Aim: The Delta Neutrophil Index (DNI) shows the ratio of immature granulocytes in the circulation and increases in conditions of infection and inflammation. The aim of this study was to investigate the suitability of using DNI as a prognostic marker of mortality in COVID-19 patients in the Intensive Care Unit (ICU). Material and Method: This retrospective study included 316 patients followed up in the ICU with a diagnosis of COVID-19. A record was made for each patient of demographic data, laboratory values, clinical results and mortality status. All the data of the patients were evaluated and compared between the two groups of surviving and non-surviving patients. Results: Mortality developed in 181 (57.27%) patients. The Glasgow Coma Scale score was lower and the APACHE II and SOFA scores were higher in the mortality group than in the surviving group (p<0.001 for all). The creatinine, procalcitonin, white blood cell, neutrophil count, neutrophil-lymphocyte ratio, lactate, interleukin -6 and C-reactive protein values were statistically significantly higher in the mortality group. In the comparison of DNI between the groups, a statistically significant difference was only determined on day 3 (p=0.026). For the DNI examined on day 3, the AUC value was 0.574 and the cutoff value was 1.35% for the prediction of mortality. Conclusion: DNI, which is low cost and simple to use, can be considered safe for use in the prediction of mortality of ICU patients diagnosed with COVID-19. The monitoring of increasing or decreasing trends by keeping regular records can be considered important for the clinical course.

Background and Objectives: Previous findings have suggested that inflammatory and nutritional biomarkers may help predict the prognosis in colorectal cancer patients; however, their predictive value and optimal use remain uncertain. Therefore, this study aimed to investigate the effects of several preoperatively measured inflammatory and nutritional biomarkers on the overall survival in patients undergoing surgery for colon cancer and to compare their predictive ability between themselves and with other clinical parameters. Materials and Methods: This retrospective cohort study included 411 patients who underwent surgery for colon cancer between May 2014 and May 2024. Demographic, clinical, pathological, and laboratory data were analyzed. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), De Ritis ratio, Gustave Roussy Immune (GRIM) score, and hemoglobin, albumin, lymphocyte, and platelet (HALP) score were calculated from preoperative laboratory values. Cox regression, receiver operating characteristic (ROC), and Kaplan–Meier survival analyses were performed. Results: During follow-up, 270 patients (65.7%) survived, and 141 (34.3%) died. The survival group was significantly younger than the mortality group (p < 0.001). The hemoglobin level and HALP score were significantly higher in the survival group, whereas the PLR was significantly higher in the mortality group. In the multivariate analysis, adjusted for baseline clinical and pathological factors, the age (HR: 1.046, 95% CI: 1.030–1.062, p < 0.001) and the HALP score (HR: 0.984, 95% CI: 0.971–0.998, p = 0.025) were identified as independent predictors of mortality. A HALP score cut-off value of 38.8 predicted mortality with 85.1% sensitivity and 31.9% specificity (AUC: 0.597, p = 0.001). Patients with HALP scores > 38.8 had significantly longer overall survival (p < 0.001). Conclusions: The preoperative HALP score is an independent predictor of overall survival in patients with colon cancer. As a simple and readily available immune–nutritional biomarker, the HALP score may contribute to preoperative risk stratification and prognostic assessment in routine clinical practice, serving as a supplementary tool alongside traditional staging.

Background: This study aims to evaluate the predictive value of metabolic parameters in detecting invasive breast cancer molecular subtypes. Methods: We enrolled 112 patients who had a preoperative ¹⁸F-fluorodeoxyglucose positron emission tomography computed tomography (¹⁸F-FDG PET-CT) scan and were operated on with a diagnosis of invasive breast cancer between January 2017 and August 2020. We evaluated associations among maximum standardized uptake value (SUV_max), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and clinicopathological findings by dividing the specimen into three tumor subtypes according to estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER-2) expressions. Results: There was a significant difference between the three groups in the SUV_max value of axillary lymph node metastasis (P = 0.014), but no significant difference was revealed for TLG and MTV (P = 0.858 and P = 0.083, respectively). There was a significant difference between groups in SUV_max and TLG (P < 0.001 and P = 0.001, respectively) for the primary tumor, but no significant difference was observed in MTV (P = 0.051). Conclusion: We suggest that primary tumor SUV_max can be used to differentiate triple-negative patients from other subgroups, and primary tumor TLG can be used to distinguish hormone receptor positive (HR+) patients from other subgroups.