PURPOSE: Trauma is well known as one of the main causes of death and disability throughout the world. Identifying the risk factors for mortality in trauma patients can significantly improve the quality of care and patient outcomes, as well as reducing mortality rates. METHODS: In this retrospective cohort study, systematic randomization was used to select 849 patients referred to the main trauma center of south of Iran during a period of six months (February 2017-July 2017); the patients' case files were evaluated in terms of demographic information, pre- and post-accident conditions, clinical conditions at the time of admission and finally, accident outcomes. A logistic regression model was used to analyze the role of factors affecting mortality among subjects. RESULTS: Among subjects, 60.4% were in the age-group of 15-39 years. There was a 10.4% mortality rate among patients and motor-vehicle accidents were the most common mechanism of injury (66.7%). Aging led to increased risk of fatality in this study. For each unit increase in Glasgow coma scale (GCS), risk of death decreased by about 40% (odds ratio (OR) = 0.63, 95% confidence interval (CI): 0.59-0.67). For each unit increase in injury severe score (ISS), risk of death increased by 10% (OR = 1.11%, 95% CI: 1.08-1.14) and for each unit increase in trauma revised injury severity score (TRISS), there was 18% decrease in the risk of fatality (OR = 0.82, 95% CI: 0.71-0.88). CONCLUSION The most common cause of trauma and the most common cause of death from trauma was traffic accidents. It was also found that an increase in the ISS index increases the risk of death in trauma patients, but the increase in GCS, revised trauma score (RTS) and TRISS indices reduces the risk of death in trauma patients. The TRISS indicator is better predictor of traumatic death than other indicators.

Background: Pulmonary thromboembolism (PTE) is a significant contributing factor to vascular diseases.This study aimed to determine the prevalence of pulmonary thromboembolism and its predisposing factors in patients with COVID-19. Methods: This cross-sectional study included 284 patients with COVID-19 who were admitted to Nemazee Teaching Hospital (Shiraz, Iran) between June and August 2021. All patients were diagnosed with COVID-19 by a physician based on clinical symptoms or positive polymerase chain reaction (PCR) test results. The collected data included demographic data and laboratory findings. Data were analyzed using the SPSS software. P ≤0.05 was considered statistically significant. Results: There was a significant difference in the mean age between the PTE group and non-PTE group (P=0.037). Moreover, the PTE group had a significantly higher prevalence of hypertension (36.7% vs. 21.8%, P=0.019), myocardial infarction (4.5% vs. 0%, P=0.006), and stroke (23.9% vs. 4.9%, P =0.0001). Direct bilirubin (P =0.03) and albumin (P =0.04) levels significantly differed between the PTE and non-PTE groups. Notably, there was a significant difference in the partial thromboplastin time (P =0.04) between the PTE and non-PTE groups. A regression analysis indicated that age (OR, 1.02; 95% CI, 1.00‒1.004; P =0.005), blood pressure (OR, 2.07; 95% CI, 1.12‒3.85; P=0.02), heart attack (OR, 1.02; 95% CI, 1.28‒6.06; P =0.009), and albumin level (OR, 0.39; 95% CI, 0.16‒0.97; P =0.04) were all independent predictors of PTE development. Conclusion Regression analysis revealed that age, blood pressure, heart attack, and albumin levels were independent predictors of PTE.

Objectives: Machine learning has been widely used to predict diseases, and it is used to derive impressive knowledge in the healthcare domain. Our objective was to predict in-hospital mortality from hospital-acquired infections in trauma patients on an unbalanced dataset. Methods: Our study was a cross-sectional analysis on trauma patients with hospital-acquired infections who were admitted to Shiraz Trauma Hospital from March 20, 2017, to March 21, 2018. The study data was obtained from the surveillance hospital infection database. The data included sex, age, mechanism of injury, body region injured, severity score, type of intervention, infection day after admission, and microorganism causes of infections. We developed our mortality prediction model by random under-sampling, random over-sampling, clustering (k-mean)-C5.0, SMOTE-C5.0, ADASYN-C5.5, SMOTE-SVM, ADASYN-SVM, SMOTE-ANN, and ADASYN-ANN among hospital-acquired infections in trauma patients. All mortality predictions were conducted by IBM SPSS Modeler 18. Results: We studied 549 individuals with hospital-acquired infections in a trauma hospital in Shiraz during 2017 and 2018. Prediction accuracy before balancing of the dataset was 86.16%. In contrast, the prediction accuracy for the balanced dataset achieved by random under-sampling, random over-sampling, clustering (k-mean)-C5.0, SMOTE-C5.0, ADASYN-C5.5, and SMOTE-SVM was 70.69%, 94.74%, 93.02%, 93.66%, 90.93%, and 100%, respectively. Conclusions Our findings demonstrate that cleaning an unbalanced dataset increases the accuracy of the classification model. Also, predicting mortality by a clustered under-sampling approach was more precise in comparison to random under-sampling and random over-sampling methods.

PURPOSE: Trauma is a major health concern. Length of hospital stay (LOS) has been targeted as an important metric to assess trauma care. This study aims to evaluate the risk factors that affect LOS among trauma patients in a trauma center in Southwestern Iran. METHODS: This cross-sectional study was conducted on patients admitted to Rajaee Trauma Center, Shiraz, Iran between January 1, 2018 and December 30, 2018. The inclusion criteria were age above 15 years and having traffic accident injuries, including car, motorcycle and pedestrian injury mechanisms. The exclusion criteria were existing diseases including cardiovascular, cerebral, renal, and pulmonary diseases prior to this study, dead upon arrival or within 48 h after admission, and stay at the hospital for less than 6 h. The risk variables analyzed for prolonged LOS were age, gender, mechanism of traffic accident injury, infection during hospital stay, type of injury, injury severity score, surgery during hospitalization, and survival. Poisson regression was performed to evaluate the partial effects of each covariate on trauma hospitalization (≥3 days as longer stay). RESULTS: This study was conducted on 14,054 patients with traffic accident injury and the mean age was (33.89 ± 15.78) years. Additionally, 74.35% of the patients were male, with male to female ratio of 2.90. The result of Poisson regression indicated that male patients, higher age, combination of thoracic injuries, onset of infected sites, and surgery patients were more susceptible to have a longer LOS. Considering the site of injury, patients with face injuries followed by those with thorax injuries had the highest means of LOS (3.74 days and 3.36 days, respectively). Simultaneous existence of surgical intervention and infection in a patient had the greatest impact on prolonged LOS. CONCLUSION This study identified that age, gender, mechanism of injury, infection, type of injury, survival, and ISS could lead to prolongation of LOS, but the affect can be reduced by eliminating modifiable risk factors.
Accidental Injuries ; Accidents, Traffic ; Adult ; Age Factors ; Facial Injuries ; Female ; Humans ; Iran ; Length of Stay ; statistics & numerical data ; Male ; Middle Aged ; Risk Factors ; Sex Factors ; Thoracic Injuries ; Wound Infection ; Young Adult

PURPOSE: After car accident, motorcycle accident ranks as the second leading cause of traffic fatality in Iran. This study aimed to compare the severity and clinical presentations between drivers and passengers under the same injury circumstance. METHODS: This study was conducted in the trauma center of Shiraz, Iran in 2017. Data on demographics, triage level, blood pressure, respiratory rate, Glasgow coma scale (GCS), injured body region, injury severity score (ISS), revised trauma score (RTS), and result of accident were compared between pairs of drivers and passengers. The agreement of any type of injury between drivers and passengers evaluated by Kappa test. RESULTS: This study included 143 matched pairs of drivers and passengers. Most of the pairs (84.5%) did not use helmet and 77.2% of the riders do not have driving license. ISS was significantly higher in drivers than passengers. In the unmatched pairs, drivers and passengers showed no difference in sustaining injuries in the face, head & neck, chest and soft tissue, but drivers were found more likely to suffer from injuries in the abdomen, extremities, pelvis and spine than passengers. Once one part of the matched pair suffered injury in the head & neck, face, chest, abdomen, extremities and soft tissue & skin injury, the probability that the other part had an injury in the same region was 50%, 9%, 13%, 7%, 22% and 34% respectively. Kappa value for these body regions was 0.006, 0.009, -0.006, 0.068, 0.063 and 0.001, respectively, which was significant in abdomen and extremities. CONCLUSION Although drivers had higher level of injury severity and some different injury distributions, we recommend equal treatment to drivers and passengers. We also recommend related authorities to develop policies on helmet use, driving license and third-party insurance.

PURPOSETrauma-related injuries are the leading cause of death worldwide. Some risk factors make traumatic patients susceptible to infection. Furthermore, some mortality risk factors, including length of hospitalization and increasing age, were detected in non-traumatic infected patients. This study aimed to assess mortality risk factors among nosocomial infected traumatic patients in Rajaee trauma center, Shiraz, Iran.

METHODSThis prospective cohort study was conducted during a period of 2 years since April 2015 to March 2017 in Rajaee hospital, which is the center of emergency medical services for traumatic injuries in Shiraz, Iran. Centers for Disease Control and Prevention/National Healthcare Safety Network surveillance system criteria were applied to define 5 types of nosocomial infections. The variables analyzed as the risk factors of infection and mortality included sex, age, mechanism of injury, site of injury, injury severity score (ISS), surgical intervention, length of hospitalization, intensive care unit (ICU) admission, and type of pathogen. Then, the incidence of nosocomial infection and also risk factors of mortality in traumatic patients were evaluated. All data analyses were performed using the statistical package for social sciences, version 15 (SPSS Inc., Chicago) and p ≤ 0.05 is considered to be statistically significant.

RESULTSThe incidence of nosocomial infection was 7.2% (p < 0.001). Pneumonia was the most common type of infection detected in our study. Infection led to a 7.8-fold increase in mortality of the traumatic patients (p < 0.001). Admission in intensive care units and old age were the main risk factors of mortality in infected traumatic patients. Old age, gunshot and motor vehicle accidents, trauma to extremities and abdomen, higher injury severity score, and prolonged hospitalization, made the traumatic patients more susceptible to infection.

CONCLUSIONThe really high incidence of nosocomial infection in traumatic patients in Iran depends on some risk factors that should be considered. Also infection increases the mortality rate in the traumatic patients, which could be reduced by eliminating its risk factors.

PURPOSE: Nosocomial infection is a major threat to the health care system and patient welfare. After the pandemic, new protocols were established in hospitals and communities to protect against the transmission of COVID-19, which may have changed the incidence of nosocomial transmission. This study was conducted to compare the incidence of nosocomial infection before and after the COVID-19 pandemic. METHODS: This was a retrospective cohort study performed on trauma patients who were admitted, from May 22, 2018 to November 22, 2021, to the largest level-1 trauma center in Shiraz, Iran (Shahid Rajaei Trauma Hospital). All the trauma patients over 15 years old admitted during the study time were included in this study. Individuals who were declared dead upon arrival were excluded. Patients were evaluated in 2 periods: before the pandemic (May 22, 2018 - February 19, 2020) and after the pandemic (February 19, 2020 - November 22, 2021). Patients were assessed based on demographic information (age, gender, length of hospital stay, and patient outcome), the occurrence of hospital infection, and the type of infection. The analysis was done using SPSS version 25. RESULTS: Overall, 60,561 patients were admitted, with a mean age of 40 years. Nosocomial infection was diagnosed in 4.00% (n = 2423) of all admitted patients. The incidence rate of post-COVID-19 hospital-acquired infections decreased by 16.28% (p < 0.001) when compared to before the pandemic; in contrast, surgical site infection (p < 0.001) and urinary tract infection (p = 0.043) were responsible for this change, while hospital-acquired pneumonia (p = 0.568) and bloodstream infection (p = 0.156) were not significantly different. Overall mortality was 1.79%, while 28.52% of all patients with nosocomial infections died. During the pandemic, there was a 25.78% increase (p < 0.001) in the overall incidence rate of mortality, which was also observed among patients with nosocomial infections (17.84%). CONCLUSION The incidence of nosocomial infection has decreased during the pandemic, possibly due to the use of more personal protective equipment and modified protocols after the outbreak. This also explains the difference in the change in incidence rates of nosocomial infection subtypes.
Humans ; Adult ; Adolescent ; Cross Infection/prevention & control* ; Incidence ; Retrospective Studies ; COVID-19/epidemiology* ; Pandemics/prevention & control* ; Prospective Studies ; Infection Control

PURPOSEThe administrative data from trauma centers could serve as potential sources of invaluable information while studying epidemiologic features of car accidents. In this cross-sectional analysis of Shahid Rajaee hospital administrative data, we aimed to evaluate patients injured in car accidents in terms of age, gender, injury severity, injured body regions and hospitalization outcome in the recent four years (2011-2014).

METHODSThe hospital registry was accessed at Shiraz Trauma Research Center (Shiraz, Iran) and the admission's unit data were merged with the information gathered upon discharge. A total number of 27,222 car accident patients aged over 15 years with International Classification of Diseases 10th revision (ICD-10) external causes of injury codes (V40.9-V49.9) were analyzed. Injury severity score and injured body regions were determined based on converting ICD-10 injury codes to Abbreviated Injury Scale (AIS-98) severity codes using a domestically developed electronic algorithm. A binary logistic regression model was applied to the data to examine the contribution of all independent variables to in-hospital mortality.

RESULTSMen accounted for 68.9% of the injuries and the male to female ratio was 2.2:1. The age of the studied population was (34 ± 15) years, with more than 77.2% of the population located in the 15-45 years old age group. Head and neck was the most commonly injured body region (39.0%) followed by extremities (27.2%). Injury severity score (ISS) was calculated for 13,152 (48.3%) patients, of whom, 80.9% had severity scores less than 9. There were 332 patients (1.2%) admitted to the intensive care units and 422 in-hospital fatalities (1.5%) were recorded during the study period. Age above 65 years [OR = 7.4, 95% CI (5.0-10.9)], ISS above 16 [OR = 9.1, 95% CI (5.5-14.9)], sustaining a thoracic injury [OR = 7.4, 95% CI (4.6-11.9)] and head injury [OR = 4.9, 95% CI (3.1-7.6)] were the most important independent predictors of death following car accidents.

CONCLUSIONHospital administrative databases of this hospital could be used as reliable sources of information in providing epidemiologic reports of car accidents in terms of severity and outcomes. Improving the quality of recordings at hospital databases is an important initial step towards more comprehensive injury surveillance in Fars, Iran.

Accidents, Traffic ; Adolescent ; Adult ; Aged ; Automobile Driving ; Cross-Sectional Studies ; Female ; Hospital Mortality ; Humans ; Injury Severity Score ; Iran ; epidemiology ; Logistic Models ; Male ; Middle Aged ; Registries ; Wounds and Injuries ; epidemiology

PURPOSE: Spine injury is one of the leading causes of death and mortality worldwide. The objective of this study was to determine the incidence, pattern and outcome of trauma patients with spine injury referred to the largest trauma center in southern Iran during the last 3 years. METHODS: This is a cross-sectional study conducted between March 2018 and June 2021 in the largest trauma center in the southern Iran. The data collection form included the age, sex, injury location (cervical, thoracic, and lumbar), cause of injury (traffic accidents, falls, and assaults), length of hospital stay, injured segment of spine injury, severity of injury, and outcome. Statistical analyzes were performed using SPSS software version 24. RESULTS: Totally 776 cases of spine injury were identified. The spine injury rate was 17.0%, and the mortality rate was 15.5%. Cervical spine injury (20.4%) more often occulted in motorcycle accident, and thoracic spine injury (20.1%) occulted in falls. The highest and lowest rates of spine injurys were related to lumbar spine injury (30.2%) and cervical spine injury (21.5%), respectively. There was a statistically significant relationship between the mechanism of injury and the location of spine injury (p < 0.001). And patients with lumbar spine injury had the highest mortality rate (16.7%). Injury severity score (OR= 1.041, p < 0.001) and length of stay (OR = 1.018, p < 0.001) were strong predictors of mortality in trauma patients with spine injury. CONCLUSION The results of the study showed that the incidence of traumatic spine injury rate was approximately 17.0% in southern of Iran. Road traffic injury and falls are the common mechanism of injury to spine. It is important to improve the safety of roads, and passengers, as well as work environment, and improve the quality of cars. Also, paying attention to the pattern of spine injury may assist to prevent the missing diagnosis of spine injury in multiple trauma patients.
Humans ; Incidence ; Trauma Centers ; Iran/epidemiology* ; Cross-Sectional Studies ; Spinal Injuries/etiology* ; Neck Injuries ; Accidents, Traffic