Archives of Trauma Research
Volume:12 Issue: 2, Apr-Jun 2023

Dear Editor Traumatic brain injury (TBI) is a harmful condition that permanently or temporarily damages brain functions and imposes enormous costs on health systems. Computed tomography (CT) scan is the preferred modality to detect injuries and determine TBI patients' prognoses in emergency departments. Thus far, some scoring systems have been introduced for grading TBI based on CT scan findings, including the Marshal,[1] Rotterdam,[2] Helsinki,[3] Stockholm,[4] and NeuroImaging Radiological Interpretation System (NIRIS) [Table 1].[5] This letter aims to briefly raise issues regarding the scoring of epidural hematoma (EDH) in CT scan-based scoring systems of TBI.Epidural hematoma is the gathering of blood between the dura mater and the skull. This intracranial hematoma usually occurs following the bleeding from the middle meningeal artery and, less commonly, from the dural venous sinuses.[6] Some studies have shown that EDH positively affects the outcome, so patients with EDH would have a better overall prognosis.[2] A typical EDH's prognosis is good if diagnosed early and managed before deterioration. Gennarelli et al., showed that the EDH death rate is approximately one-tenth of subdural hematoma.[7] Bricolo et al., reported that mortality should be zero in uncomplicated EDH.[8]On the other hand, EDH can be potentially life-threatening. EDH of venous origin can gradually spread, and its findings may appear late, leading to a delayed diagnosis and treatment. Consequently, EDH expansion can lead to herniation, permanent neurological damage, and death.[9] EDH with a size greater than 30 ml or a midline shift of more than 10 mm does not have a good prognosis.[9] The swirl sign indicating active bleeding also worsens the prognosis.[10]The presence or absence of EDH is evaluated in four CT scan-based scoring systems of TBI [Table 1]. Three scoring systems, including Rotterdam, Helsinki, and Stockholm, consider the presence of EDH as a favorable prognostic factor, i.e., patients with EDH on their brain CT scans get a lower score. However, in the NIRIS, EDH is scored as an adverse prognostic factor based on its volume, leading to a higher score.Hence, EDH cannot always be a favorable prognostic indicator. For instance, the presence of EDH along with diffuse axonal injury (DAI) worsens the outcome.[11] However, according to Rotterdam, Helsinki, and Stockholm systems, the association of EDH with DAI would have a lower score than DAI alone. Besides, high-volume EDH can worsen the situation by causing a midline shift and brain herniation.[9] Nonetheless, the specific size of EDH is not checked in any of these three systems.The scoring systems have been developed from the statistical weighting of variables. However, it is necessary to look at the issue more dynamically and comprehensively for a more accurate outcome prediction. Adjusting CT scoring systems with clinical characteristics and scales such as the Glasgow Coma Scale (GCS) and head injury biomechanics may also be helpful.

Emergency Trauma Score (EMTRAS), Revised Trauma Score (RTS) and Glasgow Age Pressure (GAP) are used to determine the patient status, and to predict the intervention and prognosis. The aim of the present study was to evaluate the association between mortality and trauma severity scores (EMTRAS, RTS, and GAP) in multiple trauma patients. In this study, patients who had referred to the Emergency Department of Mustafa Kemal University Hospital due to multiple trauma within a one-year period were evaluated retrospectively. The hospital is located in the central district of Hatay, Antakya in the Republic of Turkey, 680 km from the capital, on the Syrian border. Its population is 1,5 million. Antakya is located as the central district of Hatay with population of 400,000. Demographic data, trauma type, nationality, vital parameters [pulse, peripheral oxygen saturation (SO2), respiratory count, systolic blood pressure (SBP), diastolic blood pressure (DBP)], physiological scoring systems (GCS, RTS, GAP and EMTRAS), and mortality states of the patients were reviewed. Data were analysed by SPSS 21, and the effect of current parameters on short-term (in the emergency service) and long-term (30 days) mortality was examined. Three hundred and thirty-three multi-trauma patients were enrolled into the study. The median age of the patients was 31 (IQR: 22) years; 88.3% (294) of the patients were male. The exitus rate was detected as 7.8% in the emergency service and 26.4% within one month. GCS, RTS and GAP values of the patients who have died in the emergency service and within one month were significantly lower; however, the EMTRAS level was significantly higher in these patients (p<0.05). RTS and EMTRAS were detected as short- and long-term independent variables for mortality (p<0.05). After Receiver Operating Characteristic (ROC) analysis, the areas under the curve (AUC) of GCS, GAP, RTS and EMTRAS for short-term mortality were 0.861cm2, 0.876 cm2, 0.901cm2 and 0,917cm2, respectively; the AUC of such parameters for long-term mortality was detected 0.896cm2, 0.904 cm2, 0.914cm2and 0.899cm2, respectively. EMTRAS values were detected more significant parameters for short-term mortality whereas RTS was more significant for long-term mortality in multiple trauma patients. Such two scores may be useful to predict the patient prognosis along with GCS or solely.

Muscle-sparing thoracotomy (MST) has been proposed as an alternative to standard posterolateral thoracotomy (sPLT) for elective thoracic procedures with limited use in urgent thoracotomies. The aim of this study was to compare the results of sPLT and MST during urgent thoracotomy for the treatment of chest trauma. This case series study included patients who underwent urgent thoracotomies within the first 48 hours of admission for treatment of chest trauma, from January 2019 to July 2022. Patients were divided into two groups: sPLT and MST groups. In addition, the MST group was divided into partial (pMST) or complete (cMST).‎ Seventy-five out of 1400 patients with chest trauma (5.3%) underwent urgent thoracotomy, and 30 of them (40%) had MST. Compared with the sPLT group, the MST group had a lower abbreviated injury scale (AIS) of the thoracic region, with a significant difference (4.09 ± 0.66 versus 3.77 ± 0.72, P = 0.052). There was no significant difference between the two groups with regard to the duration of tube drainage, ICU stay, hospital stay, and postoperative complications. The length of hospital stay was shorter in the MST group with no statistically significant difference (14.30 ± 3.01 vs. 15.5 ± 2.48, P = 0.08). The extent of MST, whether partial or complete, had no significant effect on postoperative outcomes. If it does not impede access or chest exposure, MST can be performed with early recovery and therefore a shorter hospital stay than sPLT.

Non-operative management (NOM) has shown success in the management of cases of blunt abdominal trauma (BAT), especially in hemodynamically stable patients, even if there is a higher grade of injury. The aim of this study was to determine the healing rate with NOM and associated risk factors of non-healing in patients with BAT. This prospective study was conducted on 20 hemodynamically stable patients of BAT who were treated in a tertiary care hospital by NOM. Clinical monitoring and biochemical investigations were done. The patients were followed-up for three months. The outcome measures were the average time of healing and complications. A p-value less than 0.05 was considered statistically significant. The mean age of the patients was 24.5 years with 18 (90%) males and 2(10%) females. Nine patients (45%) had isolated liver injury, 8 (40%) had isolated splenic injury, 1 (5%) had isolated left renal injury, 1 (5%) had combined liver and splenic injury and 1 (5%) had combined liver and right renal injury. At 3 months of follow-up, 16 (80%) cases showed complete healing, 3(15%) showed incomplete healing and 1 (5%) patient with grade 4 splenic injury had failure of NOM. On performing univariate regression analysis, grade 3/4 was an independent risk factor of non-healing with an odds ratio of 5.667. In conclusion, NOM appears to be a safe and effective management protocol for patients with BAT, provided regular follow-ups and monitoring are done.

There are many debates on socioeconomic indicators influencing trauma outcomes. This study aimed to determine the association between education as a socioeconomic indicator and trauma outcomes. This descriptive-analytical study was conducted on 30,448 trauma patients during 2016-2021. The data were based on the minimum dataset of the National Trauma Registry of Iran (NTRI) from six different trauma centers in various cities of the country. The variables used in this study included age, education level, marital status, cause of injury, Glasgow Coma Scale (GCS), intensive care unit (ICU) admission, Injury Severity Score (ISS), and in-hospital mortality. Logistic regression was used to investigate the association between independent variables and trauma outcomes. The study included 30,448 trauma patients with male predominance (75.8%). The mean age was 36.9 years. The most frequent education level was secondary education, with 14,228 (46.6%). Education levels had significant relationships with ISS, death, and ICU admission (P<0.001). Moreover, after applying the multiple logistic regression, the odds of deaths for trauma patients with no formal, primary, and secondary education levels were 3.36, 5.03, and 3.65 times, respectively, more than the odds of deaths at the higher education level after controlling for other factors (all Ps<0.05). However, there were no such relationships between education levels and the odds of ICU admission. Findings of the present study showed a significant association between the education levels and trauma outcomes. Adjusted for other covariates, the chance of death for trauma patients with no formal, primary, or secondary education levels was higher than that at the higher education level.

The femur is the longest bone in the body. Injury or fracture in this bone strongly affects the quality of life of people. The aim of this study was to investigate the morphometric parameters of femur proximal part and its relationship with body mass index (BMI). This descriptive-analytical study was conducted on 200 patients over 50 years of age referred to Shahid Beheshti Hospital in Kashan and Ayatollah Kashani Hospital in Isfahan during 2018-2019. The participants had radiographs in the supine position of femur proximal part. BMI and bone mineral density of patients were determined by the DXA method. Using radiographic images of the femur, the morphological features were evaluated. Also, the relationship of these characteristics with age, gender, BMI and bone mineral density was investigated. The values of six morphological parameters of the femur in the patients under study were Q-angle=121.93±3.78, TW=86.06±7.65, HW=52.4±4.69, FW=37.74±4.29, HAL=118.43±10.47 and FAL=105.34±7.59 mm, which were higher in men. There was a direct and significant correlation of 23% between age and TW, which was significant according to the Pearson Correlation Test (P=0.039). Inverse correlation of 14% was observed between HAL width and BMI, which was statistically significant (P=0.042). FAL variable had a decreasing trend with decreasing BMD (P=0.031). Proximal femur characteristics were significantly related to factors such as gender and BMI. The morphological specifications of femur proximal were higher in men than in women. Compared to evaluations in other regions, the included characteristics are distinct from other countries, which these differences can be caused by genetic characteristics, environment, nutritional status, and lifestyle.

Many surgical treatment methods have been presented for Kienböck's disease. The most current treatment method is the surgical procedure with 4+5 extensor compartmental artery (ECA) bone graft. However, the graft harvest site is very close to the radioulnar and radiocarpal joints. This study aimed at determining the efficacy of intraoperative fluoroscopy evaluation of 4+5 ECA. Intraoperative fluoroscopic visualization of the 4+5 ECA may facilitate the surgical procedure. Patients with lunate avascular necrosis at stage II-IIIA according to Lichtman classification who underwent 4+5 ECA bone graft were included in the study. A total of 13 patients (3 females, 10 males) participated in the study. The mean follow-up period of the patients was 15 months. In all patients, 4+5 ECA localizations were determined fluoroscopically. None of the patients experienced complications related to graft harvest. Locating the intraoperative fluoroscopic 4+5 ECA may make the surgical procedure safer.

Mandibular fractures are a common trauma in oral and maxillofacial surgery. The accurate diagnosis of these fractures is crucial for successful treatment. However, the interpretation of radiographic scans can be time-consuming and prone to human error. The advent of artificial intelligence (AI), specifically Convolutional Neural Networks (CNNs), has opened up new possibilities for improving the accuracy and efficiency of fracture detection.

This review aims to explore the role of AI in detecting mandibular fractures.

A comprehensive literature search was performed using PubMed, Embase, Web of Science, and Google Scholar databases. Studies were included if they used AI techniques, specifically CNNs or transformers, for the detection of mandibular fractures.

The systematic search yielded 53 studies, with eight studies meeting the inclusion criteria. The AI models across these studies demonstrated a generally high degree of effectiveness in detecting mandibular fractures, with F1 scores ranging from 45% to 100%. Some studies also compared the diagnostic prowess of human clinicians and AI models, with AI models often matching or surpassing human performance.

The application of AI in detecting mandibular fractures represents a promising avenue of research. AI models have the potential to reduce the workload of radiologists, improve the efficiency of fracture detection, and lead to faster diagnosis and treatment. However, further research is needed to validate these findings in larger and more diverse datasets and to address challenges such as the interpretability of AI algorithms and the availability of large, well-annotated datasets.