Background/Objectives: Sepsis remains a leading cause of mortality worldwide, necessitating the development of effective prognostic markers for early risk stratification. The C-reactive protein–albumin–lymphocyte (CALLY) index is a novel biomarker that integrates inflammatory, nutritional, and immunological parameters. This study aimed to evaluate the association between the CALLY index and 30-day all-cause mortality in sepsis patients. Methods: This retrospective cohort study included adult patients diagnosed with sepsis in the emergency department between 1 January 2022, and 1 January 2025. The CALLY index was calculated as (CRP × absolute lymphocyte count)/albumin. The primary outcome was 30-day all-cause mortality. Five machine learning models—extreme gradient boosting (XGBoost), multilayer perceptron, random forest, support vector machine, and generalized linear model—were developed for mortality prediction. Four feature selection strategies (gain score, SHAP values, Boruta, and LASSO regression) were used to evaluate predictor consistency. The clinical utility of the CALLY index was assessed using decision curve analysis (DCA). Results: A total of 1644 patients were included, of whom 345 (21.0%) died within 30 days. Among the five machine learning models, the XGBoost model achieved the highest performance (AUC: 0.995, R²: 0.867, MAE: 0.063, RMSE: 0.145). In gain-based feature selection, the CALLY index emerged as the top predictor (gain: 0.187), followed by serum lactate (0.185) and white blood cell count (0.117). The CALLY index also ranked second in SHAP analysis (mean value: 0.317) and first in Boruta importance (mean importance: 37.54). DCA showed the highest net clinical benefit of the CALLY index within the 0.10–0.15 risk threshold range. Conclusions: This study demonstrates that the CALLY index is a significant predictor of 30-day mortality in sepsis patients. Machine learning analysis further reinforced the prognostic value of the CALLY index.

Objectives: Identifying early predictors of dialysis requirements in earthquake-related injuries is crucial for optimal resource allocation and timely intervention. This study aimed to develop a predictive scoring system, named SAFE-QUAKE (Seismic Assessment of Kidney Function to Rule Out Dialysis Requirement), to identify patients at high risk of developing acute kidney injury (AKI) and requiring dialysis.Methods: A retrospective analysis was conducted on a cohort of 205 patients presenting with earthquake-related injuries. Patients were divided into two groups based on their need for dialysis: the no dialysis group (n = 170) and the dialysis group (n = 35). Demographic, clinical, and laboratory data were collected and compared between the two groups to identify significant predictors of dialysis requirements. The parameters that would form the score were determined by conducting an importance analysis using artificial neural networks (ANNs) to identify parameters that exhibited statistically significant differences in univariate analysis.Results: The dialysis group had a significantly longer median duration of being trapped under debris (48 hours) compared to the no dialysis group (eight hours). Blood gas and laboratory analyses revealed significant differences in pH levels, lactate values, creatinine levels, lactate dehydrogenase (LDH) levels, and aspartate transaminase (AST)-to-alanine transaminase (ALT) ratio between the two groups. Based on these findings, the SAFE-QUAKE rule-out scoring system was developed, incorporating entrapment duration (7.31), creatinine levels (<2mg/dL), LDH levels (<1600mg/dL), and the AST-to-ALT ratio (<2.4) as key predictors of dialysis requirements. This score included 139 patients, and among them, only one patient required dialysis, resulting in a negative predictive value of 99.29%.Conclusions: The SAFE-QUAKE scoring system demonstrated a high negative predictive value of 99.29% in ruling out the need for dialysis among earthquake-related injury cases. This scoring system offers a practical approach for health care providers to identify patients at high risk of developing AKI and requiring dialysis in earthquake-affected regions.

Objective:This case series aims to provide a comprehensive description of the utilization of doppler ultrasonography (USG) and computerized tomography angiography (CTA) in evaluating patients with earthquake-induced crush injuries in the emergency department (ED).Methods:This retrospective case series was conducted on 11 patients who presented with crush injuries following a seismic event. These patients underwent initial assessment using doppler USG, with CTA performed when deemed necessary. Clinical outcomes and diagnostic findings were systematically reviewed.Results:A cohort of 11 earthquake-related crush injury patients (six females, five males; age 3-59 years), predominantly with lower extremity injuries, with entrapped durations that ranged from 12 to 128 hours. Transport centers received patients from both affected regions and nearby provinces. Initial X-rays identified fractures in two cases. Doppler USG and subsequent CTA were employed for vascular evaluation, with CTA confirming doppler USG findings. Of the 11 patients, five exhibited abnormal doppler USG findings. Four patients required dialysis and four underwent amputation surgery. Fasciotomy and debridement procedures were performed in five and seven patients, respectively. Three patients received hyperbaric oxygen therapy (HBOT).Conclusion:Doppler USG emerged as a dependable tool for assessing vascular injuries in earthquake-related crush injuries, offering an effective alternative to CTA without the associated contrast agent risks. These findings underscore the need for further research to establish definitive imaging guidelines in these challenging clinical scenarios.

Objective: This study retrospectively evaluated the clinical, laboratory, and radiological predictors of 30-day mortality in patients with spontaneous intracerebral hemorrhage(ICH), along with the discriminative power of various inflammatory and prognostic indices. Materials and Methods: Between January 2022 and December 2024, the demographic characteristics, vital signs, laboratory parameters, and imaging findings of 150 patients who presented to the emergency department with spontaneous ICH and had accessible 30-day mortality data were retrospectively analyzed. Inflammatory indices including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), HALP score, systemic inflammation response index (SIRI), and glucose-to-lymphocyte ratio were calculated. Patients were stratified according to 30-day survival status, and intergroup comparisons were performed. The predictive performance of these indices was assessed ROC curve analysis. Results: A total of 47.3% of the patients died within 30 days. Low Glasgow Coma Scale(GCS) , large hematoma volume, presence of intraventricular hemorrhage(IVH), midline shift, need for intubation, and elevated blood pressure were all significantly associated with mortality (all p < 0.001). Hematoma volume had the highest area under the ROC curve (AUROC = 0.897; 95% CI: 0.847–0.947). The HALP score was significantly lower in non-survivors, while NLR, PLR, SIRI, and the glucose-to-lymphocyte ratio were significantly higher in this group (all p < 0.001). NLR demonstrated particularly high specificity (88.6%) for predicting mortality. Conclusion: Hematoma volume is the best way to predict mortality in spontaneous ICH. Simple inflammatory indices such as NLR, HALP and SIRI can also help with early risk stratification.

Aims: This study aims to categorize adolescent patients presenting to the hospital due to falls from heights into two groups: suicidal and non-suicidal. It seeks to compare the clinical characteristics, trauma patterns, and outcomes between these groups. Methods: A total of 69 patients were included in the study. The demographic features, trauma patterns, imaging methods, medical interventions, and clinical outcomes of the patients were retrospectively assessed. Results: 63.8% (n=44) of the patients were categorized in the suicidal group, while 36.2% (n=25) were in the non-suicidal group. There was no statistically significant difference observed between the mean age of the suicidal group (16.27±2.52) and the non-suicidal group (15.96±2.85) (p=0.638). In the suicidal group, the incidence rates of maxillofacial trauma, pelvic trauma, and thoracic trauma were statistically significantly higher compared to the non-suicidal group (respectively; p=0.041, p=0.014, p<0.001). The in-hospital mortality rate in the suicidal group (22.7%, n=10) was statistically significantly higher than in the non-suicidal group (0%, n=0) (p=0.007). Conclusion: Cases of falls from heights due to suicide attempts result in more severe outcomes compared to accidental falls. These patients require a more comprehensive medical assessment and intervention.

Background: Acute upper gastrointestinal (GI) bleeding is a common and potentially life-threatening emergency frequently seen in emergency departments. Early and accurate risk stratification is essential for guiding clinical management. This study aimed to assess the effectiveness of various clinical scoring systems and laboratory parameters in predicting in-hospital mortality in patients with upper GI bleeding. Methods: This retrospective study included patients aged 18 and older diagnosed with upper GI bleeding between January 1, 2016, and January 1, 2019. The Glasgow Blatchford Score (GBS), Pre-endoscopic Rockall Score (PRS), total Rockall Score, AIMS65, and NEWS+L scores were calculated. Laboratory parameters were also analyzed for their association with mortality. Results: A total of 316 patients were included, with an in-hospital mortality rate of 13.3%. Among the scoring systems, AIMS65 and NEWS+L demonstrated higher predictive accuracy (AUC) for in-hospital mortality compared to PRS. GBS and total Rockall scores also performed better than PRS. Conclusion: AIMS65 and NEWS+L scores were superior to PRS in predicting mortality. Additionally, low hemoglobin, elevated lactate, high neutrophil-to-lymphocyte (NLR) and platelet-to-lymphocyte (PLR) ratios, and increased urea-to-creatinine levels were associated with higher mortality risk.