Browsing by Author "Radisavljevic, Nina (57201418152)"

Background: Previous studies suggested an important role of impairments in T cell subsets in different stages during type 1 diabetes (T1D) development, while data regarding CD25high T cells and transforming growth factor β1 (TGFβ1), both T regulatory associated, remains controversial. We analyzed the level of (a) CD25high T cells (b) TGFβ1 in 17 first-degree relatives of patients with T1D in stage 1 (FDRs1) (GADA+, IA-2+); 34 FDRs in stage 0 (FDRs0) (GADA-, IA-2-); 24 recent-onset T1D in insulin-requiring state (IRS); 10 patients in clinical remission (CR); 18 healthy, unrelated controls (CTR). Methods: T cell subsets were characterized by two-color immunofluorescence staining and flow cytometry; TGFβ1 was determined by ELISA, GADA, and IA-2 by RIA. Results: The percentage of CD25high T cells in FDRs1 was lower than controls, FDRs0, IRS, and CR (p<0.001). Additionally, the cut-off value for CD25high = 1.19%, with a probability of 0.667, for having a higher risk for T1D. TGFβ1 concentration in FDRs1, FDRs0, IRS, and CR, was lower than controls (p<0.001). IRS has a higher TGFβ1 concentration than CR (p<0.001). Conclusions: Stage 1, a higher risk for T1D, is characterized by decreases in CD25high T cells and TGFβ1, partially reflecting impaired T regulatory response, implying that changes of this T cells subset might be a risk marker for T1D. FDRs, irrespective of risk for T1D and T1D patients irrespective of state, had depletion of TGFβ1, suggesting the association of TGFβ1 could have potential with familiar risk and manifestation of T1D. Furthermore, the result suggested that the clinical course of overt T1D might be modulated on the TGFβ1 level. © 2024 Society of Medical Biochemists of Serbia. All rights reserved.

Background: Previous studies suggested an important role of impairments in T cell subsets in different stages during type 1 diabetes (T1D) development, while data regarding CD25high T cells and transforming growth factor β1 (TGFβ1), both T regulatory associated, remains controversial. We analyzed the level of (a) CD25high T cells (b) TGFβ1 in 17 first-degree relatives of patients with T1D in stage 1 (FDRs1) (GADA+, IA-2+); 34 FDRs in stage 0 (FDRs0) (GADA-, IA-2-); 24 recent-onset T1D in insulin-requiring state (IRS); 10 patients in clinical remission (CR); 18 healthy, unrelated controls (CTR). Methods: T cell subsets were characterized by two-color immunofluorescence staining and flow cytometry; TGFβ1 was determined by ELISA, GADA, and IA-2 by RIA. Results: The percentage of CD25high T cells in FDRs1 was lower than controls, FDRs0, IRS, and CR (p<0.001). Additionally, the cut-off value for CD25high = 1.19%, with a probability of 0.667, for having a higher risk for T1D. TGFβ1 concentration in FDRs1, FDRs0, IRS, and CR, was lower than controls (p<0.001). IRS has a higher TGFβ1 concentration than CR (p<0.001). Conclusions: Stage 1, a higher risk for T1D, is characterized by decreases in CD25high T cells and TGFβ1, partially reflecting impaired T regulatory response, implying that changes of this T cells subset might be a risk marker for T1D. FDRs, irrespective of risk for T1D and T1D patients irrespective of state, had depletion of TGFβ1, suggesting the association of TGFβ1 could have potential with familiar risk and manifestation of T1D. Furthermore, the result suggested that the clinical course of overt T1D might be modulated on the TGFβ1 level. © 2024 Society of Medical Biochemists of Serbia. All rights reserved.

Background: The COVID-19 pandemic revealed an unexpected pattern known as the “smoker’s paradox”, with lower rates of severe disease among smokers compared to non-smokers, highlighting the need for the specific investigation of disease progression in non-smoking populations. Objective: To identify early mortality predictors in non-smoking patients with severe COVID-19 through the evaluation of clinical, laboratory, and oxygenation parameters. Methods: This retrospective observational cohort study included 59 non-smokers hospitalized with COVID-19 between November and December 2020. Clinical parameters, laboratory findings, and respiratory support requirements were analyzed on Days 1 and 7 of hospitalization. ROC curves were constructed to assess the predictive value of the parameters. Results: The overall mortality rate was 54.2%. The seventh-day SOFA score showed the strongest predictive value (AUC = 0.902, p = 0.004), followed by pCO2 (AUC = 0.853, p = 0.012). Significant differences between survivors and non-survivors were observed in acid–base parameters, oxygenation indices, and hematological markers. Mortality rates varied significantly with ventilation type: 84.6% for IMV and 50% for NIMV, with no deaths in HFNC patients. Conclusions: Multiple parameters measured on Day 7 of hospitalization demonstrate significant predictive value for mortality in non-smoking COVID-19 patients, with the SOFA score being the strongest predictor. The type of respiratory support significantly influences outcomes, suggesting the importance of careful ventilation strategy selection. © 2025 by the authors.

Background: The COVID-19 pandemic revealed an unexpected pattern known as the “smoker’s paradox”, with lower rates of severe disease among smokers compared to non-smokers, highlighting the need for the specific investigation of disease progression in non-smoking populations. Objective: To identify early mortality predictors in non-smoking patients with severe COVID-19 through the evaluation of clinical, laboratory, and oxygenation parameters. Methods: This retrospective observational cohort study included 59 non-smokers hospitalized with COVID-19 between November and December 2020. Clinical parameters, laboratory findings, and respiratory support requirements were analyzed on Days 1 and 7 of hospitalization. ROC curves were constructed to assess the predictive value of the parameters. Results: The overall mortality rate was 54.2%. The seventh-day SOFA score showed the strongest predictive value (AUC = 0.902, p = 0.004), followed by pCO2 (AUC = 0.853, p = 0.012). Significant differences between survivors and non-survivors were observed in acid–base parameters, oxygenation indices, and hematological markers. Mortality rates varied significantly with ventilation type: 84.6% for IMV and 50% for NIMV, with no deaths in HFNC patients. Conclusions: Multiple parameters measured on Day 7 of hospitalization demonstrate significant predictive value for mortality in non-smoking COVID-19 patients, with the SOFA score being the strongest predictor. The type of respiratory support significantly influences outcomes, suggesting the importance of careful ventilation strategy selection. © 2025 by the authors.