Background: Published data regarding the impact of obesity on COVID-19 outcomes are inconsistent. However, in most studies, body composition was assessed using body mass index (BMI) alone, thus neglecting the presence and distribution of adipose tissue. Therefore, we aimed to investigate the impact of body and visceral fat on COVID-19 outcomes.Methods: Observational, prospective cohort study included 216 consecutive COVID-19 patients hospitalized at University Clinical Center Kragujevac (Serbia) from October to December 2021. Body composition was assessed using the BMI, body fat percentage (%BF), and visceral fat (VF) via bioelectrical impedance analysis (BIA). In addition to anthropometric measurements, variables in the research were socio-demographic and medical history data, as well as admission inflammatory biomarkers. Primary end-points were fatal outcomes and intensive care unit (ICU) admission.Results: The overall prevalence of obesity was 39.3% according to BMI and 50.9% according to % BF, while 38.4% of patients had very high VF levels. After adjusting odds ratio values for cofounding variables and obesity-related conditions, all three anthropometric parameters were significant predictors of primary end-points. However, we note that % BF and VF, compared to BMI, were stronger predictors of both mortality (aOR 3.353, aOR 3.05, and aOR 2.387, respectively) and ICU admission [adjusted odds ratio (aOR) 7.141, aOR 3.424, and aOR 3.133, respectively].Conclusion: Obesity is linked with COVID-19 mortality and ICU admission, with BIA measurements being stronger predictors of outcome compared to BMI use alone.

Background: Early prediction of COVID-19 patients’ mortality risk may be beneficial in adequate triage and risk assessment. Therefore, we aimed to single out the independent morality predictors of hospitalized COVID-19 patients among parameters available on hospital admission. Methods: An observational, retrospective–prospective cohort study was conducted on 703 consecutive COVID-19 patients hospitalized in the University Clinical Center Kragujevac between September and December 2021. Patients were followed during the hospitalization, and in-hospital mortality was observed as a primary end-point. Within 24 h of admission, patients were sampled for blood gas and laboratory analysis, including complete blood cell count, inflammation biomarkers and other biochemistry, coagulation parameters, and cardiac biomarkers. Socio-demographic and medical history data were obtained using patients’ medical records. Results: The overall prevalence of mortality was 28.4% (n = 199). After performing multiple regression analysis on 20 parameters, according to the initial univariate analysis, only four independent variables gave statistically significant contributions to the model: SaO2 < 88.5 % (aOR 3.075), IL-6 > 74.6 pg/mL (aOR 2.389), LDH > 804.5 U/L (aOR 2.069) and age > 69.5 years (aOR 1.786). The C-index of the predicted probability calculated using this multivariate logistic model was 0.740 (p < 0.001). Conclusions: Parameters available on hospital admission can be beneficial in predicting COVID-19 mortality.

Aim: We aimed to single out admission predictors of acute respiratory distress syndrome (ARDS) in hospitalized COVID-19 patients and investigate the role of bioelectrical impedance (BIA) measurements in ARDS development. Method: An observational, prospective cohort study was conducted on 407 consecutive COVID-19 patients hospitalized at the University Clinical Center Kragujevac between September 2021 and March 2022. Patients were followed during the hospitalization, and ARDS was observed as a primary endpoint. Body composition was assessed using the BMI, body fat percentage (BF%), and visceral fat (VF) via BIA. Within 24 h of admission, patients were sampled for blood gas and laboratory analysis. Results: Patients with BMI above 30 kg/m², very high BF%, and/or very high VF levels were at a significantly higher risk of developing ARDS compared to nonobese patients (OR: 4.568, 8.892, and 2.448, respectively). In addition, after performing multiple regression analysis, six admission predictors of ARDS were singled out: (1) very high BF (aOR 8.059), (2) SaO₂ < 87.5 (aOR 5.120), (3) IL-6 > 59.75 (aOR 4.089), (4) low lymphocyte count (aOR 2.880), (5) female sex (aOR 2.290), and (6) age < 68.5 (aOR 1.976). Conclusion: Obesity is an important risk factor for the clinical deterioration of hospitalized COVID-19 patients. BF%, assessed through BIA measuring, was the strongest independent predictor of ARDS in hospitalized COVID-19 patients.

Background/Objectives: Impaired quality of life (QoL) represents one of the most important clinical determinants in heart failure with preserved ejection fraction (HFpEF). This study aimed to evaluate the incremental explanatory value of functional performance and inflammatory biomarkers for QoL in a clinically stable HFpEF cohort. Methods: A single-center observational study enrolled 110 consecutive patients with stable HFpEF. Functional capacity was assessed using the six-minute walk test (6MWT), expressed mainly as percentage of predicted distance. Health-related QoL was measured using the EQ-5D-5L utility index (primary outcome). Circulating IL-6, CRP, and NT-proBNP were obtained from peripheral blood. Hierarchical multivariable linear regression was applied to quantify the incremental contribution of clinical variables, functional capacity, and biomarkers. Results: The median age was 72 years, and 52.7% of the participants were women. The median 6MWT distance was 340 m (75.9% of predicted), and the median EQ-5D index was 0.76. The baseline clinical regression model (age, sex, atrial fibrillation, and glomerular filtration rate) explained 23.5% of EQ-5D variance. The addition of functional capacity increased explained variance to 45.2% (ΔR² = +0.217). The inclusion of IL-6 and NT-proBNP provided a modest additional increase (R² = 0.468; ΔR² = +0.042 in addition to Model 2). In the fully adjusted model, functional capacity (β = 0.376, p < 0.001) and IL-6 (β = −0.185, p < 0.05) remained independent predictors, whereas NT-proBNP lost significance. Conclusions: In stable HFpEF, objective functional capacity represents the dominant determinant of QoL, while inflammatory activation provides an independent but smaller contribution. Functional assessment may therefore be central to patient-centered phenotyping and therapeutic targeting.

Background/Objectives: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome characterized by systemic inflammation and impaired functional capacity. Interleukin-6 (IL-6) is implicated in HFpEF pathophysiology, but the influence of IL6 genetic variability on its clinical impact remains unclear. This study investigated the associations of circulating IL-6, IL6 polymorphisms, and functional severity in HFpEF. Methods: This single-center observational study included 110 clinically stable HFpEF patients. Clinical, laboratory, and functional data, including C-reactive protein (CRP), IL-6 serum levels were collected. The neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio were calculated from complete blood count, while IL6 polymorphisms rs1800795 and rs1818879 were genotyped using TaqMan assays. Functional status was assessed using NYHA classification, the six-minute walk test (6MWT), and the Borg dyspnea scale. Results: Among carriers of the rs1800795 G/C+C/C genotype, elevated IL-6 was associated with higher odds of advanced symptoms (NYHA III; OR = 6.08, 95% CI 1.45–25.45, p = 0.014) and reduced exercise capacity (6MWT; OR = 6.55, 95% CI 1.60–26.72, p = 0.009). The combined effect of elevated IL-6 levels and the rs1800795 genotype was also associated with greater dyspnea burden, as assessed by the Borg scale (OR = 1.17, 95% CI 1.02–1.34, p = 0.029). In multivariable analysis, the NYHA and 6MWT models additionally retained NLR as an independent predictor, while the Borg model included advanced age, pulmonary hypertension, and the combined effect of elevated IL-6 levels and the rs1800795 genotype. Conclusions: The observed combined effect of elevated IL-6 levels and the rs1800795 genotype on symptom burden and functional impairment suggests that combined inflammatory and genetic profiling may improve severity assessment in HFpEF.