Admission In Trauma Patients Research Articles

Does a given abbreviated injury scale value in different body regions contribute to the same risks of in-hospital mortality and ICU admission in trauma patients?

Objective: We aimed to investigate the hypothesis that identical abbreviated injury scale (AIS) scores may lead to varying risks of in-hospital mortality and admission to the intensive care unit (ICU) depending on the specific body region affected. Methods: This study focused on hospitalized trauma patients with moderate to serious injuries (AIS=2, 3). The final sample was stratified based on the injured body regions. To determine the impact of these injuries on mortality and ICU admission, we conducted binary logistic regression after adjusting for confounding factors. Results: Overall, 16,040 trauma patients with moderate injury (AIS=2) and 1,338 trauma patients with serious injury (AIS=3) were included in this study. When comparing outcome of trauma patients in different body region, there was no significant difference in the odds of two main outcomes in various injury sites, except for extremities (P values>0.05). When the AIS=2 patients were controlled for confounding factors, the adjusted odds of mortality were significantly higher for head, face, and neck injuries, as well as spine/back, thoracic, and abdominal injuries, compared to extremity injuries (adjusted odds ratio (aOR)s=9.81,8.78, 8.11, and 3.96, respectively; P-values<0.05). Among those with AIS=3, the odds of mortality were significantly greater for abdominal (aOR=7.05, P-value=0.009) and head, face, and neck injuries (aOR=2.73, P-value=0.001) than for extremity injuries. Conclusion: Injuries with the same AIS (=2, 3) value almost indistinguishably confer the same mortality risk and ICU admission, except for extremities. The unique AIS value assigned to various body sites almost consistently indicate the same likelihood of negative outcomes.

Predictors of clinical deterioration and intensive care unit admission in trauma patients transferred from northern Quebec to a level 1 trauma centre: a retrospective cohort study.

Trauma care in Nunavik, Quebec, is highly challenging. Geographic distances and delays in transport can translate into precarious patient transfers to tertiary trauma care centres. The objective of this study was to identify predictors of clinical deterioration during transport and eventual intensive care unit (ICU) admission for trauma patients transferred from Nunavik to a tertiary trauma care centre. This is a retrospective cohort study using the Montreal General Hospital (MGH) trauma registry. All adult trauma patients transferred from Nunavik and admitted to the MGH from 2010 to 2019 were included. Main outcomes of interest were hemodynamic and neurologic deterioration during transport and ICU admission. In total, 704 patients were transferred from Nunavik and admitted to the MGH during the study period. The median age was 33 (interquartile range [IQR] 23-47) years and the median Injury Severity Score was 10 (IQR 5-17). On multiple regression analysis, transport time from site of injury to the MGH (odds ratio [OR] 1.04, 95% confidence interval [CI] 1.01-1.06), thoracic injuries (OR 1.75, 95% CI 1.03-2.99), and head and neck injuries (OR 3.76, 95% CI 2.10-6.76) predicted clinical deterioration during transfer. Injury Severity Score (OR 1.04, 95% CI 1.01-1.08), abnormal local Glasgow Coma Scale score (OR 2.57, 95% CI 1.34-4.95), clinical deterioration during transfer (OR 4.22, 95% CI 1.99-8.93), traumatic brain injury (OR 2.44, 95% CI 1.05-5.68), and transfusion requirement at the MGH (OR 4.63, 95% CI 2.35-9.09) were independent predictors of ICU admission. Our study identified several predictors of clinical deterioration during transfer and eventual ICU admission for trauma patients transferred from Nunavik. These factors could be used to refine triage criteria in Nunavik for more timely evacuation and higher level care during transport.

Performance of severity indices for admission and mortality of trauma patients in the intensive care unit: a retrospective cohort study

BackgroundLittle is known about the performance of severity indices for indicating intensive care and predicting mortality in the Intensive Care Unit (ICU) of trauma patients. This study aimed to compare the performance of severity indices to predict trauma patients’ ICU admission and mortality.MethodsA retrospective cohort study which analyzed the electronic medical records of trauma patients aged ≥ 18 years, treated at a hospital in Brazil, between 2014 and 2017. Physiological [Revised Trauma Score (RTS), New Trauma Score (NTS) and modified Rapid Emergency Medicine Score (mREMS)], anatomical [Injury Severity Score (ISS) and New Injury Severity Score (NISS)] and mixed indices [Trauma and Injury Severity Score (TRISS), New Trauma and Injury Severity Score (NTRISS), Base-deficit Injury Severity Score (BISS) and Base-deficit and New Injury Severity Score (BNISS)] were compared in analyzing the outcomes (ICU admission and mortality) using the Area Under the Receiver Operating Characteristics Curves (AUC–ROC).ResultsFrom the 747 trauma patients analyzed (52.5% female; mean age 51.5 years; 36.1% falls), 106 (14.2%) were admitted to the ICU and 6 (0.8%) died in the unit. The ISS (AUC 0.919) and NISS (AUC 0.916) had better predictive capacity for ICU admission of trauma patients. The NISS (AUC 0.949), TRISS (AUC 0.909), NTRISS (AUC 0.967), BISS (AUC 0.902) and BNISS (AUC 0.976) showed excellent performance in predicting ICU mortality.ConclusionsAnatomical indices showed excellent predictive ability for admission of trauma patients to the ICU. The NISS and the mixed indices had the best performances regarding mortality in the ICU.

Comparative study of the diagnostic power of full outline of unresponsiveness score and Glasgow coma scale in patients with traumatic brain injury in an emergency department

Background: The Glasgow coma scale (GCS) is the most commonly used scale, and the full outline of unresponsiveness (FOUR) score is new validated coma scale as an alternative to GCS to measure the level of consciousness and evaluate the severity of the injury in traumatic brain injury (TBI) patients. Aims and Objectives: The present study compared the performance of FOUR scores and GCS in outcome predictions of TBI cases. Materials and Methods: This prospective and cross-sectional study was conducted over a year by the Emergency Department of a tertiary care hospital, Kovai Medical Center and Hospital, Coimbatore, India. Of 159, 123 patients were recruited from intensive care unit (ICU), and 36 from the ward were included in this study. Data were collected using an observation checklist to determine the similarities and differences in predicting outcomes using the two assessment scales (GCS and FOUR). Results: Most patients were 51–60 years (38%), with a mean age of 41.57. About 82% were male, 18% were female, and 31% had comorbidity of hypertension. Data analysis showed a significant statistical difference in mean FOUR and GCS scores between ICU and ward admission. A multivariate logistic regression study revealed that the probability of ICU admission in trauma patients from the emergency department was associated with a decline in GCS and FOUR scores. The range of predicted ICU admission was similar in both GCS and FOUR score models. Conclusion: Although both scores are good predictors of TBI patients, we concluded that the FOUR score is a recommended predictive model for patients admitted to the medical ICU.

Importance of the neutrophil‑to‑lymphocyte ratio as a prognostic factor in patients with spleen trauma: A single center experience.

Abdominal trauma is a common diagnosis for patients admitted to the emergency room. Evaluation of the severity of such patients can sometimes be difficult due to rapid hemodynamic changes caused by the activation of inflammatory and anti-inflammatory regulatory mechanisms. To evaluate the prognosis of trauma patients, it is crucial to identify these changes and adapt various treatment strategies. Using the records of the Mures County Emergency Clinical Hospital, 126 patients were included in the present study with traumatic splenic injury admitted over 6 years. Blood parameters such as the neutrophil, lymphocyte, and platelet counts, the neutrophil to lymphocyte ratio (NLR), and the platelet to lymphocyte ratio (PLR) were determined, and the association between these and the severity of the traumatic injury [quantified as the injury severity score (ISS)] was calculated. We used linear and multiple regression analyses to identify and quantify the relationships. We found statistically significant associations between the ISS and the NLR (P=0.002), with an AUC of 0.816 and a cut-off value of NLR=6.075 (sensitivity=76.7%, specificity=74.3%), and between the ISS and hemoglobin (P<0.0001), hematocrit (P<0.0001), neutrophil count (P<0.0001), lymphocyte count (P=0.0224), and platelet count (P=0.0163). No association was found between the PLR and the severity of trauma. An elevated NLR at admission in trauma patients had significant predictive power for the severity of trauma. Patients with an NLR greater than the cut-off value of 6.075 were more likely to have suffered serious injuries and undergone deterioration.

Evaluation of the Nelson Criteria as an Indicator for Nonsurgical Admission in Trauma Patients.

Geriatric patients with complex medical comorbidities who sustain minor injuries may warrant admission to nonsurgical services. The Nelson score provides an objective scoring system that helps identify patients appropriate for nonsurgical admission (NSA). The purpose of this study is to assess the utility of the Nelson criteria in determining the most appropriate admission service. A retrospective review was performed on patients ≥65 years admitted from 12/2016 to 11/2020. 2410 patients met the inclusion criteria. Patients with Nelson score ≥6 were older with more comorbidities, had a lower injury severity score (7.5 vs 12.5, p<0.0001), and a higher rate of NSA (29.2% vs 12.7%, p<0.0001) compared to patients with Nelson score <6. On the multivariable logistic regression, admission service was not identified as an independent predictor of mortality. Utilizing the Nelson criteria may provide an objective measure to stratify and identify patients who would benefit from NSA.

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

The primary aim was to determine whether a shock index (SI) ≥ 1 in adult trauma patients was associated with increased in-hospital mortality compared to an SI < 1. This systematic review including a meta-analysis was performed in accordance with the PRISMA guidelines. EMBASE, MEDLINE, and Cochrane Library were searched, and two authors independently screened articles, performed the data extraction, and assessed risk of bias. Studies were included if they reported in-hospital, 30-day, or 48-h mortality, length of stay, massive blood transfusion or ICU admission in trauma patients with SI recorded at arrival in the emergency department or trauma center. Risk of bias was assessed using the Newcastle-Ottawa Scale, and the strength and quality of the body of evidence according to GRADE. Data were pooled using a random effects model. Inter-rater reliability was assessed with Cohen's kappa. We screened 1350 citations with an inter-rater reliability of 0.90. Thirty-eight cohort studies were included of which 14 reported the primary outcome. All studies reported a significant higher in-hospital mortality in adult trauma patients with an SI ≥ 1 compared to those having an SI < 1. Twelve studies involving a total of 348,687 participants were included in the meta-analysis. The pooled risk ratio (RR) of in-hospital mortality was 4.15 (95% CI 2.96-5.83). The overall quality of evidence was low. This systematic review found a fourfoldincreased risk of in-hospital mortality in adult trauma patients with an initial SI ≥ 1 in the emergency department or trauma center.

Effect of the COVID-19 pandemic at a major Danish trauma center in 2020 compared with 2018-2019: A retrospective cohort study.

BackgroundThe COVID‐19 pandemic demanded changes in societal behavior and health care worldwide. Previous studies have compared trauma patient admissions in COVID‐19‐related lockdowns to prior years. This study describes the COVID‐19 impact on trauma patient admissions during entire 2020 at a major trauma center in Denmark.MethodsWe retrospectively analyzed trauma patients received by a trauma team and admitted at Aarhus University Hospital in 2020 compared with 2018–2019. The incidence of injuries, mechanism of injury, 30‐day mortality, and Injury Severity Score (ISS) were investigated.ResultsThe incidence of minor injuries (ISS 1–15) increased by 24% in 2020 compared with 2018–2019 (incidence rate ratio 1.24 [95% CI: 1.11–1.39]). The incidence of severe injuries (ISS >15) in 2020 did not change compared with 2018–2019 (incidence rate ratio 0.97 [95% CI: 0.80–1.17]). The 30‐day mortality was similar in 2020 compared with 2018–2019. Comparing 2020 with 2018–2019, the risk ratio of traffic injuries decreased (0.90 [95% CI: 0.82–0.99]), risk ratio for fall injuries was 1.13 (95% CI: 0.97–1.30), for violence 1.13 (95% CI: 0.51–2.50), and for self‐harm 1.94 (95% CI: 0.95–3.94). During the first lockdown of 2020, trauma team activations declined from 49.5 to 42 and the risk ratio for traffic injuries was 0.74 (95% CI: 0.50–1.10) compared with the same period in 2018–2019.ConclusionThe incidence of minor injuries increased, but the incidence of severe injuries was similar in 2020 compared with 2018–2019. Societal restrictions might alter the mechanism of injuries. The first lockdown indicated an association with reduced traffic injuries.

Defining Risk and Risk Factors for Unplanned ICU Admission of Trauma Patients

Unplanned ICU admissions (up-ICUad) are associated with poor outcomes. It is difficult to identify who is at risk for up-ICUad in trauma patients. This study aimed to identify injury patterns and comorbidities associated with up-ICUad and develop a predictive tool for who is at risk. A retrospective study compared trauma patients admitted to the floor who experienced an up-ICUad to similar patients without an up-ICUad. Univariate analysis and multivariate logistic regression identified independent risk factors associated with up-ICUad. Based on those factors, a Risk Score (RS) was created and compared between the two groups. 2.15% of the 7206 patients experienced an up-ICUad. The up-ICUad group was older, experienced longer length of stay, and had higher mortality. Age, congestive heart failure, COPD, peptic ulcer disease, mild liver disease, CKD, and significant injuries to the thorax, spine, and lower extremities were independently associated with up-ICUad. A RS equation was created and was used for each patient. Trauma patients are at increased risk for up-ICUad based on specific factors. These factors can be used to calculate a RS to determine who is at greatest risk for an up-ICUad which may be helpful for preventing up-ICUad.

Electronic health record machine learning model predicts trauma inpatient mortality in real time: A validation study.

Patient outcome prediction models are underused in clinical practice because of lack of integration with real-time patient data. The electronic health record (EHR) has the ability to use machine learning (ML) to develop predictive models. While an EHR ML model has been developed to predict clinical deterioration, it has yet to be validated for use in trauma. We hypothesized that the Epic Deterioration Index (EDI) would predict mortality and unplanned intensive care unit (ICU) admission in trauma patients. A retrospective analysis of a trauma registry was used to identify patients admitted to a level 1 trauma center for >24 hours from October 2019 to July 2020. We evaluated the performance of the EDI, which is constructed from 125 objective patient measures within the EHR, in predicting mortality and unplanned ICU admissions. We performed a 5 to 1 match on age because it is a major component of EDI, then examined the area under the receiver operating characteristic curve (AUROC), and benchmarked it against Injury Severity Score (ISS) and new injury severity score (NISS). The study cohort consisted of 1,325 patients admitted with a mean age of 52.5 years and 91% following blunt injury. The in-hospital mortality rate was 2%, and unplanned ICU admission rate was 2.6%. In predicting mortality, the maximum EDI within 24 hours of admission had an AUROC of 0.98 compared with 0.89 of ISS and 0.91 of NISS. For unplanned ICU admission, the EDI slope within 24 hours of ICU admission had a modest performance with an AUROC of 0.66. Epic Deterioration Index appears to perform strongly in predicting in-patient mortality similarly to ISS and NISS. In addition, it can be used to predict unplanned ICU admissions. This study helps validate the use of this real-time EHR ML-based tool, suggesting that EDI should be incorporated into the daily care of trauma patients. Prognostic, level III.

1270 Secondary Survey Documentation in Trauma Patients - A Review Following Implementation of a Dedicated Trauma Ward

Abstract Introduction A secondary survey is a detailed head to toe assessment performed in trauma patients following initial primary survey and patient stabilisation. It forms part of the ATLS guidelines and is an important tool in the recognition of patient injury. We performed an audit within the Regional Trauma Unit to assess the standard of documentation of secondary surveys in trauma admissions. We then repeated this audit following staff teaching and the implementation of a dedicated Trauma Ward, with an aim of improving secondary survey documentation and the early recognition and management of associated injuries. Method Admission notes for all trauma patients admitted in the three months prior to the opening of the dedicated Trauma Ward were reviewed for documentation of a secondary survey (n = 30), with the incidence of any missed injuries on follow up recorded. A further audit loop was then performed on all trauma admissions following the opening of the Trauma Ward and trauma staff teaching (n = 52). Results Complete documentation of a full secondary survey improved from 10% to 98% for trauma patient admissions. This also improved early identification of initially missed injuries from the primary survey including extremity fractures, chest trauma, and multi-ligament knee injuries. Conclusions Secondary surveys are an important tool in assessing trauma patients and can help identify significant injuries. The implementation of a dedicated Trauma Ward along with teaching to the trauma staff has led to an improvement in performance of secondary surveys with a direct improvement in identifying associated injuries in trauma patients.

Which criteria is a better predictor of ICU admission in trauma patients? An artificial neural network approach

PurposeOne of the most critical concerns in the intensive care unit (ICU) section is identifying the best criteria for entering patients to this part. This study aimed to predict the best compatible criteria for entering trauma patients in the ICU section. MethodThe present study was a historical cohort study. The data were collected from 2448 trauma patients referring to Shahid Rajaee Hospital between January 2015 and January 2017 in Shiraz, Iran. The artificial neural network (ANN) models with cross-validation and logistic regression (LR) with a backward method was used for data analysis. The final analysis was performed on a total of 958 patients who were transferred to the ICU section. ResultsBased on the present results, the motor component of the GCS score at each cutoff point had the highest importance. The results also showed better performance for the AUC and accuracy rate for ANN compared with LR. ConclusionThe most critical indicators in predicting the optimal use of ICU services in this study were the Motor component of the GCS. Results revealed that the ANN had a better performance than the LR in predicting the main outcomes of the traumatic patients in both the accuracy and AUC index. Trauma section surgeons and ICU specialists will benefit from this study's results and can assist them in making decisions to predict the patient outcomes before entering the ICU.

Staffing in a Level 1 Trauma Center: Quantifying Capacity for Preparedness.

We sought to determine who is involved in the care of a trauma patient. We recorded hospital personnel involved in 24 adult Priority 1 trauma patient admissions for 12 h or until patient demise. Hospital personnel were delineated by professional background and role. We cataloged 19 males and 5 females with a median age of 50-y-old (interquartile range [IQR], 35.5-67.5). The average number of hospital personnel involved was 79.71 (standard deviation, 17.62; standard error 3.6). A median of 51.2% (IQR, 43.4%-59.8%) of personnel were first involved within hour 1. More personnel were involved in direct versus indirect care (median 54.5 [IQR, 47.5-67.0] vs 25.0 [IQR, 22.0-30.5]; P < 0.0001). Median number of health-care professionals and auxiliary staff were 74.5 (IQR, 63.5-90.5) and 6.0 (IQR, 5.0-7.0), respectively. More personnel were first involved in hospital locations external to the emergency department (median, 53.0 [IQR, 41.5-63.0] vs 27.5 [IQR, 24.0-30.0]; P < 0.0001). No differences existed in total personnel by Injury Severity Score (P = 0.1266), day (P = 0.7270), or time of admission (P = 0.2098). A large number of hospital personnel with varying job responsibilities respond to severe trauma. These data may guide hospital staffing and disaster preparedness policies.

Impact of the COVID-19 outbreak on severe trauma trends and healthcare system reassessment in Lombardia, Italy: an analysis from the regional trauma registry

BackgroundsThe COVID-19 pandemic drastically strained the health systems worldwide, obligating the reassessment of how healthcare is delivered. In Lombardia, Italy, a Regional Emergency Committee (REC) was established and the regional health system reorganized, with only three hospitals designated as hubs for trauma care. The aim of this study was to evaluate the effects of this reorganization of regional care, comparing the distribution of patients before and during the COVID-19 outbreak and to describe changes in the epidemiology of severe trauma among the two periods.MethodsA cohort study was conducted using retrospectively collected data from the Regional Trauma Registry of Lombardia (LTR). We compared the data of trauma patients admitted to three hub hospitals before the COVID-19 outbreak (September 1 to November 19, 2019) with those recorded during the pandemic (February 21 to May 10, 2020) in the same hospitals. Demographic data, level of pre-hospital care (Advanced Life Support-ALS, Basic Life Support-BLS), type of transportation, mechanism of injury (MOI), abbreviated injury score (AIS, 1998 version), injury severity score (ISS), revised trauma score (RTS), and ICU admission and survival outcome of all the patients admitted to the three trauma centers designed as hubs, were reviewed. Screening for COVID-19 was performed with nasopharyngeal swabs, chest ultrasound, and/or computed tomography.ResultsDuring the COVID-19 pandemic, trauma patients admitted to the hubs increased (46.4% vs 28.3%, p < 0.001) with an increase in pre-hospital time (71.8 vs 61.3 min, p < 0.01), while observed in hospital mortality was unaffected. TRISS, ISS, AIS, and ICU admission were similar in both periods. During the COVID-19 outbreak, we observed substantial changes in MOI of severe trauma patients admitted to three hubs, with increases of unintentional (31.9% vs 18.5%, p < 0.05) and intentional falls (8.4% vs 1.2%, p < 0.05), whereas the pandemic restrictions reduced road- related injuries (35.6% vs 60%, p < 0.05). Deaths on scene were significantly increased (17.7% vs 6.8%, p < 0.001).ConclusionsThe COVID-19 outbreak affected the epidemiology of severe trauma patients. An increase in trauma patient admissions to a few designated facilities with high level of care obtained satisfactory results, while COVID-19 patients overwhelmed resources of most other hospitals.

Blood Glucose Levels Combined with Triage Revised Trauma Score Improve the Outcome Prediction in Adults and in Elderly Patients with Trauma.

This study was aimed to assess if combining the evaluation of blood glucose level (BGL) and the Triage Revised Trauma Score (T-RTS) may result in a more accurate prediction of the actual clinical outcome, both in general adult population and in elderly patients with trauma. This is a retrospective cohort study, conducted in the emergency department (ED) of an urban teaching hospital, with an average ED admission rate of 75,000 patients per year. Those excluded: known diagnosis of diabetes, age <18 years old, pregnancy, and mild trauma (classified as isolate trauma of upper or lower limb, in absence of exposed fractures). A combined Revised Trauma Score Glucose (RTS-G) score was obtained adding to T-RTS: two for BGL <160mg/dL (8.9mmol/L); one for BGL ≥160mg/dL and < 200mg/dL (11.1mmol/L); and zero for BGL ≥ 200mg/dL. The primary outcome was a composite of patient's death in ED or admission to intensive care unit (ICU). Receiver Operating Characteristic (ROC) curve analysis was used to evaluate the overall performance of T-RTS and of the combined RTS-G score. Among a total of 68,933 traumas, 9,436 patients (4,407 females) were enrolled, aged from 18 to 103 years; 4,288 were aged ≥65 years. A total of 577 (6.1%) met the primary endpoint: 38 patients died in ED (0.4%) and 539 patients were admitted to ICU. The T-RTS and BGL were independently associated to primary endpoint at multivariate analysis. The cumulative RTS-G score was significantly more accurate than T-RTS and reached the best accuracy in elderly patients. In general population, ROC area under curve (AUC) for T-RTS was 0.671 (95% CI, 0.661 - 0.680) compared to RTS-G ROC AUC 0.743 (95% CI, 0.734 - 0.752); P <.001. In patients ≥65 years, T-RTS ROC AUC was 0.671 (95% CI, 0.657 - 0.685) compared to RTS-G ROC AUC 0.780 (95% CI, 0.768 - 0.793); P <.001. Results showed RTS-G could be used effectively at ED triage for the risk stratification for death in ED and ICU admission of trauma patients, and it could reduce under-triage of approximately 20% compared to T-RTS. Comparing ROC AUCs, the combined RTS-G score performs significantly better than T-RTS and gives best results in patients ≥65 years.

Cold weather is independently associated with hypothermia in severely injured trauma patients

Introduction Hypothermia at admission in trauma patients has been significantly associated with worse outcomes and increased blood usage. Previous studies have found variably significant associations between ambient temperatures and incidence of hypothermia in trauma patients. Methods The trauma quality improvement registry was queried for data on trauma patients admitted direct from the scene over a 5-year period. This database was matched to daily weather data taken from the nearest National Oceanic and Atmospheric Administration land-based climate monitoring center, and further combined with blood usage data from the laboratory information system. Results Multivariate logistic regression models predicted significant associations between ambient temperature and patient admission temperature for severely injured patients. No significant direct associations were predicted between ambient temperature and in-hospital mortality or blood usage. Models predicted a significant association between decreased admission temperature and increased likelihood of both blood transfusion and mortality for a severely injured subgroup. Conclusions Ambient temperature is a significant contributor to the rate of admission hypothermia in trauma patients. Most of the variability in admission temperatures for severely injured trauma patients remains unaccounted for by models using standard markers of anatomic and physiologic severity. Decreasing admission temperature is significantly associated with increased mortality and likelihood of blood transfusion for severely injured patients.

Pre-hospital CPR and early REBOA in trauma patients \u2014 results from the ABOTrauma Registry

BackgroundSeverely injured trauma patients suffering from traumatic cardiac arrest (TCA) and requiring cardiopulmonary resuscitation (CPR) rarely survive. The role of resuscitative endovascular balloon occlusion of the aorta (REBOA) performed early after hospital admission in patients with TCA is not well-defined. As the use of REBOA increases, there is great interest in knowing if there is a survival benefit related to the early use of REBOA after TCA. Using data from the ABOTrauma Registry, we aimed to study the role of REBOA used early after hospital admission in trauma patients who required pre-hospital CPR.MethodsRetrospective and prospective data on the use of REBOA were collected from the ABOTrauma Registry from 11 centers in seven countries globally between 2014 and 2019. In all patients with pre-hospital TCA, the predicted probability of survival, calculated with the Revised Injury Severity Classification II (RISC II), was compared with the observed survival rate.ResultsOf 213 patients in the ABOTrauma Registry, 26 patients (12.2%) who had received pre-hospital CPR were identified. The median (range) Injury Severity Score (ISS) was 45.5 (25–75). Fourteen patients (54%) had been admitted to the hospital with ongoing CPR. Nine patients (35%) died within the first 24 h, while seventeen patients (65%) survived post 24 h. The survival rate to hospital discharge was 27% (n = 7). The predicted mortality using the RISC II was 0.977 (25 out of 26). The observed mortality (19 out of 26) was significantly lower than the predicted mortality (p = 0.049). Patients not responding to REBOA were more likely to die. Only one (10%) out of 10 non-responders survived. The survival rate in the 16 patients responding to REBOA was 37.5% (n = 6). REBOA with a median (range) duration of 45 (8–70) minutes significantly increases blood pressure from the median (range) 56.5 (0–147) to 90 (0–200) mmHg.ConclusionsMortality in patients suffering from TCA and receiving REBOA early after hospital admission is significantly lower than predicted by the RISC II. REBOA may improve survival after TCA. The use of REBOA in these patients should be further investigated.

A comparative observational study of injury severity score and new injury severity score as criteria for admission of trauma patients in a tertiary care center

Background: Trauma has been a major cause of morbidity and mortality all across the globe. For the improvement of delivery of efficient care to these victims, various trauma severity indices have been devised which make it possible to plan emergency care and assess need for hospitalization and optimize hospital resources. This study was carried out to compare and evaluate Injury Severity Score (ISS) and New Injury Severity Score (NISS) as criteria for admission of trauma patients. Materials and Methods: It was a prospective observational study. The available data were analyzed to determine and compare ISS and NISS as the criteria for admission. The statistical software SPSS (version 20) was used for data analysis. Results: A total of 102 patients were studied at trauma center of our hospital. Out of the total patients, 59.8% of patients had their NISS scores greater than ISS, which showed that NISS is more sensitive and accurate than ISS. It was observed that NISS was not better in predicting hospital stay as compared to ISS. The relationship between NISS and number of hospitalization days was not statistically significant (P = 0.112) whereas ISS was a better predictor of hospital stay (P = 0.042). Conclusion: In this study, it was observed that majority of parameters have favored NISS whereas parameters like hospital stay have favored ISS. Hence, we concluded that NISS is a better score than ISS in many aspects and it can be preferred over ISS as one of the criteria for Hospital admission of trauma patients.

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.

Pre-hospital times and clinical characteristics of severe trauma patients: A comparison between mountain and urban/suburban areas

ObjectiveWe investigated pre-hospital times, clinical characteristics and therapeutic interventions in multisystem trauma patients injured in mountainous areas in comparison to both urban and suburban trauma patient admissions. MethodsPre-hospital and in-hospital data collected from trauma patients included in the International Alpine Trauma Register (IATR) hosted in Bolzano, Italy (aged 16–80 yr with an ISS ≥ 16), were compared with trauma patient data published from those urban and suburban areas included in the Trauma Register DGU® (TR-DGU) of the German Trauma Society. ResultsA total of 94 patients from the IATR and 11,020 patients from the TR-DGU met the inclusion criteria. Due to longer treatment-free intervals (mean 59.1 vs. 19.7 min), total out-of-hospital time was reportedly longer in individuals injured in mountainous areas, compared to urban/suburban areas (117.4 ± 142.9 vs. 68.7 ± 28.6 min, p = 0.002), despite the more frequent helicopter rescue (93% vs. 40%, p < 0.001). 57% of IATR patients were hypothermic at hospital arrival, mean ISS was higher (38.5 ± 15.8 vs. 28.6 ± 12.2, p < 0.001) and patients with a systolic blood pressure (SBP) ≤90 mm Hg were more frequent (27% vs. 15%, p = 0.005), yet less patients had received volume therapy (82% vs. 93%, p = 0.001). However, overall no difference in hospital mortality was observed (11% vs. 17%, p = 0.159). ConclusionTrauma incidents in mountainous areas commonly feature significantly increased out-of-hospital time which is associated with a more severe ISS, higher risk of accidental hypothermia and more frequent hypotension compared to urban/suburban trauma. Nonetheless, the mortality rate of IATR patients is comparable to urban/suburban trauma patients.