Background: The systemic inflammatory response index (SIRI), which depends on peripheral neutrophil, monocyte, and lymphocyte count, was found as an effective prognostic indicator for various malignancies. This study aims to investigate the predictive value of preoperative SIRI in the prognosis of gastric cancer patients without neoadjuvant therapy. Methods: The patients who underwent gastric cancer surgery in Marmara University Hospital's General Surgery Department between 2019 and 2021 were analyzed retrospectively. SIRI was calculated from preoperative peripheral blood samples’ neutrophil, lymphocyte, and monocyte count. The optimal cut-off value for SIRI was calculated by the receiver operating characteristics (ROC) curve and was found to be 1.35. The clinicopathological outcomes and overall survival (OS) were analyzed under two groups according to the SIRI values lower or higher than 1.35. Results: The number of eligible patients was 199. The median follow-up time was 25 (1-56) months. The higher SIRI was associated with male gender (p = 0.044), lower serum albumin (0.002) level, and Clavien-Dindo (CD) Grade III and higher complications (p = 0.018). However, there was no significant difference between the groups regarded pathological tumor, nodes, and metastases (TNM) stages, histological grade, and Lauren Type. In addition, OS and stage-specific OS were similar between the groups. Conclusions: SIRI may be a valuable and effective predictive indicator for postoperative morbidity. The prognostic performance of SIRI on long-term OS is still controversial. Further investigations are needed into this topic.

For prediction of mortality and clinical course, various scoring systems had been developed. We choose four well known burn specific scoring systems and a general scoring system that using in Intensive Care Units. The primary outcome of this study was evaluate the predictive performances of this models and define the optimal one for our patient population. Variables analyzed were age, gender, burn type, total burned surface area (TBSA), total partial thickness burn area, total full thickness burn area, inhalation injuries, mechanical ventilation supports, blood products usage, total scores of Abbreviated Burn Severity Index (ABSI), revised Baux, Belgian Outcome in Burn Injury, Fatality by Longevity, Acute Physiology and Chronic Health Eval-uation II (APACHE II) score, Measured Extent of burn and Sex (FLAMES) and APACHE II, and their relations with mortality. In our study, a statistically significant relationship was found with mortality between age, TBSA, full thickness burn percent-age, inhalation injury, burn type, and it was similar to literature. Female gender was found to be a significant risk factor for mortality. We compared several burn mortality scoring systems and their predictional mortality rates. ABSI scores of patients for estimated mortality rates were similar to our mortality rate. Consequently, it was thought that ABSI was included all mortality-re-lated parameters.

Backgrounds: Extended resection for gastric cancer in elderly patients is still challenging for surgeons. This study aimed to evaluate the prognosis and the postoperative outcomes of elderly patients underwent gastric cancer surgery in a high-volume center. Methods: The medical records of patients with gastric cancer surgery at Marmara University Hospital’s General Surgery Department were examined retrospectively. Patients were divided into two groups: Age ≤ 70 and Age > 70. The clinicopathological data of the patients were compared. The prognostic factors regarding gastric cancer surgery were analyzed with Cox proportional regression models. Kaplan Meier analysis and log-rank test were used to compare Overall Survival (OS) and Cancer-Specific Survival (CSS) among the groups. Competing risk regression analysis was used to examine cause-specific hazards among elderly patients. Results: The number of eligible patients was 250. Age > 70 group was 68 patients, and Age ≤ 70 group was 182 patients. There is no significant difference between the patient’s demographics or pathological outcomes. Neoadjuvant therapies performed less in elderly patients [40 (22%) vs. 7 (10%), p: 0.03, respectively]. There was no significant difference in severe complication (≥ Grade III) rates in both groups. Multivariate analysis showed that advanced T stage and adjacent organ invasion were the independent risk factors for OS. No significant difference was observed between the groups regarding OS (Log Rank (Mantel-Cox): 0.102). Younger patients have worse CSS than those who are older. Cause-specific hazard model demonstrated a not increased hazard ratio [HR: 1.04(0.78–1.38)] for elderly patients for OS and CSS. Conclusion: Gastric resections can be safely performed for elderly patients diagnosed with gastric cancer. This study showed that growing age is no longer a factor that will affect the clinician’s decision in performing surgery in gastric cancer patients.

Backgrounds: Acute Appendicitis (AA) is one of the most common surgical emergencies worldwide. This study aims to investigate the predictive performances of 6 different Machine Learning (ML) algorithms for simple and complicated AA. Methods: Data regarding operated AA patients between 2012 and 2022 were analyzed retrospectively. Based on operative findings, patients were evaluated under two groups: perforated AA and none-perforated AA. The features that showed statistical significance (p < 0.05) in both univariate and multivariate analysis were included in the prediction models as input features. Five different error metrics and the area under the receiver operating characteristic curve (AUC) were used for model comparison. Results: A total number of 1132 patients were included in the study. Patients were divided into training (932 samples), testing (100 samples), and validation (100 samples) sets. Age, gender, neutrophil count, lymphocyte count, Neutrophil to Lymphocyte ratio, total bilirubin, C-Reactive Protein (CRP), Appendix Diameter, and PeriAppendicular Liquid Collection (PALC) were significantly different between the two groups. In the multivariate analysis, age, CRP, and PALC continued to show a significant difference in the perforated AA group. According to univariate and multivariate analysis, two data sets were used in the prediction model. K-Nearest Neighbors and Logistic Regression algorithms achieved the best prediction performance in the validation group with an accuracy of 96%. Conclusion: The results showed that using only three input features (age, CRP, and PALC), the severity of AA can be predicted with high accuracy. The developed prediction model can be useful in clinical practice.

BACKGROUND: Burns is one of the most common traumas worldwide. Severely injured burn patients have an increased risk for mortality and morbidity. This study aimed to evaluate well-known risk factors for burn mortality and comparison of six machine learning (ML) Algorithms' predictive performances. METHODS: The medical records of patients who had burn injuries treated at Izmir Bozyaka Training and Research Hospital's Burn Treatment Center were examined retrospectively. Patients' demographics such as age and gender, total burned surface area (TBSA), Inhalation injury (II), full-thickness burns (FTBSA), and burn types (BT) were recorded and used as input features in ML models. Patients were analyzed under two groups: Survivors and Non-Survivors. Six ML algorithms, including k-Nearest Neighbor, Decision Tree, Random Forest, Support Vector Machine, Multi-Layer Perceptron, and AdaBoost (AB), were used for predicting mortality. Several different input feature combinations were evaluated for each algorithm. RESULTS: The number of eligible patients was 363. All six parameters (TBSA, Gender, FTBSA, II, Age, BT) that were included in ML algorithms showed a significant difference (p<0.001). The results show that AB algorithm using all input features had the best prediction performance with an accuracy of 90% and an area under the curve of 92%. CONCLUSION: ML algorithms showed strong predictive performance in burn mortality. The development of an ML algorithm with the right input features could be useful in the clinical practice. Further investigations are needed on this topic.

Purpose: The Systemic Inflammatory Response Index (SIRI), which depends on peripheral neutrophil, monocyte, and lymphocyte count, was found to be an effective prognostic indicator for various malignancies. In this study, we aimed to investigate the diagnostic value and the prognostic impact of SIRI on rectal cancer patients. Method: The medical records of patients underwent sphincter-sparing rectal cancer surgery at general surgery between 2017 and 2022 were examined retrospectively. Patient demographics, operation types, neoadjuvant chemo/radiotherapies, pathological results, and complications were recorded. A total number of 99 patients who operated with diagnoses other than cancer were conducted as a control group. SIRI was calculated from preoperative peripheral blood samples’ neutrophil, lymphocyte, and monocyte count. The optimal cut-off value for SIRI was found to be 1.38. The clinicopathological outcomes and Overall Survival (OS) were analyzed under two groups according to the SIRI values lower or higher than 1.38. Results: The number of eligible patients was 104. The median age of the entire cohort was 62 (31–89). The median follow-up time was 33 (1–62) months. The median SIRI value in the study group was significantly higher compared with the control group. The study group was examined under two groups: SIRI 1.38 and SIRI > 1.38. The male gender was significantly more frequent in the high SIRI group. The remaining patient demographics and operation types were similar between the groups. The pathological outcomes were similar between the two groups. Overall Survival rate was better in the low SIRI group than those higher. The higher group had significantly higher complication rates than the lower SIRI group (p: 0.004). Conclusion: SIRI may be a valuable diagnostic marker in rectal cancer patients. Higher SIRI levels were also associated with poorer prognosis and increased complication rates. Still, further prospective studies with a larger number of patients are needed.