Prognostic Utility of dNLR, ALRI, APRI, and SII in COVID-19 Patients with Diabetes: A Cross-Sectional Study.

The coronavirus disease 2019 (COVID-19) pandemic has necessitated the identification of biomarkers that can predict disease severity, particularly in vulnerable populations such as individuals with diabetes. This study aims to evaluate the predictive value of inflammatory and liver function markers, specifically derived Neutrophil to Lymphocyte Ratio (dNLR), aspartate aminotransferase (AST)-to-lymphocyte ratio (ALRI), AST to Platelet Ratio Index (APRI), and Systemic Inflammation Index (SII), in COVID-19 patients with and without diabetes. This cross-sectional study included 336 participants, comprising 168 patients with diabetes matched with 168 without, based on gender, body mass index (BMI), and COVID-19 severity at hospitalization. The study was conducted at Victor Babes Hospital for Infectious Diseases and Pulmonology from January 2021 to December 2023. All participants had a confirmed SARS-CoV-2 infection and met the inclusion criteria of being 18 years or older with type 1 or type 2 diabetes as per American Diabetes Association guidelines. At 3 days post symptom onset, significant differences in inflammatory and liver function markers were observed between the two groups. The dNLR, ALRI, APRI, and SII were notably higher in diabetic patients. At a dNLR cutoff of 2.685, the sensitivity and specificity were 70.312% and 65.978%, respectively, with an AUC of 0.624 (p < 0.001). The ALRI showed a cutoff of 0.812, with a sensitivity of 76.429% and specificity of 69.541% (AUC 0.752, p < 0.001). These markers demonstrated statistically significant hazard ratios at both 3 and 7 days, indicating their predictive relevance for severe COVID-19 outcomes. For instance, at 7 days, SII demonstrated a hazard ratio of 2.62 (CI: 1.29-5.04, p < 0.001), highlighting its strong prognostic capability. The study successfully identified significant differences in inflammatory and liver function markers between COVID-19 patients with and without diabetes, with these markers showing good predictive value for disease severity. The results underscore the potential of these biomarkers, particularly ALRI and SII, as valuable tools in managing COVID-19, aiding in the timely identification of patients at increased risk of severe outcomes.

Comparative Analysis of COVID-19 Outcomes in Type 1 and Type 2 Diabetes: A Three-Year Retrospective Study.

Background and Objectives: This comprehensive retrospective study assesses COVID-19 outcomes in type 1 (T1D) and type 2 diabetes (T2D) patients across three years, focusing on how these outcomes varied with the evolving pandemic and changes in diabetes management. The study aims to determine if COVID-19 outcomes, including severity, intensive care unit (ICU) admission rates, duration of hospitalization, and mortality, are significantly different between these diabetes subtypes. Materials and Methods: The study analyzed data from patients admitted to the Victor Babes Hospital for Infectious Diseases and Pulmonology with confirmed COVID-19 and pre-existing diabetes, from the years 2020, 2021, and 2022. Results: Among 486 patients (200 without diabetes, 62 with T1D, 224 with T2D), T2D patients showed notably higher severity, with 33.5% experiencing severe cases, compared to 25.8% in T1D. Mortality rates were 11.6% in T2D and 8.1% in T1D. T2D patients had longer hospital stays (11.6 ± 7.0 days) compared to T1D (9.1 ± 5.8 days) and were more likely to require ICU admission (OR: 2.24) and mechanical ventilation (OR: 2.46). Hyperglycemia at admission was significantly higher in the diabetes groups, particularly in T2D (178.3 ± 34.7 mg/dL) compared to T1D (164.8 ± 39.6 mg/dL). Conclusions: The study reveals a discernible difference in COVID-19 outcomes between T1D and T2D, with T2D patients having longer hospital admissions, mechanical ventilation necessities, and mortality risks.

Healthcare Workers' Vulnerability to SARS-CoV-2 in Western Romania: A Study on Incidence and Risk Factors for Non-Vaccination and Reinfection.

Purpose: The COVID-19 pandemic has severely impacted healthcare workers, a professional category at risk of infection in both hospital and community settings. The aim of the study was to compare morbidity among hospital staff and that in general population, as well as the factors predicting non-vaccination and reinfection. Patients and Methods: The present study is a retrospective, cross-sectional study. It was conducted by including all the confirmed COVID-19 infection cases in medical staff members during the period 01.01.2021-31.03.2022 that were reported to the Public Health Authority of Timis County, Timisoara, Western Romania. Results: Direct, strong, statistically significant correlations were found between the incidence of COVID-19 recorded in all categories of medical personnel and the community pandemic trend, with maximum values for auxiliary and medium medical staff (rho = 0.852/0.821, p < 0.001). The high socio-economic level, as well as the advanced medical education level, were predictor factors for anti-SARS-COV-2 vaccination among the personnel. The non-vaccinated status as well as incomplete vaccination or even the 2-dose vaccination represented independent risk factors for reinfection in 2022. Conversely, receiving a higher number of vaccine doses emerged as the primary protective factor. Notably, reduced adherence to the administration of the following doses was observed particularly among medium and auxiliary staff, leading to additional risks of infection with the Omicron variant. Conclusion: Despite over 70% vaccination coverage among all studied medical personnel categories, there was low adherence to repeat doses of vaccination, particularly among medium and auxiliary staff. The study highlighted a distinct necessity for enhanced training on preventive behaviours and targeted prevention/control strategies for all professional groups interacting with patients, including caretakers, ambulance workers, receptionists, physiotherapists, and psychologists.

Monoclonal antibodies targeted against melanoma and ovarian tumors enhance dendritic cell-mediated cross-presentation of tumor-associated antigens and efficiently cross-prime CD8+ T cells.

Dendritic cells (DCs) constitute very attractive vectors for cancer immunotherapy due to their ability to efficiently capture and present tumor antigens, which initiates tumor-directed T-cell responses. Because the initiation of cytotoxic anti-tumor immune responses requires the cross-presentation mechanism, antigen targeting to DCs represents a very important step in the chain of events that constitutes the cross-priming immune process. In the current study, we explored the ability of DCs loaded with antibody-coated melanoma and ovarian carcinoma tumor cells to cross-present tumor antigens to CD8+ T cells and elicit in vitro anti-tumor immune responses. Coating melanoma and ovarian cancer cells with monoclonal antibodies against different surface antigens (CD44, ME491, LFA-3, and CD24) expressed by the tumor cells promoted the cross-presentation of the tumor-associated antigens as MART-1, gp100, tyrosinase, and NY-ESO-1 by DCs to CD8+ T. These tumor antigen-specific CD8+ T-cell populations resulting from the DC-mediated cross-priming process were identified using specific immune tetramers and were a few fold larger than the ones generated using peptide-pulsed or apoptotic tumor cell-loaded DCs. The CD8+ T cells generated by DCs loaded with monoclonal antibody-coated tumor cells were cytotoxic against the primary melanoma and ovarian carcinoma cells. Thus, targeting monoclonal antibody-coated tumor cells to DCs is a novel method that opens new perspectives for immunotherapy strategies.