This study aimed to develop a predictive model for the early identification of patients at risk of sepsis, using routinely available clinical information and laboratory test results collected during the initial phase of patient care. Methods: This retrospective analysis included electronic medical records of 22,400 adult patients who presented with suspected infection to a tertiary care university hospital in Korea between January 2013 and May 2024. Patients were classified according to Systemic Inflammatory Response Syndrome (score ≥ 2) or Quick Sequential Organ Failure Assessment (score ≥ 2), in combination with sepsis-related International Classification of Diseases, 10th revision codes. Four different machine learning models were trained and validated using five-fold cross-validation. In addition, Shapley additive explanations analysis was performed to interpret the contribution and clinical relevance of key predictive variables. Results: Among the evaluated models, CatBoost demonstrated the strongest predictive performance. Notably, platelet distribution width, alveolar–arterial oxygen difference, procalcitonin, and the arterial/alveolar oxygen ratio consistently emerged as major predictors. Importantly, several variables that did not reach statistical significance in univariate analysis nevertheless contributed substantially to overall model performance, highlighting the importance of complex, multidimensional interactions among clinical factors. Conclusion: These findings indicate that a model based on simple, routinely collected clinical data can achieve high predictive accuracy and strong generalizability. Such a tool may support early clinical decision-making by multidisciplinary teams, including nurses, across diverse real-world care settings. Further prospective studies are warranted to validate its clinical utility and to assess its potential effects on patient outcomes.

Venous leg ulcers (VLUs) represent the most advanced manifestation of chronic venous disease and arise from sustained ambulatory venous hypertension due to superficial reflux, deep venous obstruction, or both. Accurate etiologic assessment is essential, with duplex ultrasound serving as the primary tool to identify axial reflux, perforator incompetence, and signs of proximal outflow obstruction in accordance with contemporary ESVS and SVS/AVF guidelines. Compression therapy remains the foundation of treatment, with inelastic or adjustable compression systems providing the most effective pressure reduction and edema control. Optimal wound care—including moisturebalancing dressings, debridement, and judicious use of antimicrobials—supports timely epithelialization. Adjunctive pharmacologic agents such as micronized purified flavonoid fraction, pentoxifylline, and sulodexide may further enhance healing. Early correction of superficial reflux accelerates healing and reduces recurrence, as demonstrated in the Early Venous Reflux Ablation trial. Iliac venous obstruction should be considered in nonhealing or recurrent ulcers, with IVUS-guided stenting appropriate when significant stenosis is confirmed. Integrating guideline-directed venous intervention, optimized compression, and structured wound care is central to improving long-term outcomes in VLU management.

Objective: Early prediction of the multiple organ dysfunction syndrome (MODS) and providing early innovative treatment may improve outcomes in patients with severe trauma. Lactate and serum albumin levels, which are widely used markers predicting the severity of critically ill patients, tend to diverge during clinical deterioration. This study aimed to evaluate the clinical utility of the lactate/albumin ratio (LAR) as a predictive factor for MODS and 30-day mortality in patients with severe trauma. Methods: This retrospective, observational cohort study was performed with patients prospectively integrated into a critical pathway for trauma. We analyzed severe trauma patients (Injury Severity Score≥16) admitted to the emergency department (ED), between January 1, 2011, and May 31, 2017. The outcomes were the development of MODS and 30-day mortality. Results: In total, 348 patients were enrolled, of which 18 (5.2%) died within 96 hours of ED admission, and the remaining 330 patients (94.8%) were evaluated for the development of MODS. An increase in the LAR at admission (odds ratio, 1.618; P=0.028) was an independent predictor of MODS development. The area under the receiver operating characteristic curve (0.755) and Harrell's C-index (0.783) showed that LAR could predict MODS and 30-day mortality. Conclusion Initial LAR is an independent predictor of MODS development in patients with severe trauma. Our study results suggest that an elevated LAR can be a useful prognostic marker in patients with severe trauma.