Outcomes and associated factors of traumatic brain injury among adult patients treated in Amhara regional state comprehensive specialized hospitals

Effect of Transcranial Direct Current Stimulation on Memory and Emotional Recovery in Patients with Stroke and Traumatic Brain Injury: A Prospective, Multicenter, Interventional Pilot Study

Background/Objectives: Emotional and cognitive impairments are prevalent in patients with acute ischemic stroke (AIS) and traumatic brain injury (TBI), significantly affecting their quality of life and recovery potential. Transcranial direct current stimulation (tDCS) has emerged as a promising non-invasive method to enhance neurorehabilitation outcomes by modulating neural activity. Methods: This prospective, open-label, multicenter interventional study included 100 participants (50 AIS, 50 TBI) who underwent 10 sessions of tDCS. Emotional states, depression levels, and memory and learning outcomes were assessed pre- and post-intervention using the UWIST Mood Adjective Checklist (UMACL), Depression Measurement Questionnaire (DMQ), Benton Visual Retention Test (BVRT), and Brain Damage Diagnostic Test (BDDT). Results: Significant improvements in emotional states were observed post-tDCS. Hedonic tone increased (AIS: 2.5 to 5 stens; TBI: 1.5 to 4 stens), while tension arousal decreased (AIS: 8 to 6 stens; TBI: 8 to 6 stens; all p < 0.001). Depression levels dropped significantly, with the overall depression index decreasing from 131 to 100 points in AIS and from 126 to 104 points in TBI (both p < 0.001). Memory and learning scores improved significantly, evidenced by increased correct responses and reduced errors in BVRT and BDDT tests (all p < 0.001). Conclusions: tDCS effectively improved emotional states, reduced depression levels, and enhanced cognitive functions in AIS and TBI patients. These findings support the integration of tDCS into neurorehabilitation protocols, with further research needed to explore long-term benefits and individualized treatment strategies.

Modified Early Warning Score (MEWS) combined with biomarkers in predicting 7-day mortality in traumatic brain injury patients in the emergency department: a retrospective cohort study

Background

Traumatic brain injury (TBI) is a leading cause of injury-related disability and death globally, which negatively affects individuals, families, and society. Predicting the risk for mortality among TBI patients is crucial in guiding further timely and effective treatment plans. Both the standard risk assessment tools and blood-based biomarkers are helpful in predicting outcomes among TBI patients. However, no studies have compared the predicting performance of the individual and combined indicators from the two major types.

Aim

This study aimed to compare the Modified Early Warning Score (MEWS), Red blood cell distribution width (RDW), and creatine in predicting 7-day mortality among TBI patients.

Methods

A retrospective study was conducted in the emergency department of the First People's Hospital of Changde, China, from January 1, 2023, to June 30, 2023. Data of 1,701 patients with TBI were obtained from the hospital's electronic medical records. A logistic regression model was used to determine independent factors influencing 7-day mortality. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) was calculated to compare the individual and combined effects of MEWS, RDW, and creatine in predicting 7-day mortality based on bootstrap resampling (500 times).

Results

Among the 1,701 patients, 225 died, with a mortality rate of 13.23%. The multivariate analysis showed that the type of TBI lesion, MEWS, SBP, DBP, MAP, SpO2, temperature, RDW, and creatine were significantly associated with 7-day mortality. MEWS (AUC: 0.843) performed better than RDW (AUC: 0.785) and creatine (AUC: 0.797) in predicting 7-day mortality. MEWS+RDW (AUC: 0.898) performed better than MEWS+creatine (AUC: 0.875) and RDW+ creatine (AUC: 0.822) in predicting 7-day mortality. The combination of all three indicators, MEWS+RDW+creatine, showed the best predicting performance (AUC: 0.906).

Conclusion

MEWS performed best in predicting the 7-day mortality of TBI patients, and its predicting performance was improved when combined with blood-based biomarkers such as RDW and creatine. Our findings provide preliminary evidence supporting the combination of MEWS with blood-based biomarkers as a new method for predicting 7-day mortality in patients with TBI.

Motorbike Accidents Involving Delivery Personnel at King Hamad University Hospital, Kingdom of Bahrain: A Retrospective Study

Background Motorcycles, favored for commercial commuting, offer the dual benefits of optimizing road system utilization and reducing environmental impact. However, the surge in home delivery services in Bahrain has led to an increase in motorcycle-related injuries. This study aimed to explore the effects of motorcycle accidents on delivery personnel, focusing on injury patterns, severity, and contributing factors. Methods This retrospective observational study analyzed 313 cases of delivery personnel involved in motorcycle accidents during their working hours at King Hamad University Hospital, Bahrain, from January 2016 to December 2019. Participants included delivery personnel aged 18-60 years with acute injuries from motorbike accidents who presented within 72 hours. Eligibility required complete medical records and employment verification. Cases involving incomplete data, fatalities before arrival, or accidents with other vehicles were excluded. Data sources included emergency department logs, hospital admission records, operative documents, and standardized forms. Variables included demographics, ambulance use, injury type and location, and interventions such as the need for CT scans, endotracheal intubation, blood transfusion, and trauma code activation. Group comparisons utilized chi-square test, Fisher's exact test, and Mann-Whitney U tests with significance set at p < 0.05. Subgroup analyses explored associations by age, injury type, and trauma code activation. Results The mean age of the patients was 30.1 ± 8.26 years, with more than half (N = 167, 53.4%) aged 30 years old or younger. Of all patients, 25 (8%) had trauma code activation, and 175 (55.9%) utilized an ambulance. The most common location of injury was the lower limb (N = 205, 65.5%), followed by the upper limb (N = 164, 52.4%) and the head (N = 64, 20.4%). The median (range) of hospital stay days was 1 (1-32) days. Abrasions were the major type of injury sustained by the patients (N = 233, 74.4%), followed by lacerations (N = 45, 14.4%). Ambulance use was significantly higher in patients with trauma code activation (p = 0.001), head injury (p = 0.042), and pelvic injury (p = 0.047). Blood transfusion was significantly higher among those with abdominal injury (p = 0.002). There were no fatalities recorded during the study period. Conclusions This study highlights the risks faced by young delivery personnel in Bahrain, with lower limb injuries and head trauma being prevalent. Despite the effectiveness of current trauma care protocols in managing injuries, gaps remain in preventing severe injuries. The research emphasizes the need for region-specific measures, such as mandatory helmet laws, the use of protective gear, and the establishment of safer routes for delivery personnel. Furthermore, local awareness campaigns about safe riding practices and enhanced training programs for delivery staff can play a crucial role in reducing injury risks. By providing unique data on injury patterns and trauma care in the Gulf region, the study contributes to improving road safety and trauma management while supporting further research and policy development tailored to the specific needs of delivery personnel in Bahrain.

Prediction analysis of TBI 24-h survival outcome based on machine learning

Background

Traumatic brain injury (TBI) is the major reason for the death of young people and is well known for its high mortality and morbidity. This paper aim to predict the 24h survival of patients with TBI.

Methods

A total of 1224 samples were involved in this analysis, and the clinical indicators involved included age, gender, blood pressure, MGAP and other fields, among which the target variable was "outcome", which was a binary variable. The methods mainly involved in this paper include data visualization analysis, single factor analysis, feature engineering analysis, random forest model (RF), K-Nearst Neighbors (KNN) model, and so on. Logistic regression model (LR) and deep neural network model (DNN). We will oversample the training set using the SMOTE method because of the very unbalanced labeling of the sample itself.

Results

Although the accuracy of all models is very high, the recall rate is relatively low. The DNN model with the best performance only reaches 0.17, and the corresponding AUC is 0.80. After resampling, we find that the recall rate of positive samples of all models has increased a lot, but the AUC of some models has decreased. Finally, the optimal model is LR, whose positive sample recall rate is 0.67 and AUC is 0.82.

Conclusion

Through resampling, we obtained that the best model is the RF model, whose recall rate and AUC are the best, and the AUC level is about 0.87, indicating that the accuracy performance of the model is still good.

Therapeutic benefits of quercetin in traumatic brain injury model exposed to cigarette smoke

Scientific evidences reported the deleterious effect of cigarette smoking or passive smoking on brain health particularly cognitive functions, blood-brain barrier (BBB) permeability, up-regulation of inflammatory cascades, and depletion of the antioxidant system. These combined effects become more progressive in the events of stroke, traumatic brain injury (TBI), and many other neurodegenerative diseases. In the current study, we investigated the long-term administered therapeutic potential of quercetin in ameliorating the deleterious neurobiological consequences of chronic tobacco smoke exposure in TBI mice. After exposure to 21 days of cigarette smoke and treatment with 50 mg/kg of quercetin, C57BL/6 mice were challenged for the induction of TBI by the weight drop method. Subsequently, a battery of behavioral tests and immunohistochemical analyses revealed the beneficial effect of quercetin on the locomotive and cognitive function of TBI + smoked group mice (p < 0.05 vs control sham). Immunohistochemistry analysis (Nrf2, HO-1, NFkB, caspase 3) demonstrated a marked protection after 21 days of quercetin treatment in the chronic tobacco smoking group possibly by up-regulation of antioxidant pathways, and decreased apoptosis. In conclusion, our findings support the therapeutic effectiveness of quercetin in partly protecting the central neurological functions that become aberrantly impaired in combined habitual cigarette-smoking individuals impacted with TBI.