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We aim to develop machine learning (ML) models for predicting the complexity and mortality of polytrauma patients using clinical features, including physician diagnoses and physiological data. We conducted a retrospective analysis of a cohort comprising 756 polytrauma patients admitted to the intensive care unit (ICU) at Pizhou People’s Hospital Trauma Center, Jiangsu, China between 2020 and 2022. Clinical parameters encompassed demographics, vital signs, laboratory values, clinical scores and physician diagnoses. The two primary outcomes considered were mortality and complexity. We developed ML models to predict polytrauma mortality or complexity using four ML algorithms, including Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN) and eXtreme Gradient Boosting (XGBoost). We assessed the models’ performance and compared the optimal ML model against three existing trauma evaluation scores, including Injury Severity Score (ISS), Trauma Index (TI) and Glasgow Coma Scale (GCS). In addition, we identified several important clinical predictors that made contributions to the prognostic models. The XGBoost-based polytrauma mortality prediction model demonstrated a predictive ability with an accuracy of 90% and an F -score of 88%, outperforming SVM, RF and ANN models. In comparison to conventional scoring systems, the XGBoost model had substantial improvements in predicting the mortality of polytrauma patients. External validation yielded strong stability and generalization with an accuracy of up to 91% and an AUC of 82%. To predict polytrauma complexity, the XGBoost model maintained its performance over other models and scoring systems with good calibration and discrimination abilities. Feature importance analysis highlighted several clinical predictors of polytrauma complexity and mortality, such as Intracranial hematoma (ICH). Leveraging ML algorithms in polytrauma care can enhance the prognostic estimation of polytrauma patients. This approach may have potential value in the management of polytrauma patients.

BACKGROUND: The early management of polytrauma patients with traumatic spinal cord injury (tSCI) is a major challenge. Sparse data is available to provide optimal care in this scenario and worldwide variability in clinical practice has been documented in recent studies. METHODS: A multidisciplinary consensus panel of physicians selected for their established clinical and scientific expertise in the acute management of tSCI polytrauma patients with different specializations was established. The World Society of Emergency Surgery (WSES) and the European Association of Neurosurgical Societies (EANS) endorsed the consensus, and a modified Delphi approach was adopted. RESULTS: A total of 17 statements were proposed and discussed. A consensus was reached generating 17 recommendations (16 strong and 1 weak). CONCLUSIONS: This consensus provides practical recommendations to support a clinician's decision making in the management of tSCI polytrauma patients.

Background and Objectives: Despite the potential benefits for the patient, aerospace interventions pose significant risks. Pre-hospital triage and patient transport are two essential elements for achieving an organized system of trauma. The advantages and disadvantages of using land transport from the scene of the accident to the trauma centers have been extensively studied, but there are gaps for air transport, and their exact level of efficiency is not known. Materials and Methods: The present study includes a total number of 77 patients, present at SMURD Galați air service for polytraumas caused by various mechanisms, with pluri-regional involvement. The identification of patients, as well as the selection of the most important anamnestic data, was performed after signing a confidentiality agreement; subsequently, all this information was introduced in centralized tables made in the statistical program IBM SPSS Statistics V24. Results: Out of the total of 77 polytraumatized patients who needed air transfer, an average age of 17.3 years will be noted, with a predominance of males in a 2:1 ratio. Most polytraumas are due to road accidents (74%) and patients with minimal tri-regional damage (51.4%). Conclusions: Taking into account the existing statistics in this research, it is important to implement prevention elements, designed based on the profile of the polytraumatized patient. Thus, accessing the most important characteristics of these patients can be an extremely important starting point in reducing the incidence of polytrauma or even patient deaths.

Traumatic brain injury (TBI) is a leading cause of death and disability, and there are currently no pharmacological treatments known to improve patient outcomes. Unquestionably, contributing toward a lack of effective treatments is the highly complex and heterogenous nature of TBI. In this review, we highlight the recent surge of research that has demonstrated various central interactions with the periphery as a potential major contributor toward this heterogeneity and, in particular, the breadth of research from Australia. We describe the growing evidence of how extracranial factors, such as polytrauma and infection, can significantly alter TBI neuropathology. In addition, we highlight how dysregulation of the autonomic nervous system and the systemic inflammatory response induced by TBI can have profound pathophysiological effects on peripheral organs, such as the heart, lung, gastrointestinal tract, liver, kidney, spleen, and bone. Collectively, this review firmly establishes TBI as a systemic condition. Further, the central and peripheral interactions that can occur after TBI must be further explored and accounted for in the ongoing search for effective treatments.

Background: Trauma is a leading cause of morbidity and mortality worldwide, often resulting in devastating physical, psychological, and social consequences. Nurses play an essential role in stabilizing patients, managing acute care, and ensuring continuity of treatment. Given the complexity of trauma care, continuous specialized training in nursing is crucial to enhance the quality of interventions and improve patient outcomes. Objective: We aimed to map and analyze nursing interventions in approaching trauma victims. Methods: This scoping review followed the methodology proposed by the Joanna Briggs Institute. The literature search was conducted in databases available on the EBSCOhost platform and in PubMed. The research question guiding this review was as follows: what nursing interventions are used to approach trauma victims? Results: Thus, 1454 articles were identified (348 from ESBOhost and 1106 from PubMed), with 13 meeting the inclusion criteria. The findings were categorized into six key areas: (1) Triage, (2) Initial Approach, (3) Secondary Approach, (4) Professional Training, (5) Interdisciplinary Collaboration, and (6) Care Maintenance. Conclusions: Trauma victims require immediate and complex care. Nurses are pivotal throughout all clinical phases, delivering physical and psychological support, collaborating with multidisciplinary teams, and advancing professional training and community education.

BackgroundTraumatic induced coagulopathy (TIC) is a key factor affecting the prognosis of patients with polytrauma. Early identification of patients at high risk for TIC and timely initiation of damage-control interventions are crucial. This study aims to develop and validate a predictive model for individualized estimation of TIC risk based on clinical characteristics and routine laboratory indicators.MethodsThis prospective cohort study included 183 adult patients, aged 18 to 85 years, with confirmed multiple injuries who presented to the emergency department of our hospital between July 1, 2023, and December 31, 2024. Patients were divided into a TIC group (n = 123) and a non-TIC group (n = 60) according to the occurrence of TIC. Candidate predictors were screened using univariate analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariable logistic regression to construct the model. Model performance was comprehensively evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA).ResultsFour core predictors were ultimately identified: emergency surgery, pH value, red blood cell count (RBC), and Injury Severity Score (ISS).The model demonstrated good discriminative ability (AUC = 0.903, 95% CI: 0.858–0.948).The optimal cut-off value determined by the Youden index was 0.651, with a sensitivity of 81.3% and a specificity of 86.7%.The calibration curve showed high agreement between predicted and observed risks. Decision curve analysis further indicated that the model provided favorable clinical net benefit across a wide range of threshold probabilities.ConclusionThe predictive model developed in this study showed promising ability to estimate individualized TIC risk in patients with polytrauma and may serve as an effective tool to optimize the allocation of medical resources and facilitate early diagnosis and intervention for traumatic coagulopathy.

ObjectiveThe aim of this study was to construct a novel nomogram prediction model and to investigate the value of the new predictors in predicting perioperative deep vein thrombosis formation in lower limb traumatic closed fracture (LTCF).MethodsIn this study, we reviewed data from 1,608 patients with LTCF, developed a new predictive model through analysis, and used Lasso regression to screen for the final reliable variables. Modeling was followed by using the ROC curve analysis, calculation of area under the ROC curve and Validation function. Calibration curves, decision curve analysis and clinical impact curves were used to comprehensively assess the performance of the model, and used to construct new predictors, inflammatory immune factors and traditional scores by using ROC analysis model, which was compared with the new predictive model.ResultsThe novel nomogram model was constructed with an AUC = 0.918, 95% CI: 0.894-0.942, C-index = 0.913. The new predictors (PHR and PDR), inflammatory-immune domain factors (NLR, PLR, and SII), and traditional scoring systems (Wells and Caprini) had AUC values of 0.689, 0.838, 0.552, 0.557, 0.542, 0.897, and 0.872.ConclusionThe novel nomogram model constructed in this study is feasible for predicting the occurrence of perioperative DVT in LTCF. PHR and PDR demonstrated superior predictive performance for perioperative DVT in LTCF patients, integrating platelet, metabolic, and fibrinolytic pathways. Associated inflammatory indices (NLR, PLR, SII) offered adjunctive risk assessment value. Threshold analysis indicated optimal performance at a 0.35 cutoff (F1 = 0.828), with perfect precision achievable at ≥0.65, highlighting the model's clinical adaptability through adjustable thresholds.

Purpose Although the term “major fracture” is commonly used in the management of trauma patients, it is defined insufficiently to date. The polytrauma section of ESTES is trying to develop a more standardized use and a definition of the term. In this process, a standardized literature search was undertaken. We test the hypothesis that the understanding of “major fractures” has changed and is modified by a better understanding of patient physiology. Methods A systematic literature search of the Medline and EMBASE databases was conducted in March 2022. Original studies that investigated surgical treatment strategies in polytraumatized patients with fractures were included: This included timing, sequence and type of operative treatment. A qualitative synthesis regarding the prevalence of anatomic regions of interest and core factors determining decision-making was performed. Data were stratified by decades. Results 4278 articles were identified. Of these, 74 were included for qualitative evaluation: 50 articles focused on one anatomic region, 24 investigated the relevance of multiple anatomic regions. Femur fractures were investigated most frequently (62) followed by pelvic (22), spinal (15) and tibial (15) fractures. Only femur (40), pelvic (5) and spinal (5) fractures were investigated in articles with one anatomic region of interest. Before 2010, most articles focused on long bone injuries. After 2010, fractures of pelvis and spine were cited more frequently. Additional determining factors for decision-making were covered in 67 studies. These included chest injuries (42), TBI (26), hemorrhagic shock (25) and other injury-specific factors (23). Articles before 2000 almost exclusively focused on chest injury and TBI, while shock and injury-specific factors (e.g., soft tissues, spinal cord injury, and abdominal trauma) became more relevant after 2000. Conclusion Over time, the way “major fractures” influenced surgical treatment strategies has changed notably. While femur fractures have long been the only focus, fixation of pelvic and spinal fractures have become more important over the last decade. In addition to the fracture location, associated conditions and injuries (chest trauma and head injuries) influence surgical decision-making as well. Hemodynamic stability and injury-specific factors (soft tissue injuries) have increased in importance over time.

Background Many factors of trauma care have changed in the last decades. This review investigated the effect of these changes on global all-cause and cause-specific mortality in polytrauma patients admitted to the intensive care unit (ICU). Moreover, changes in trauma mechanism over time and differences between continents were analyzed. Main body A systematic review of literature on all-cause mortality in polytrauma patients admitted to ICU was conducted. All-cause and cause-specific mortality rates were extracted as well as trauma mechanism of each patient. Poisson regression analysis was used to model time trends in all-cause and cause-specific mortality. Thirty studies, which reported mortality rates for 82,272 patients, were included and showed a decrease of 1.8% (95% CI 1.6–2.0%) in all-cause mortality per year since 1966. The relative contribution of brain injury-related death has increased over the years, whereas the relative contribution of death due to multiple organ dysfunction syndrome (MODS), acute respiratory distress syndrome, and sepsis decreased. MODS was the most common cause of death in North America, and brain-related death was the most common in Asia, South America, and Europe. Penetrating trauma was most often reported in North America and Asia. Conclusions All-cause mortality in polytrauma patients admitted to the ICU has decreased over the last decades. A shift from MODS to brain-related death was observed. Geographical differences in cause-specific mortality were present, which may provide region-specific learning possibilities resulting in improvement of global trauma care.

Tamer R Armanious,1 Ahmed A Khalifa,2 Hossam Abubeih,1 Mahmoud Badran,1 Faisal Fahmy Adam,1 Osama Farouk1 1Orthopaedic Department, Assiut University Trauma Hospital, Assiut, Egypt; 2Orthopaedic Department, Qena Faculty of Medicine and University Hospital at South Valley University, Qena, EgyptCorrespondence: Ahmed A Khalifa, Orthopaedic and Traumatology, Orthopaedic Department, Qena Faculty of Medicine and University Hospital, South Valley University, Qena, Egypt, Tel +201224466151, Email ahmedₐdel0391@med.svu.edu.egBackground: Abnormal admission blood glucose levels were proved to have a mortality predictive value in polytraumatized patients, as reported by studies in developed countries. Reports from developing countries are scarce.Objective: To evaluate the reliability of on-admission blood glucose levels in predicting mortality in polytraumatized patients presented to a North African (developing country) trauma center. The secondary objectives were to investigate other possible mortality predictors and if a cutoff value for each could be obtained.Methods: In this prospective longitudinal study, over one year, we included adult (≥ 18 years) patients who were polytraumatized (ISS ≥ 17) and presented to our trauma center within six hours of the trauma incident. Various clinical, laboratory, and trauma scores were collected. Blood glucose levels were assessed from blood samples obtained directly after admission. Patients were divided into five groups based on the admission blood glucose levels.Results: We included 202 patients, having a mean age of 44± 13.9 (20 to 70) years, and 52% were females. The mortality rate was 10.9% (including all patients presented with blood glucose levels≥ 15 mmol/L). The following were significant mortality predictors, admission blood glucose (OR=3.31, 95% CI=1.902– 5.763, p< 0.001), serum lactate levels (OR=4.017, 95% CI=1.627– 9.917, p=0.003), length of hospital stay (OR=1.18, 95% CI= 1.058– 1.305, p=0.003), RTS score (OR=1.43, 95% CI=1.023– 2.005, p=0.037), and TRISS score (OR=1.099, 95% CI=1.052– 1.148, p< 0.001). Admission blood glucose levels cutoff value of 15 mmol/L can significantly differentiate between survivors and non-survivors with sensitivity, specificity, PPV, and NPV of 86.4%, 100%, 100%, and 88%, respectively.Conclusion: Abnormal admission blood glucose with a cutoff value of 15mmol/L is a significant mortality predictor in polytraumatized patients from developing country trauma center, among other clinical, laboratory, and trauma scores parameters.Keywords: severely injured patients, polytrauma, admission blood glucose, hyperglycemia, mortality