The purpose of this study is to evaluate serum Pentraxin-3 (PTX-3) levels in Sars-CoV-2 virus infection (COVID-19) patients and to investigate whether PTX-3 predicts the disease prognosis. This study was conducted on 88 confirmed COVID-19 patients who were hospitalized due to symptomatic pneumonia between April 15 2020 and August 15 2020. The patients were divided into two groups as survived patients and non-survived patients. Both groups were compared according to demographic features, comorbid conditions and measurement of the PTX-3 and other laboratory parameters of the patients. Of 88 patients with COVID-19, 59 (67%) were discharged with complete cure and 29 (33%) resulted in death. 46 (52.3%) of the patients were men. PTX-3 median value [IQR] was 3.66 ng/mL (0.9-27.9) in all patients, 3.3 ng/mL (0.9-27.9) in survivors and 3.91 ng/mL (1.9-23.2) in non-survivors which was significantly higher (p= 0.045). As a receiver operating characteristic curve analysis the cut-off value of PTX-3 for predicting mortality in patients was 3.73 with 65% sensitivity and 65% specificity (AUC: 0.646, 95% CI: 0.525-0.767, P= 0.045). Also, we found significant cut-off values with respect to D-Dimer, D-Dimer/ PTX-3, high-sensitivity troponin, high-sensitivity troponin/ PTX-3, lymphocyte, PTX-3/ lymphocyte, procalcitonin, procalcitonin/ PTX-3, CRP, and CRP/ PTX-3 (P<0.05). In this study, as far as we know, for the first time, we have shown PTX-3 as the new mortality biomarker for COVID-19 disease.

Objectives: Fournier’s gangrene is an aggressive, rapidly progressing, and life-threatening necrotizing fasciitis of the perineal and genital regions. Various scoring systems have been developed for predicting survival and prognosis in Fournier’s gangrene. This retrospective study aimed to evaluate the effectiveness of the newly developed Fournier’s gangrene mortality index (FGMI) in predicting mortality associated with Fournier’s gangrene. Methods: The study included patients over the age of 18 years who were followed-up with a diagnosis of Fournier’s gangrene in the general surgery clinics of three different hospitals in Şanlıurfa province between 2014 and 2024. The patients included in this study were divided into two groups: deceased (n = 20) and surviving (n = 149). In FGMI, the parameters used were age, creatinine level, albumin level, lymphocyte percentage, and neutrophil-to-lymphocyte ratio. Based on the total score and risk assessment, <5 points were categorized as low-to-moderate mortality risk and ≥5 points as high mortality risk. Results: A total of 169 patients with a diagnosis of Fournier’s gangrene were included in the study; 87 were men (51.48%). The median age of all patients was 53 (40–63) years; 20 patients (11.8%) died. The Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score did not show a statistically significant difference between the deceased and surviving groups (p = 0.5). Compared to the survivors, the deceased had higher neutrophil counts, neutrophil percentages, neutrophil-to-lymphocyte ratios, platelet-to-lymphocyte ratios, and C-reactive protein-to-albumin ratios, whereas lymphocyte counts, lymphocyte percentages, eosinophil counts, eosinophil percentages, monocyte counts, and monocyte percentages were lower, and these differences were statistically significant. According to receiver operating characteristic (ROC) analysis, the ROC-area under the curve for predicting mortality based on an FGMI score of ≥5 was 0.88 (95% CI: 0.80–0.95) with a sensitivity of 90% and a specificity of 70% (p < 0.001). Univariate risk analysis was performed, and the odds ratio revealed that mortality risk in patients followed-up for Fournier’s gangrene with a FGMI score of ≥5 was 20 times higher (4.48–90.91) (p < 0.001). Conclusions: The results reveal that the FGMI score is a scoring system that can predict mortality at the initial clinical presentation of patients with Fournier’s gangrene. Another important finding of the present study is that the LRINEC score was not sufficiently effective in predicting mortality.

Background/aim: The COVID-19 infection, which started in Wuhan City, China, in December 2019, turned into a pandemic in a very short time, affecting mainly the elderly and those with serious chronic illnesses. COVID-19 infections have been observed to have a high mortality rate, especially in patients undergoing maintenance hemodialysis. Materials and methods: Forty-two patients over 18 years of age who underwent a maintenance hemodialysis program at our unit, who tested positive for COVID-19 by PCR from nasopharyngeal swabs, and/or who were observed to have disease-related signs in their CTs were included in the study. Results: In this study, 23 of 42 patients receiving hemodialysis support in our clinic were included. The median age was 67 years old (min: 35; max: 91 years), and all of our patients had primary hypertension and other comorbidities. Their clinical evaluation showed that dry cough (47.8%) and shortness of breath (47.8%) were the most common symptoms. Fever was less pronounced (30.4%). The median time from the onset of symptoms to hospitalization was 1 day (min: 0; max:), and the time from hospitalization to death was 18 days (min: 1; max: 22). Transfer from the inpatient ward to the ICU took a median of 7 days (min: 1; max: 13). Among the 23 patients, 3 died during follow-up, and 20 were discharged with full recovery. Baseline ferritin, procalcitonin levels, and CRP/albumin rates were higher, and neutrophil/lymphocyte levels were lower in patients who eventually died. In these patients, despite being nonsignificant, there were more diabetic patients, and the D-dimer levels were higher than 1000 ugFEU/L. Conclusion: The COVID-19 infection is associated with increased mortality in chronic kidney diseases patients. Despite being nonsignificant, there was a trend towards increased mortality in patient with diabetes, D-dimer levels >1000 ugFEU/L, higher ferritin and prokalsitonin levels, an increased CRP/albumin ratio, and a lower neutrophil/lymphocyte ratio.

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity classification.

The primary objective of this study was to explore the impact of metformin and metformin/gliptin combination therapy on the serum concentrations of vitamin B12, ferritin, and folic acid in individuals diagnosed with type 2 diabetes.