Relationship Between Epicardial Adipose Tissue and Body Composition as Determined by Multi-Frequency Bioelectrical Impedance Analysis in Patients with Stage 5 Chronic Kidney Disease.

BACKGROUND The main cause of mortality among chronic kidney disease (CKD) patients is cardiovascular disease (CVD). Epicardial adipose tissue (EAT) is considered to be novel cardiovascular risk factor. We assessed EAT in non-dialyzed stage 5 CKD patients and explored the association of EAT with body composition as determined by multi-frequency BIA. MATERIAL AND METHODS The present included 70 stage 5 CKD patients who had not undergone dialysis and 40 healthy control subjects. EAT thickness was assessed by echocardiography. Hydration status and body composition were evaluated by multi-frequency bioelectrical impedance analysis. RESULTS Stage 5 CKD patients had significantly higher EAT thickness than healthy subjects (6.56±1.18 vs. 4.05±1.45, p<0.001). Fat tissue mass, systolic blood pressure (SBP), age, fat tissue index, and body mass index were positively correlated with EAT thickness in the CKD patient group (p<0.05). Lean tissue mass, lean tissue index (LTI), and high-density lipoprotein (HDL) were negatively correlated with EAT thickness in the CKD patient group (p<0.05). Stepwise multiple regression analysis showed that age, SBP, and LTI were independently associated with EAT thickness in CKD patients. CONCLUSIONS We found significantly higher EAT thickness in stage 5 CKD patients who were not on dialysis compared to healthy controls. EAT was significantly associated with age, SBP, and LTI in CKD patients. Interventions to reduce the risk factors associated with EAT thickness might protect against CVD disease in CKD patients.

Evaluating Mortality Predictors in COVID-19 Intensive Care Unit Patients: Insights into Age, Procalcitonin, Neutrophil-to-Lymphocyte Ratio, Platelet-to-Lymphocyte Ratio, and Ferritin Lactate Index.

INTRODUCTION: Numerous studies suggest that alterations in blood parameters, such as changes in platelet, lymphocyte, hemoglobin, eosinophil, and basophil counts; increased neutrophil counts; and elevated neutrophil/lymphocyte and platelet/lymphocyte ratios, signal COVID-19 infection and predict worse outcomes. Leveraging these insights, our study seeks to create a predictive mortality model by assessing age and crucial laboratory markers. MATERIALS AND METHODS: Patients were categorized into two groups based on their hospital outcomes: 130 survivors who recovered from their Intensive Care Unit (ICU) stay (Group 1) and 74 who died (Group 2). We then developed a predictive mortality model using patients' age, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), procalcitonin levels, and ferritin lactate (FL) index results. RESULTS: A total of 204 patients were included. Patients in Group 2 had a notably higher mean age compared to those in Group 1 (76 ± 11 vs. 66 ± 15 years) (p < 0.001). Using specific cut-off values, our analysis revealed varying effectiveness in predicting COVID-19 mortality: Those aged over 73 years showed 74% sensitivity and 60% specificity, with an area under the curve (AUC) of 0.701. Procalcitonin levels above 0.35 ng/mL balanced true-positive and -negative identifications well, achieving an AUC of 0.752. The FL index, with a threshold of 1228 mg/dL, had 68% sensitivity and 65% specificity with an AUC of 0.707. A PLR higher than 212 resulted in 48% sensitivity and 69% specificity, with an AUC of 0.582. An NLR higher than 5.8 resulted in 55% sensitivity and 63% specificity, with an AUC of 0.640, showcasing diverse predictive accuracies across parameters. The statistical analysis evaluated the effects of age (>73), procalcitonin levels (>0.35), FL > 1228, PLR > 212, and NLR > 5.8 on mortality variables using logistic regression. Ages over 73 significantly increased event odds by 2.1 times (p = 0.05), procalcitonin levels above 0.35 nearly quintupled the odds (OR = 5.6, p < 0.001), high FL index levels more than tripled the odds (OR = 3.5, p = 0.003), a PLR > 212 significantly increased event odds by 3.5 (p = 0.030), and an NLR > 5.8 significantly increased event odds by 1.6 (p = 0.043). CONCLUSIONS: Our study highlights significant predictors of mortality in COVID-19 ICU patients, including advanced age, elevated procalcitonin, FL index levels, the PLR, and the NLR.

The Role of Monocyte to High-Density Lipoprotein Cholesterol Ratio in Predicting the Severity of Proteinuria and Renal Dysfunction in Primary Nephrotic Syndrome.

INTRODUCTION: Monocyte to high-density lipoprotein (HDL) cholesterol ratio (MHR) has emerged as a novel marker of endothelial injury, inflammation, and oxidative stress. This study aimed to investigate the effect of MHR on primary nephrotic syndrome (NS) and its relationship with the severity of proteinuria. METHODS:  This study enrolled 161 patients newly diagnosed with primary NS and 100 healthy individuals. Demographic characteristics of the patients, primary NS diagnosis, basal laboratory parameters, the amount of 24-hour urinary protein excretion, and MHR were recorded. The groups were compared regarding these parameters. RESULTS:  MHR was significantly higher in patients with primary NS compared with the healthy group (12.89 ± 4.86 and 9.71 ± 2.30, respectively; p < 0.001). There was no difference between the groups in terms of age and sex. The amount of protein in the 24-hour urine in patients with a diagnosis of primary NS was 6.91 ± 3.73 g/day. The correlation analysis showed a positive correlation between MHR and the amount of proteinuria (r = 0.519, p < 0.001) and creatinine level (r = 0.167, p = 0.034). The multivariate regression analysis found that the severity of proteinuria was independently correlated to MHR (p < 0.001). According to the receiver operating characteristic curve analysis, the optimal cut-off level for MHR in NS was 10.08 (area under the curve of 0.704, sensitivity of 68%, and a specificity of 62%). CONCLUSION:  Our study is the first to compare the severity of proteinuria and renal functions with MHR in patients with primary NS. We believe that MHR can be used as a biomarker to determine inflammation, endothelial injury, and the level of oxidative stress, and may be useful to predict prognosis in patients with primary NS.