Background: Severe traumatic brain injury (sTBI) in adults remains a leading cause of mortality and disability worldwide. Early identification of reliable predictors of outcome is crucial for risk stratification and ICU management. Disturbances of hemostasis and metabolic factors such as body mass index (BMI) have been proposed as potential prognostic markers, but evidence remains limited. Methods: We conducted a retrospective, multicenter study including 307 adult patients with sTBI (Glasgow Coma Scale ≤ 8) admitted to three tertiary intensive care units in Ukraine between September 2023 and July 2024. All patients underwent surgical evacuation of hematomas and decompressive craniotomy. Laboratory parameters (APTT, INR, fibrinogen, platelets, D-dimer) were collected within 12 h of admission. BMI was calculated from measured height and weight. Predictive modeling was performed using L1-regularized logistic regression and Random Forest algorithms. Class imbalance was addressed with SMOTE. Model performance was assessed by AUC, accuracy, calibration, and feature importance. Results: The 28-day all-cause mortality was 32.9%. Compared with survivors, non-survivors had significantly lower GCS scores and higher INR, D-dimer, and APTT values. Very high VIF values indicated severe multicollinearity between predictors. Classical logistic regression was not estimable due to perfect separation; therefore, regularized logistic regression and Random Forest were applied. Random Forest demonstrated higher performance (AUC 0.95, accuracy ≈ 90%) than logistic regression (AUC 0.77, accuracy 70.1%), although results must be interpreted cautiously given the small sample size and potential overfitting. Feature importance analysis identified increased BMI, prolonged APTT, and elevated D-dimer as leading predictors of mortality. Sensitivity analysis excluding BMI still yielded strong performance (AUC 0.91), confirming the prognostic value of coagulation markers and GCS. Conclusions: Mortality in adult sTBI patients was strongly associated with impaired hemostasis, obesity, and low neurological status at admission. Machine learning-based modeling demonstrated promising predictive accuracy but is exploratory in nature. Findings should be interpreted with caution due to retrospective design, severe multicollinearity, potential overfitting, and absence of external validation. Larger, prospective, multicenter studies are needed to confirm these results and improve early risk stratification in severe TBI.

Background/Objectives: Treatment of severe traumatic brain injury (TBI) remains a major challenge in neurocritical care. The functional state of the brain largely depends on the applied ventilation strategy. Many patients develop acute respiratory distress syndrome (ARDS), for which lung-protective ventilation is recommended. However, its effect on outcomes in severe TBI remains unclear. This study aimed to assess whether a lung-protective ventilation strategy improves short-term outcomes in patients with severe TBI complicated by ARDS. Methods: This multicenter retrospective study included patients with severe TBI and ARDS treated in three Ukrainian tertiary hospitals. Lung-protective ventilation was defined as the use of a low tidal volume and moderate positive end-expiratory pressure (PEEP). The primary endpoint was 28-day mortality; secondary endpoints included the Glasgow Coma Scale (GCS) score and intracranial pressure (ICP) on day 28. Univariate and multivariate logistic regression analyses identified factors associated with mortality. Results: Mortality did not depend on arterial PaO₂ (p = 0.173) but correlated with lower GCS (p < 0.001), reduced PaO₂/FiO₂ ratio (p < 0.001), higher tidal volume (p < 0.001), and lower PEEP (p < 0.001). Lung-protective ventilation reduced mortality from 78.6% to 31.4%. Conclusions: Lung-protective ventilation is safe and effective in severe TBI with ARDS, significantly improving short-term survival without compromising cerebral outcomes.

Background: Combat-related lower extremity injuries frequently require prolonged tourniquet application to control life-threatening hemorrhage. Although effective for hemorrhage control, prolonged ischemia followed by reperfusion substantially increases the risk of rhabdomyolysis, acute kidney injury (AKI), limb loss, and mortality. The optimal timing of anti-rhabdomyolysis infusion therapy in relation to tourniquet release remains uncertain. Methods: This retrospective single-center cohort study analyzed 120 Ukrainian military casualties with combat-related lower extremity injuries requiring prolonged tourniquet application and subsequent surgical management, including fasciotomy and tourniquet release. Patients were divided into two groups based on infusion strategy: standard therapy initiated after tourniquet release and early anti-rhabdomyolysis infusion therapy initiated before tourniquet removal during the ischemic phase. Primary outcomes included dialysis-requiring AKI, limb amputation, and death. Multivariable logistic regression models were adjusted for baseline physiological severity, including shock index at admission and baseline acid–base status. Model performance was evaluated using the Akaike Information Criterion (AIC) and receiver operating characteristic (ROC) analysis. Propensity score–based inverse probability of treatment weighting (IPTW) was applied as a sensitivity analysis. Results: After adjustment, early infusion therapy was independently associated with lower rates of dialysis-requiring AKI (adjusted odds ratio [OR] 0.33; 95% confidence interval [CI] 0.13–0.84; p = 0.020), limb amputation (OR 0.32; 95% CI 0.11–0.95; p = 0.040), and mortality (OR 0.23; 95% CI 0.07–0.77; p = 0.017). Adjusted models demonstrated good discriminative ability, with areas under the ROC curve of 0.813 for AKI, 0.838 for amputation, and 0.823 for mortality. Sensitivity analyses using IPTW yielded consistent results. Conclusions: In combat-related lower extremity injuries requiring prolonged tourniquet application, early initiation of anti-rhabdomyolysis infusion therapy prior to reperfusion is associated with significantly reduced risks of severe AKI, limb loss, and death. These findings suggest that preventive renal-protective strategies initiated before tourniquet release may improve outcomes in high-risk military trauma settings and warrant further prospective investigation.

Background: Severe traumatic brain injury (TBI) is associated with high mortality. There is increasing evidence suggesting that intestinal dysbiosis may influence clinical outcomes; however, its prognostic significance in patients with severe TBI remains poorly defined. Methods: This retrospective cohort study included 235 patients with severe TBI (Glasgow Coma Scale [GCS] score ≤ 8) admitted to the intensive care units of three participating hospitals between September 2023 and December 2024. Quantitative microbiological analysis of jejunal aspirates was performed at admission and repeated on days 12–14 of the ICU stay. Small intestinal bacterial overgrowth (SIBO) was defined as a bacterial load of ≥10⁵ colony-forming units per milliliter (CFU/mL). Multivariable logistic regression and receiver operating characteristic (ROC) curve analyses were performed. Results: At admission, SIBO was uncommon (3.8%) but increased to 27.9% among patients who underwent repeated assessment. Within the day-14 landmark cohort (n = 179), post-day-14 mortality was higher in patients with SIBO than in those without (34.0% vs. 23.3%). In multivariable logistic regression analysis, SIBO was independently associated with post-day-14 in-hospital mortality after adjustment for age, body mass index, GCS score, PaO₂/FiO₂ ratio, and blood glucose (OR 2.83, 95% CI 1.06–7.58; p = 0.039). The ROC model demonstrated good discriminative performance, with an apparent area under the curve (AUC) of 0.846 and an optimism-corrected AUC of 0.823 after bootstrap validation. Conclusions: In patients with severe TBI who survived and remained hospitalized through the day-14 landmark, SIBO detected at days 12–14 was independently associated with increased subsequent in-hospital mortality. However, its incremental contribution to discrimination beyond established clinical predictors was modest. Therefore, late SIBO should be interpreted primarily as a dynamic marker associated with prolonged critical illness and adverse outcome rather than as a demonstrated cause of mortality. Prospective validation is required.

Background: Severe traumatic brain injury (TBI) remains associated with high in-hospital mortality. Although classical clinical predictors are widely used, additional biomarkers reflecting systemic dysfunction may improve prognostic assessment. Small intestinal bacterial overgrowth (SIBO) may represent a late marker of critical illness. This study evaluated the prognostic value of SIBO compared with traditional predic-tors in severe TBI. Methods: In this retrospective cohort study, 174 patients with severe TBI (Glasgow Coma Scale ≤ 8) were included. Baseline clinical parameters were rec-orded at admission. Quantitative cultures of small intestinal aspirates were obtained at admission (colony-forming units per milliliter, CFU/mL; CFU1) and on days 12–14 (CFU14). Multivariable logistic regression, receiver operating characteristic (ROC), and landmark analyses were performed. Results: Age (OR 1.06 per year, 95% CI 1.03–1.10, p < 0.001), lower GCS (OR 0.48 per point, 95% CI 0.28–0.83, p = 0.008), and res-piratory dysfunction reflected by lower PaO₂/FiO₂ values independently predicted mortality. Late bacterial load >10⁵ CFU/mL showed a strong association with death (OR 5.15, 95% CI 2.15–12.34, p < 0.001). Baseline CFU1 was not significant. The model demonstrated good discrimination (AUC = 0.84). Landmark analysis confirmed higher post-day-14 mortality and delayed discharge with elevated CFU14. Conclusions: Late intestinal bacterial overgrowth is independently associated with mortality and may complement traditional predictors for risk stratification in severe TBI.