In-hospital Mortality In Trauma Patients Research Articles

Impact of Time-to-operation on In-hospital Mortality of Trauma Patients with Abdominal Injury Who Underwent Door-to-door Laparotomy

Impact of Time-to-operation on In-hospital Mortality of Trauma Patients with Abdominal Injury Who Underwent Door-to-door Laparotomy

Intubation and In-Hospital Mortality After Trauma With Glasgow Coma Scale Score Eight or Less–A Cohort Study

IntroductionMost trauma societies recommend intubating trauma patients with Glasgow Coma Scale (GCS) scores ≤8 without robust supporting evidence. We examined the association between intubation and 30-d in-hospital mortality in trauma patients arriving with a GCS score ≤8 in an Indian trauma registry. MethodsOutcomes of patients with a GCS score ≤8 who were intubated within 1 h of arrival (intubation group) were compared with those who were intubated later or not at all (nonintubation group) using various analytical approaches. The association was assessed in various subgroup and sensitivity analyses to identify any variability of the effect. ResultsOf 3476 patients who arrived with a GCS score ≤8, 1671 (48.1%) were intubated within 1 h. Overall, 1957 (56.3%) patients died, 947 (56.7%) in the intubation group and 1010 (56.0%) in the nonintubation group, with no significant difference in mortality (odds ratio = 1.2 [confidence interval, 0.8-1.8], P value = 0.467) in multivariable regression and propensity score-matched analysis. This result persisted across subgroup and sensitivity analyses. Patients intubated within an hour of arrival had longer durations of ventilation, intensive care unit stay, and hospital stay (P < 0.001). ConclusionsIntubation within an hour of arrival with a GCS score ≤8 after major trauma was not associated with differences in-hospital mortality. The indications and benefits of early intubation in these severely injured patients should be revisited to promote optimal resource utilization in LMICs.

Nomogram for predicting in-hospital mortality in trauma patients undergoing resuscitative endovascular balloon occlusion of the aorta: a retrospective multicenter study

Recently, resuscitative endovascular balloon occlusion of the aorta (REBOA) had been introduced as an innovative procedure for severe hemorrhage in the abdomen or pelvis. We aimed to investigate risk factors associated with mortality after REBOA and construct a model for predicting mortality. This multicenter retrospective study collected data from 251 patients admitted at five regional trauma centers across South Korea from 2015 to 2022. The indications for REBOA included patients experiencing hypovolemic shock due to hemorrhage in the abdomen, pelvis, or lower extremities, and those who were non-responders (systolic blood pressure (SBP) < 90 mmHg) to initial fluid treatment. The primary and secondary outcomes were mortality due to exsanguination and overall mortality, respectively. After feature selection using the least absolute shrinkage and selection operator (LASSO) logistic regression model to minimize overfitting, a multivariate logistic regression (MLR) model and nomogram were constructed. In the MLR model using risk factors selected in the LASSO, five risk factors, including initial heart rate (adjusted odds ratio [aOR], 0.99; 95% confidence interval [CI], 0.98–1.00; p = 0.030), initial Glasgow coma scale (aOR, 0.86; 95% CI 0.80–0.93; p < 0.001), RBC transfusion within 4 h (unit, aOR, 1.12; 95% CI 1.07–1.17; p < 0.001), balloon occlusion type (reference: partial occlusion; total occlusion, aOR, 2.53; 95% CI 1.27–5.02; p = 0.008; partial + total occlusion, aOR, 2.04; 95% CI 0.71–5.86; p = 0.187), and post-REBOA systolic blood pressure (SBP) (aOR, 0.98; 95% CI 0.97–0.99; p < 0.001) were significantly associated with mortality due to exsanguination. The prediction model showed an area under curve, sensitivity, and specificity of 0.855, 73.2%, and 83.6%, respectively. Decision curve analysis showed that the predictive model had increased net benefits across a wide range of threshold probabilities. This study developed a novel intuitive nomogram for predicting mortality in patients undergoing REBOA. Our proposed model exhibited excellent performance and revealed that total occlusion was associated with poor outcomes, with post-REBOA SBP potentially being an effective surrogate measure.

Association between albumin-corrected anion gap and in-hospital mortality of intensive care patients with trauma: A retrospective study based on MIMIC-Ⅲ and Ⅳ databases.

To investigate the correlation between albumin-corrected anion gap(ACAG) within the first 24 hours of admission and in-hospital mortality in trauma patients in intensive care unit(ICU). We utilized the MIMIC-Ⅲ and MIMIC-Ⅳ databases to examine trauma patients admitted to the ICU. The relationship between ACAG and in-hospital mortality in trauma patients was analyzed using Receiver Operating Characteristic(ROC) curve, Kaplan-Meier (K-M) survival curve, and Cox regression model. Propensity score matching (PSM) and subgroup analysis were conducted to enhance stability and reliability of the findings. Mortality at 30-day and 90-day served as secondary outcomes. The study enrolled a total of 1038 patients. The AUC for ACAG (0.701, 95%CI: 0.652-0.749) was notably higher than that for anion gap and albumin. The Log-rank test revealed that the optimal cut-off point of ACAG for predicting in-hospital mortality was determined to be 20.375mmol/L. The multivariate Cox regression analysis demonstrated an independent association between high ACAG level and a higher risk of in-hospital mortality (HR = 3.128, 95% CI: 1.615-6.059). After PSM analysis, a matched cohort consisting of 291 subjects was obtained. We found no signifcant interaction in most stratas. Finally, The in-hospital, 30-day, and 90-day survival rates in the high ACAG group exhibited a statistically decrease compared to those in the low ACAG group both pre- and post-matching. The elevated level of ACAG was found to be independently associated with increased in-hospital mortality among trauma patients in the ICU.

DIAGNOSTIC ACCURACY OF RAPID EMERGENCY MEDICINE SCORE (REMS) AS A PROGNOSTIC MARKER AND ITS COMPARISON WITH TRADITIONAL SCORING SYSTEMS IN TRAUMA

A Hospital-based screening test study was conducted at the Department of Emergency Medicine at Mahatma Gandhi Mission Medical College and Hospital, Kamothe, Navi Mumbai. The study aimed to compare the diagnostic accuracy of Rapid Emergency Medicine Score (REMS) with that of other traditional scoring systems like Injury Severity Score (ISS) and Revised Trauma Score (RTS). We also aimed to correlate in association with raised lactate values to predict in-hospital mortality in trauma patients as compared to REMS alone. The study included 100 consecutive trauma patients coming to our emergency department, fullling the eligibility criteria. Following observations were made during the study, Mean age of the study cases was 38.98 years with over half of them being between 21 to 40 years of age. Out of the 100 cases, 87% were males and 13% were females. Nature of trauma was a road trafc accident in the majority of the cases (63%). Other causes were falling (26%), assault (10%), and workplace injury (1%). Loss of consciousness was seen in 34% of cases while vomiting and seizures were seen in 21% and 6% cases respectively. Compromised airway was noted in 42% cases while the hypotensive and hypertensive state was observed in 68% and 3% cases respectively.Mortality rate in the present study was 11%.On ROC analysis, all the scores including REMS, ISS, and RTS were observed to be signicant predictors of mortality among trauma cases.

The Addition of ROTEM Parameter Did Not Significantly Improve the Massive Transfusion Prediction in Severe Trauma Patients.

Background Rotational thrombelastometry (ROTEM) has been used to evaluate the coagulation state, predict transfusion, and optimize hemostatic management in trauma patients. However, there were limited studies on whether the prediction value could be improved by adding the ROTEM parameter to the prediction model for in-hospital mortality and massive transfusion (MT) in trauma patients. Objective This study assessed whether ROTEM data could improve the MT prediction model. Method This was a single-center, retrospective study. Patients who presented to the trauma center and underwent ROTEM between 2016 and 2020 were included. The primary and secondary outcomes were massive transfusions and in-hospital mortality, respectively. We constructed two models using multivariate logistic regression with backward conditional stepwise elimination (Model 1: without the ROTEM parameter and Model 2: with the ROTEM parameter). The area under the receiver operating characteristic curve (AUROC) was calculated to assess the predictive ability of the models. Result In total, 969 patients were included; 196 (20.2%) received MT. The in-hospital mortality rate was 14.1%. For MT, the AUROC was 0.854 (95% confidence interval [CI], 0.825–0.883) and 0.860 (95% CI, 0.832–0.888) for Model 1 and 2, respectively. For in-hospital mortality, the AUROC was 0.886 (95% CI, 0.857–0.915) and 0.889 (95% CI, 0.861–0.918) for models 1 and 2, respectively. The AUROC values for models 1 and 2 were not statistically different for either MT or in-hospital mortality. Conclusion We found that the addition of the ROTEM parameter did not significantly improve the predictive power of MT and in-hospital mortality in trauma patients.

Antibiotic Initiation Timing and Mortality in Trauma Patients With Ventilator-Associated Pneumonia.

Early antibiotic initiation is considered a cornerstone in the management of ventilator-associated pneumonia (VAP). However, recent data suggests that early antibiotic initiation may not be necessary in all cases. Additionally, the benefits of early antibiotic administration for infection have not been studied in a dedicated trauma population. This study's aim was to evaluate the impact of antibiotic administration timing on in-hospital mortality in trauma patients with VAP. This retrospective case-control study identified all trauma patients at a single level 1 academic trauma center from 2016 to 2020. Patients with a TQIP-defined VAP were included and stratified into 2 subgroups by in-hospital mortality. Time interval between airway culture and antibiotic initiation was gathered. Baseline measures of injury and illness severity were collected. Univariate analysis of the data was performed. Forty-five patients met inclusion criteria. Overall, 80% of patients survived admission (n = 36) and 20% of patients did not survive admission (n = 9). There were no significant differences in baseline characteristics or cultured organism between survivors and non-survivors. The median time interval between airway culture and antibiotic initiation was 2 hours (IQR 0-4.5) for survivors, and 0 hours (IQR 0-0) for non-survivors (P = .07). Antibiotics were administered within 1 hour of airway culture for 33.3% of survivors, and 77.8% of non-survivors (P = .02). In a population of trauma patients with VAP, survivors had antibiotics initiated in more delayed fashion than non-survivors. These findings question the primacy of early antibiotic administration for suspected infection.

A Nomogram to Better Predict the In-Hospital Mortality of Trauma Patients with Sepsis in the Intensive Care Unit

Background Trauma has a high incidence and mortality worldwide, and sepsis is one of the main causes of mortality in trauma patients. Therefore, it is essential to identify the risk factors of in-hospital mortality for trauma patients with sepsis. Methods Data were extracted from the Medical Information Mart for Intensive Care III database and divided into a training set and internal validation set, and another Chinese dataset was used as external validation set. Then, risk factors were estimated using univariate and multivariate logistic regression analyses in the training set. Finally, a nomogram was created to predict the probability of in-hospital mortality for trauma patients with sepsis. Results A total of 503 patients were enrolled in our study (335 in the training set and 168 in the validation set). Multivariate logistic regression analysis revealed that age (1.047 [1.025–1.071]), respiratory rate (1.258 [1.135–1.394]), PTT (1.026 [1.008–1.044]), ventilation (6.703 [1.528–29.408]), and vasopressor use (3.682 [1.502–9.025]) were independent factors associated with in-hospital mortality. The nomogram for trauma-related sepsis predicted in-hospital mortality with AUC values of 0.8939 in the training set, 0.8200 in the internal validation set, and 0.7779 in the external validation set. Conclusions The new nomogram has a well predicted value for in-hospital mortality for patients with trauma and sepsis in intensive care units.

Shock index as a predictor for mortality in trauma patients

Background: Traumatic injury accounts for 7.8% of all deaths globally, and 30% to 40% of those deaths are due to hemorrhage. Shock Index (SI) has been found to be useful in the recognition of hemorrhage but no definite threshold for predicting mortality has been determined. Our aim was to determine whether a SI ≥ 1 in adult trauma patients was associated with increased in-hospital mortality compared to a SI &lt; 1.&#x0D; Methods: We conducted a systematic review and meta-analysis using Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. EMBASE, MEDLINE, and Cochrane Library were searched using controlled vocabulary, and retrospective observational studies were included. Studies were included if they reported in-hospital mortality in trauma patients aged ≥ 16 years, with a measurement of SI from the emergency department or trauma center, dividing patients in groups of SI ≥ 1 and SI &lt; 1. Risk of bias was assessed by using the Newcastle-Ottawa Scale, and the strength and quality of the body of evidence was assessed according to GRADE. Data was pooled using a random effects model.Results: We screened 1239 citations with an inter-rater reliability (Cohen’s kappa) of 0.90 (95% CI 0.88-0.93). Thirteen comparative cohort studies including 639210 patients were included. All studies reported a significant higher in-hospital mortality in adult trauma patients with a SI ≥ 1 compared to those having a SI &lt; 1 at first assessment in the emergency department or trauma center. Eleven studies were included in the meta-analysis. The pooled risk ratio (RR) of in-hospital mortality was RR 4.29 (95% confidence interval 3.00 - 6.12). The overall quality of evidence was low.&#x0D; Conclusion: This systematic review found a fourfold risk of in-hospital mortality in adult trauma patients with an initial SI ≥ 1 in the emergency department or trauma center.

Predictive value of machine learning for in-hospital mortality for trauma-induced acute respiratory distress syndrome patients: an analysis using the data from MIMIC III

To investigate the value of machine learning methods for predicting in-hospital mortality in trauma patients with acute respiratory distress syndrome (ARDS). A retrospective non-intervention case-control study was performed. Trauma patients with ARDS met the Berlin definition were extracted from the the Medical Information Mart for Intensive Care III (MIMIC III) database. The basic information [including gender, age, body mass index (BMI), pH, oxygenation index, laboratory indexes, length of stay in the intensive care unit (ICU), the proportion of mechanical ventilation (MV) or continuous renal replacement therapy (CRRT), acute physiology score III (APS III), sequential organ failure score (SOFA) and simplified acute physiology score II (SAPS II)], complications (including hypertension, diabetes, infection, acute hemorrhagic anemia, sepsis, shock, acidosis and pneumonia) and prognosis data of patients were collected. Multivariate Logistic regression analysis was used to screen meaningful variables (P < 0.05). Logistic regression model, XGBoost model and artificial neural network model were constructed, and the receiver operator characteristic curve (ROC) was performed to evaluate the predictive value of the three models for in-hospital mortality in trauma patients with ARDS. A total of 760 trauma patients with ARDS were enrolled, including 346 mild cases, 301 moderate cases and 113 severe cases; 618 cases survived and 142 cases died in hospital; 736 cases received MV and 65 cases received CRRT. Multivariate Logistic regression analysis screened out significant variables, including age [odds ratio (OR) = 1.035, 95% confidence interval (95%CI) was 1.020-1.050, P < 0.001], BMI (OR = 0.949, 95%CI was 0.917-0.983, P = 0.003), blood urea nitrogen (BUN; OR = 1.019, 95%CI was 1.004-1.033, P = 0.010), lactic acid (Lac; OR = 1.213, 95%CI was 1.124-1.309, P < 0.001), red cell volume distribution width (RDW; OR = 1.249, 95%CI was 1.102-1.416, P < 0.001), hematocrit (HCT, OR = 1.057, 95%CI was 1.019-1.097, P = 0.003), hypertension (OR = 0.614, 95%CI was 0.389-0.968, P = 0.036), infection (OR = 0.463, 95%CI was 0.289-0.741, P = 0.001), acute renal failure (OR = 2.021, 95%CI was 1.267-3.224, P = 0.003) and sepsis (OR = 2.105, 95%CI was 1.265-3.502, P = 0.004). All the above variables were used to construct the model. Logistic regression model, XGBoost model and artificial neural network model predicted in-hospital mortality with area under the curve (AUC) of 0.737 (95%CI was 0.659-0.815), 0.745 (95%CI was 0.672-0.819) and 0.757 (95%CI was 0.680-0.884), respectively. There was no significant difference between any two models (all P > 0.05). Logistic regression model, XGBoost model and artificial neural network model including age, BMI, BUN, Lac, RDW, HCT, hypertension, infection, acute renal failure and sepsis have good predictive value for in-hospital mortality of trauma patients with ARDS.

Clinical implications of the newly defined concept of ventilator-associated events in trauma patients.

Ventilator-associated pneumonia is the most common nosocomial infection in patients with mechanical ventilation. In 2013, the new concept of ventilator- associated events (VAEs) replaced the traditional concept of ventilator-associated pneumonia. We analyzed risk factors for VAE occurrence and in-hospital mortality in trauma patients who received mechanical ventilatory support. In this retrospective review, the study population comprised patients admitted to the Jeju Regional Trauma Center from January 2020 to January 2021. Data on demographics, injury characteristics, and clinical findings were collected from medical records. The subjects were categorized into VAE and no-VAE groups according to the Centers for Disease Control and Prevention/National Healthcare Safety Network VAE criteria. We identified risk factors for VAE occurrence and in-hospital mortality. Among 491 trauma patients admitted to the trauma center, 73 patients who received ventilator care were analyzed. Patients with a chest Abbreviated Injury Scale (AIS) score ≥3 had a 4.7-fold higher VAE rate (odds ratio [OR], 4.73; 95% confidence interval [CI], 1.46-17.9), and those with a glomerular filtration rate (GFR) <75 mL/min/1.73 m2 had 4.1-fold higher odds of VAE occurrence (OR, 4.15; 95% CI, 1.32-14.1) and a nearly 4.2-fold higher risk for in-hospital mortality (OR, 4.19; 95% CI, 1.30-14.3). The median VAE-free duration of patients with chest AIS ≥3 was significantly shorter than that of patients with chest AIS <3 (P=0.013). Trauma patients with chest AIS ≥3 or GFR <75 mL/min/1.73 m2 on admission should be intensively monitored to detect at-risk patients for VAEs and modify the care plan accordingly. VAEs should be closely monitored to identify infections early and to achieve desirable results. We should also actively consider modalities to shorten mechanical ventilation in patients with chest AIS ≥3 to reduce VAE occurrence.

Physiologic Scoring Systems versus Glasgow Coma Scale in Predicting In-Hospital Mortality of Trauma Patients; a Diagnostic Accuracy Study.

Introduction:In recent years, several scoring systems have been developed to assess the severity of trauma and predict the outcome of trauma patients. This study aimed to compare Rapid Emergency Medicine Score (REMS), Modified Early Warning Score (MEWS), Injury Severity Score (ISS), and Glasgow Coma Scale (GCS) in predicting the in-hospital mortality of trauma patients.Methods:This diagnostic accuracy study was done on adult patients admitted to the emergency department (ED) between June 21, 2019, and September 21, 2020, following multiple trauma. Patients were followed as long as they were hospitalized. The REMS, MEWS, GCS, and ISS were calculated after data gathering and comprehensive assessment of injuries. Receiver operating characteristics (ROC) analysis was performed to examine the prognostic performance of the four different tools.Results:Of the 754 patients, 32 patients (4.2%) died and 722 (95.8%) survived after 24 hours of admission. The mean age of the patients was 38.54 ± 18.58 years (78.9% male). The area under the ROC curves (AUC) of REMS, MEWS, ISS, and GCS score for predicting in-hospital mortality were 0.942 (95% CI [0.923-0.958]), 0.886 (95% CI [0.861-0.908]), 0.866 (95% CI [0.839-0.889]), and 0.851 (95% CI [0.823-0.876]), respectively. The AUC of REMS was significantly higher than GCS (p=0.035). The sensitivities of GCS ≤ 11, ISS ≥ 13, REMS ≥ 4, and MEWS ≥ 3 scores for in-hospital mortality were 0.56, 0.97, 0.81, and 0.94, respectively. Also, the specificities of GCS, ISS, REMS, and MEWS scores for in-hospital mortality were 0.93, 0.82, 0.81, and 0.85, respectively.Conclusion:It seems that REMS is more accurate than GCS, ISS, and MEWS in predicting in-hospital mortality ≥ 24 hours of multiple trauma patients.

The elderly age criterion for increased in-hospital mortality in trauma patients: a retrospective cohort study

BackgroundWith an aging population, the number of elderly individuals exposed to traumatic injuries is increasing. The elderly age criterion for traumatic injuries has been inconsistent in the literature. This study aimed at specifying the elderly age criterion when the traumatic mortality rate increases.MethodsThis is a multicenter retrospective cohort study that was conducted utilizing the data from the Emergency Department-based Injury In-depth Surveillance Registry of the Korea Disease Control and Prevention Agency, collected between January 2014 and December 2018 from 23 emergency departments. The outcome variable was in-hospital mortality. Multivariable logistic regression analysis was used to calculate the adjusted mortality rate for each age group. By using the shape-restricted regression splines method, the relationship between age and adjusted traumatic mortality was plotted and the point where the gradient of the graph had the greatest variation was calculated.ResultsA total of 637,491 adult trauma patients were included. The number of in-hospital deaths was 6504 (1.0%). The age at which mortality increased the most was 65.06 years old. The adjusted odds ratio for the in-hospital mortality rate with age in the ≤ 64-year-old subgroup was 1.038 (95% confidence interval (CI) 1.032–1.044) and in the ≥ 65-year-old subgroup was 1.059 (95% CI 1.050–1.068). The adjusted odds ratio for in-hospital mortality in the ≥ 65-year-old compared to the ≤ 64-year-old subgroup was 4.585 (95% CI 4.158–5.055, p < 0.001).ConclusionsThis study found that the in-hospital mortality rate rose with increasing age and that the increase was the most rapid from the age of 65 years. We propose to define the elderly age criterion for traumatic injuries as ≥ 65 years of age.

Outcomes of Extracorporeal Membrane Oxygenation in Acute Respiratory Distress Syndrome Following Traumatic Injury: A Propensity-Matched Analysis.

The purpose of this study is to evaluate the overall occurrence of inhospital mortality in trauma patients who were placed on extracorporeal membrane oxygenation following the complication of the acute respiratory distress syndrome. Observational cohort study. The data of all patients who were traumatically injured and developed the complication of acute respiratory distress syndrome were accessed from the Trauma Quality Improvement Program database from the calendar years of 2013 to 2016. Patients 16 years old and less than 90 years old were included in the study. Variables included patient demography, Injury Severity Score, Glasgow Coma Scale score, Abbreviated Injury Scale score, and outcomes. Extracorporeal membrane oxygenation. Propensity-matched analysis was performed between two groups: patients placed on extracorporeal membrane oxygenation and patients placed on conventional mode of ventilation. The primary outcome was inhospital mortality. Out of 6,121 patients who developed acute respiratory distress syndrome, 118 patients (1.93%) were placed on extracorporeal membrane oxygenation. The pair matched analysis showed significant difference between the two groups (extracorporeal membrane oxygenation vs conventional mode of ventilation) for overall inhospital mortality (35.6% vs 14.4%; p < 0.001). There were significant differences found between the two groups for the median hospital length of stay (41 [35-49] vs 27 [24-33]), ICU days (35 [30-41] vs 19 [17-24]), and ventilator days (30 [27-34] vs 15 [13-18]). All p values are less than 0.001. Approximately 2% of acute respiratory distress syndrome patients were placed on extracorporeal membrane oxygenation. The overall inhospital mortality remained high despite patients being placed on extracorporeal membrane oxygenation.

Impact of Method in Pre-Hospital Transportation on In-Hospital Mortality in Trauma Patients with Firearm Injury

Impact of Method in Pre-Hospital Transportation on In-Hospital Mortality in Trauma Patients with Firearm Injury

Body temperature and in-hospital mortality in trauma patients: analysis of a nationwide trauma database in Japan.

Avoiding body temperature (BT) abnormalities has been emphasized in trauma care, and BT correction in the initial treatment period may improve patient outcome. However, the effect of hyperthermia at hospital arrival on mortality in trauma patients is unclear. This study aimed to identify the association between BT and in-hospital mortality among adult trauma patients. This was a retrospective analysis of a multi-centre prospective cohort study. Data were obtained from the Japan Trauma Data Bank (JTDB). Adult trauma patients who were transferred directly from the scene of injury to the hospital and registered in the JTDB between January 2004 and December 2017 were included. The primary outcome was the association between BT at hospital arrival and in-hospital mortality. BT at hospital arrival was classified by 1°C strata. We conducted multivariable logistic regression analyses to calculate the adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for in-hospital mortality for each BT group using 36.0-36.9°C as a reference. Overall, 153,117 patients were included. The total mortality rate was 7% (n = 10,118). The adjusted OR for in-hospital mortality for < 35.0°C was 1.65 (95% CI 1.51-1.79, p < 0.001), 35.0-35.9°C was 1.33 (95% CI 1.25-1.41, p < 0.001), 37.0-37.9°C was 0.99 (95% CI 0.91-1.07, p = 0.639), 38.0-38.9°C was 1.30 (95% CI 1.08-1.56, p = 0.007) and > 39.0°C was 1.62 (95% CI 1.18-2.22, p = 0.003) compared to that for normothermia. Our results reveal that hypothermia and hyperthermia at hospital arrival are associated with increased in-hospital mortality in adult trauma patients.

Audit on in-hospital mortality of trauma patients: EMS Management and Mismanagement

Background: The investigation of trauma-related mortality is one of the key components in trauma studies and it is used as a performance index and measure of health care quality. Objective: The present study aimed to evaluate the performance of pre-hospital interventions and identify possible mismanagements in dealing with trauma patients transferred by emergency medical services (EMS) to the hospital and died. Methods: This study was conducted in 2019, in Tehran, Iran. All trauma patients who were transferred to the emergency department (ED) of three main referral hospitals, by Tehran EMS and died at the hospital within 24 hours of admission, were studied retrospectively. The required information was collected from the EMS and the hospital records. A panel of experts was asked to identify possible errors based on standards for each patient. Results: During the one-year study period, almost 14000 trauma patients were transported by Tehran EMS to the studied hospitals. Of them, a total of 197 deaths were recorded. The most and least provided services were breathing management (87.3%) and intravenous (IV) fluid therapy (12.2%), respectively. Needle thoracostomy, IV fluids therapy, life supports (basic and advanced cardiac), and airway management had the highest percentage of mismanagement among provided services. Bleeding control and resuscitation were consistent with the recommended standard. Conclusion: In the current study, bleeding control and immobilization was performed appropriately. Needle tracheostomy was not performed at all. Airway management and life supports of the victims were not performed properly.

Ketamine for rapid sequence intubation in adult trauma patients: A retrospective observational study.

In the trauma population, ketamine is commonly used during rapid sequence induction. However, as ketamine has been associated with important side effects, this study sought to compare in-hospital mortality in trauma patients after induction with ketamine versus other induction agents. We retrospectively identified adult trauma patients intubated in the pre-hospital phase or initially in the trauma bay at two urban level-1 trauma centers during a 2-year period using local trauma registries and medical records. In-hospital mortality was compared for patients intubated with ketamine versus other agents using logistic regression with adjustment for age, gender, Injury Severity Score (ISS), systolic blood pressure (SBP) <90mmHg, and pre-hospital Glasgow Coma Scale (GCS) score. A total of 343 trauma patients were included with a median ISS of 25 [17-34]. The most frequently used induction agents were ketamine (36%) and propofol (36%) followed by etomidate (9%) and midazolam (5%). There was no difference in ISS or the presence of SBP <90mmHg according to the agent of choice, but the pre-hospital GCS score was higher for patients intubated with ketamine (median 8 vs 5, P=.001). The mortality for patients intubated with ketamine was 18% vs 27% for patients intubated with other agents (P=.14). This remained statistically insignificant in the multivariable logistic regression analysis (odds ratio 0.68 [0.33-1.41], P=.30). We found no statistically significant difference in mortality among patients intubated in the initial phase post-trauma with the use of ketamine compared with other agents (propofol, etomidate, or midazolam).

The association between time intervals in emergency medical services and In-hospital mortality of trauma patients

Context: While the clinical practice recommends field stabilization in trauma patients, in some situations, the speed of transport is crucial. Aims: This study aimed to evaluate the association between emergency medical services (EMS) time intervals (response time [RT], scene time [ST], and transport time [TT]) and in-hospital mortality in trauma patients in Tehran, the largest metropolis of Iran. Settings and Design: A prospective cohort study was conducted between May 2017 and April 2018. Methods: All EMS operations related to trauma events in the Tehran city that were transferred to three targeted major trauma centers were included. Statistical Analysis: Logistic regression analysis was used to assess the relationship between EMS time intervals and other risk factors of trauma death. Results: A total of 14,372 trauma patients were included in the final analysis. In-hospital mortality occurred in 225 (1.6%) patients. After adjustment for confounding variables, older age (odds ratio [OR] = 1.04/year), female gender (OR = 2.16), low Mechanism, Glasgow Coma Scale (GCS), age, and arterial pressure score (OR = 0.84 for each unit), low GCS (OR = 0.56 for each unit), longer ST (OR = 1.17/10 min), and longer TT (OR = 1.21/10 min) were found to be risk factors for death in trauma. Conclusions: Our study showed that in-hospital mortality of trauma patients correlated with longer EMS ST and TT, but the RT was not associated with mortality. Our results recommend that the EMS system should consider ST and TT rather than RT, as indexes of quality control in prehospital care of trauma patients.

Association of prehospital oxygen administration and mortality in severe trauma patients (PROMIS): A nationwide cohort study.

Until now, we routinely administered oxygen to trauma patients in prehospital settings irrespective of whether oxygen delivery affected the prognosis. To determine the necessity of prehospital oxygen administration (POA) to trauma patients, we aimed to assess whether POA contributed to in-hospital mortality.This was a multicenter propensity-matched cohort study involving 172 major emergency hospitals in Japan. During 2004 to 2010, 70,683 patients with trauma aged ≥15 years were eligible for enrolment. The main outcome measures were survival until hospital discharge after POA, and propensity score analyses were used to adjust for patient factors and hospital site.Of 32,225 trauma patients, 19,985 (62.0%) were administered oxygen by the emergency medical services in prehospital settings and 12,240 (38.0%) did not receive oxygen. Overall, 29,555 patients (90.7%) survived till hospital discharge. In the multivariable unconditional logistic regression, POA had an odds ratio (OR) of 0.33 (95% confidence interval [CI], 0.30–0.37; P <.001) for favorable in-hospital mortality. Furthermore, there were significant differences in all the important variables between the POA and no POA groups (P <.001); therefore, we used propensity score matching analysis. After adjustment for the covariates of selected variables, we found that POA was not associated with a higher rate of survival after hospitalization (adjusted OR, 1.02; 95% CI, 0.99–1.04; P = .27). Even after adjustment for all covariates, POA did not improve in-hospital mortality (adjusted OR, 1.01; 95% CI, 0.99–1.03; P = .08).In this study, POA did not improve in-hospital mortality in trauma patients. However, further studies are needed to validate our results.