This study measures the vital sign values predictive of mortality among combat casualties in Iraq and Afghanistan.

METHODS

We used data from the Department of Defense Trauma Registry from January 2007 to August 2016. We used the highest documented heart rate and the lowest documented systolic pressure in the emergency department for each casualty. We constructed receiver operator curves (ROCs) to assess the accuracy of these variables for predicting survival to hospital discharge.

RESULTS

There were 38,769 encounters of which our dataset included 15,540 (40.1%). The median age of these patients was 25 years and 97.5% were male. The most common mechanisms of injury were explosives (n = 9481, 61.0%) followed by gunshot wounds (n = 2393, 15.3%). The survival rate to hospital discharge was 97.5%. The median heart rate was 94 beats per minute (bpm) with area under the ROC of 0.631 with an optimal threshold to predict mortality of 110 bpm (sensitivity 52.2%, specificity 79.2%). The median systolic blood pressure was 128 mmHg with area under the ROC of 0.790 with an optimal threshold to predict mortality of 112 mmHg (sensitivity 68.5%, specificity 81.5%).

CONCLUSIONS

Casualties with a systolic blood pressure <112 mmHg, are at high risk of mortality, a value significantly higher than the traditional 90 mmHg threshold. Our dataset highlights the need for better methods to guide resuscitation as vital sign measurements have limited accuracy in predicting mortality.

Prediction of perioperative transfusions using an artificial neural network

BACKGROUND

Accurate prediction of operative transfusions is essential for resource allocation and identifying patients at risk of postoperative adverse events. This research examines the efficacy of using artificial neural networks (ANNs) to predict transfusions for all inpatient operations.

METHODS

Over 1.6 million surgical cases over a two year period from the NSQIP-PUF database are used. Data from 2014 (750937 records) are used for model development and data from 2015 (885502 records) are used for model validation. ANN and regression models are developed to predict perioperative transfusions for surgical patients.

RESULTS

Various ANN models and logistic regression, using four variable sets, are compared. The best performing ANN models with respect to both sensitivity and area under the receiver operator characteristic curve outperformed all of the regression models (p < .001) and achieved a performance of 70-80% specificity with a corresponding 75-62% sensitivity.

CONCLUSION

ANNs can predict >75% of the patients who will require transfusion and 70% of those who will not. Increasing specificity to 80% still enables a sensitivity of almost 67%. The unique contribution of this research is the utilization of a single ANN model to predict transfusions across a broad range of surgical procedures.

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.

The Extremity/Mechanism/Shock Index/GCS (EMS-G) score: A novel pre-hospital scoring system for early and appropriate MTP activation

BACKGROUND

Numerous in-hospital scoring systems to activate massive transfusion protocols (MTP) have been proposed; however, to date, pre-hospital scoring systems have not been robustly validated. Many trauma centers do not have blood or pre-thawed plasma available in the trauma bay, leading to delays in balanced transfusion. This study aims to assess pre-hospital injury and physiologic parameters to develop a pre-hospital scoring system predictive of need for massive transfusion (MT) prior to patient arrival.

METHODS

A retrospective review of all adult full and partial trauma team activations from July 2014-July 2018 from an urban level 2 trauma center was performed utilizing our trauma registry. Stepwise logistic regression analysis was performed to develop a new scoring system, with point totals assigned proportional to the odds ratios of requiring MT for each variable. Internal validation of the EMS-G score was performed using a subset of the data which was not utilized for development of the scoring system, and sensitivity and specificity were compared to previously validated in-hospital scoring systems applied in the pre-hospital setting.

RESULTS

763 patients were included with 94 patients (12.3%) receiving early MT, defined as 4 units pRBC in 4 h or ED death. In-hospital models for predicting MT such as Assessment of Blood Consumption (ABC) or Shock Index (SI) have sensitivities and specificities of 46/85% and 94/79% respectively for early MTP utilization based on pre-hospital data. Pre-hospital variables found to be predictive of MT were used to develop the EMS-G (Extremity, Mechanism, Shock Index, GCS) score. This system assigns obvious extremity injury-1-point, penetrating mechanism -2 points, shock index ≥0.9-2 points, GCS ≤8-3 points. A score of 3 or greater was chosen to maximize sensitivity and specificity for pre-hospital MT activation. EMS-G score based on pre-hospital report is 89% sensitive, 84% specific, with a PPV of 44% and NPV of 98% for early MT. Using this system, 25% of full and partial trauma team activations met criteria for pre-hospital MTP activation.

CONCLUSION

The EMS-G Score has increased sensitivity and specificity compared to the ABC Score in the pre-hospital setting and appears more appropriate than shock index alone at predicting massive transfusion. This scoring system allows trauma centers to activate MTP prior to patient arrival to ensure early and appropriate blood product administration without blood product wastage.

Bio-Shock Index: Proposal and Rationale for a New Predictive Tool for In-Hospital Mortality in Patients with Traumatic Brain Injury

BACKGROUND

We proposed a novel prognostic tool for the prediction of in-hospital mortality based on a combination of hemodynamic parameters and biomarkers in patients with traumatic brain injury (TBI). We hypothesized that a combination of shock index (SI) with high sensitive troponin T (HsTnT), the Bio-Shock Index (Bio-SI), has better prognostic power than its individual components.

METHODS

A retrospective chart review was conducted (2011-2018) for patients with TBI. Patients were categorized into 2 groups (low and high Bio-SI) based on the receiver operating characteristic curve.

RESULTS

A total of 2619 patients were admitted with TBI, and 1471 fulfilled the inclusion criteria and 73% had high Bio-SI (≥10). High Bio-SI values were associated with more intraventricular hemorrhage (P = 0.001), brain edema (P = 0.001), and had lower mean arterial pressure (P = 0.001), admission Glasgow Coma Scale score (P = 0.001), and higher SI (P = 0.001), serum lactate (P = 0.001), HsTnT values (P = 0.001), and Rotterdam score (P = 0.03). Patients with high Bio-SI had a prolonged hospital (P = 0.003) and intensive care unit stay (P = 0.001); longer ventilatory days (P = 0.001) and had higher rates of pneumonia (P = 0.001), sepsis (P = 0.001), and in-hospital mortality (P = 0.001). The Bio-SI showed high sensitivity and negative predictive value (91.4% and 94.4%, respectively) as compared with elevated SI (50.2% and 87.6%, respectively) and positive troponin (79.7% and 93.7%, respectively).

CONCLUSIONS

The Bio-SI is potentially a better tool than its individual components to predict in-hospital mortality among patients with TBI; however, HsTnT alone outperforms SI. Prospective studies and multicenter trials studying troponin levels and SI in all patients with TBI with the inclusion of outcome scores will prove or disprove the predictability of the new index.

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.

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.

Developing a Simple Clinical Score for Predicting Mortality and Need for ICU in Trauma Patients

Several models exist to predict trauma center need in the prehospital setting; however, there is lack of simple clinical tools to predict the need for ICU admission and mortality in trauma patients. The aim of our study was to develop a simple clinical tool that can be used with ease in the prehospital or emergency setting and can reliably predict the need for ICU admission and mortality in trauma patients. We abstracted one year of National Trauma Data Bank for all patients aged ≥ 18 years. Transferred patients and those dead on arrival were excluded. Patient demographics, injury parameters, vital signs, and Glasgow Coma Scale (GCS) were recorded. Our primary outcome measures were mortality and ICU admission. Logistic regression analysis was performed using three variables (age > 55 years, shock index (SI) > 1, and GCS score) to determine the appropriate weights for predicting mortality. Appropriate weights derived from regression analysis were used to construct a simple SI, age, and GCS (SAG) score, and associated mortality and ICU admissions were calculated for three different risk groups (low, intermediate, and high). A total of 281,522 patients were included. The mean age was 47 ± 20 years, and 65 per cent were male. The overall mortality rate was 2.9 per cent, and the rate of ICU admission was 28.7 per cent. The SAG score was constructed using weights derived from regression analysis for age ≤ 55 years (4 points), SI< 1 (3 points), and GCS (3-15 points). The median [IQR] SAG score was 21 [18–22]. The area under the receiver operating curve [95% Confidence Interval (CI)] of the SAG score for predicting mortality and ICU admission was 0.873 [0.870–0.877] and 0.644 [0.642–0.647], respectively. Each 1-point increase in the SAG score was associated with 18 per cent lower odds of mortality (odds ratio [95% CI]: 0.822 [0.820–0.825]) and 10 per cent lower odds of ICU admission (odds ratio [95% CI]: 0.901 [0.899–0.902]). The SAG score is a simple clinical tool derived from variables that can be assessed with ease during the initial evaluation of trauma patients. It provides a rapid assessment and can reliably predict mortality and need for ICU admission in trauma patients. This simple tool may allow early resource mobilization possibly even before the arrival of the patient.

Shock Index in Patients Presenting With Acute Heart Failure: A Multicenter Multinational Observational Study

Shock index (SI) has a prognostic role in coronary heart disease; however, data on acute heart failure (AHF) are lacking. We evaluated the predictive values of SI in patients with AHF. Data were retrospectively analyzed from the Gulf Acute Heart Failure Registry. Patients were categorized into low SI versus high SI based on the receiver operating characteristic curves. Primary outcomes included cardiogenic shock (CS) and mortality. Among 4818 patients with AHF, 1143 had an SI ≥0.9. Compared with SI <0.9, patients with high SI were more likely males, younger, and having advanced New York Heart Association class, fewer cardiovascular risk factors and less prehospital β-blockers and angiotensin-converting enzyme inhibitor use. Shock index had significant negative correlations with age, pulse pressure, mean arterial pressure, and left ventricle ejection fraction and had positive correlation with hospital length of stay. Shock index ≥0.9 was significantly associated with higher composite end points, in-hospital, and 3-month mortality. Shock index ≥0.9 had 96% negative predictive value (NPV) and 3.5 relative risk for mortality. Multivariate regression analysis showed that SI was independent predictor of mortality and CS. With a high NPV, SI is a simple reliable bedside tool for risk stratification of patients with AHF. However, this conclusion needs further support.

Prehospital administration of tranexamic acid in trauma patients: A 1:1 matched comparative study from a level 1 trauma center

PURPOSE

The purpose of this study was to test the efficacy of prehospital administration of tranexamic acid (TXA) to injured patients on mortality, thromboembolic events and need for blood transfusion in a level 1 trauma center.

METHODS

We conducted a retrospective study comparing adult trauma patients receiving or not receiving prehospital TXA between January 2017 and September 2018. Patients not receiving TXA but transfused within 4 h of admission were 1:1 matched to TXA-treated patients for age, sex, injury severity score, head abbreviated injury score, prehospital heart rate and systolic blood pressure.

RESULTS

In total 204 patients were included (102 TXA and 102 control), with a mean age of 31 years. On admission, shock index (p = 0.03) and serum lactate (p = 0.001) were greater in the control group, whereas the initial base deficit, hemoglobin levels and EMS time were comparable in both groups. The odd ratio (OR) for shock index ≥0.9 after TXA administration was 0.44 (95% CI 0.23-0.84). The median amount of blood transfusion was greater in the control group [eight units (range 1-40) vs three (range 0-40), p = 0.01] as well as the use of massive blood transfusion [OR 0.35 (95% CI 0.19-0.67)]. In the TXA group, VTE was higher [OR 2.0 (95% CI 0.37-11.40)]; whereas the overall mortality was lower [OR 0.78 (95% CI 0.42-1.45)] without reaching statistical significance.

CONCLUSIONS

Prehospital TXA administration is associated with less in-hospital blood transfusion and massive transfusion protocol (MTP). There is no significant increase in the thromboembolic events and mortality, however, further evaluation in larger clinical trials is needed.