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Objective. The aim of present study was to analyze the serum lipid profile parameters in patients with type 2 diabetes mellitus (T2DM) and comorbidities [overweight/obesity and/or chronic pancreatitis (CP)] to determine the contribution of these pathologic factors to lipid metabolism disorders in T2DM. Methods. The study involved 579 type 2 diabetic (T2D) patients with comorbid overweight/ obesity and/or CP. The serum lipid panel parameters [total cholesterol (TC), triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C)] were determined by commercially available kits on a Cobas 6000 analyzer (Roche Hitachi, Germany). Low-density lipoprotein cholesterol (LDL-C), non-HDL-C, and remnant cholesterol (RC) levels were calculated using formulas. The data were statistically analyzed using STATISTICA 7.0. Results. It was shown that dyslipidemia in T2D patients is characterized by unidirectional changes regardless the presence/absence of comorbid overweight/obesity or CP. At the same time, the most severe dyslipidemia was detected in T2D patients with a combination of comorbid over-weight/obesity and CP. Both the elevated body mass index (BMI) and CP can aggravate lipid metabolism disorders in T2DM. In our study, however, the BMI increase positively correlated with the number of dyslipidemia patients characterized by exceeding all target lipid levels for diabetic patients. This is in contrast to T2D patients with normal body weight and comorbid CP, in whom only LDL-C and TG exceeded the target lipid levels. Conclusions. A combination of comorbidities, such as obesity and CP in T2D patients, produced a mutually aggravating course defined particularly by common pathogenic links, insulin resistance, chronic generalized low-intensity inflammation, endothelial dysfunction, and dyslipidemia caused primarily by triglyceridemia.

This study aimed to evaluate changes of the lipid panel data in patients with comorbid type 2 diabetes mellitus (T2DM) and subclinical hypothyroidism (SCH) and to identify the probable prognostic values of the lipid profile for macrovascular complication (MVC) development. The study included 370 patients presented with only T2DM and 30 patients suffering from both T2DM and SCH. Receiver operating characteristic (ROC) analysis was used to identify prognostically significant values of the lipid profile with the optimal ratio of sensitivity and specificity for MVC development. All lipid profile values in the patients with T2DM combined with SCH were significantly higher compared to those with only T2DM. At the same time, SCH + T2DM increased the risk of exceeding target levels of triglycerides by 2.9 times and HDL-C by 4.1 times. Analysis of lipid profile values according to macrovascular involvement showed that total cholesterol, LDL-C and non-HDL-C in patients with T2DM and SCH were significantly higher compared to those with only T2DM. The levels of triglycerides >1.65 mmol/L, non-HDL-C >3.74 mmol/L and remnant cholesterol >0.74 mmol/L determined by the ROC analysis can be used for stratification of patients with T2DM combined with SCH into the category of increased risk of MVC development.

Introduction:The aim of research was to assess the melatonin concentrations in the early neonatal period as a predictor of adverse outcomes of late neonatal period in preterm infants and to estimate its optimal predictive cut-off values. Materials and methods: A total of 115 preterm infants admitted to the neonatal intensive care unit were screened for eligibility, five did not meet the criteria, six parents declined the participation. So, a total of 104 preterm infants with gestational age 25-34 weeks were included in research. The concentration of melatonin in urine was determined by the Enzyme Immunoassay method (Human Melatonin Sulfate ELISA kit, Elabscience, China). The Mann-Whitney U-test and analysis of the receiver operating characteristic (ROC) curve were used in statistical analysis. Results: Analysis of the ROC curves has revealed optimal cut-off values for urinary melatonin concentration to predict late outcomes. Melatonin concentration below 3.58 ng/ml with sensitivity of 72% can predict development of retinopathy of prematurity (ROP) (AUC = 0.73; 95% confidence intervals (CI) 0.61-0.86). Good diagnostic accuracy (AUC = 0.80; 95% CI 0.67-0.93) has been shown for bronchopulmonary dysplasia (BPD). The optimal cut-off value for melatonin concentration in BPD prediction is 3.71 ng/ml (sensitivity 80%, specificity 64%). Urinary melatonin concentration below 3.79 ng/ml can be associated with late-onset sepsis (AUC = 0.76; 95% CI 0.64-0.87; sensitivity 72%; specificity 62%). There were no significant associations between melatonin concentration and necrotizing enterocolitis (P = 0.912). Conclusion: Urinary melatonin concentration below the certain cut-off values in the early neonatal period may serve as one of the predictors of adverse outcomes such as BPD, ROP, and late-onset sepsis in the late neonatal period in preterm infants.

ACE2 impact on the severity of COVID-19 is widely discussed but still controversial. To estimate its role in aspects of the main risk factors and comorbidities, we involved post-COVID-19 patients in Ternopil region (Ukraine). Recruitment period was July 2020 to December 2021. Medical records, treatment modalities and outcomes were recorded and analyzed. Serum human ACE2 protein was measured with Cusabio ELISA kits (Houston, TX, USA). Statistical analysis was performed with SPSS21.0 software (SPSS Inc., Chicago, IL, USA). The level of ACE2 serum protein was significantly higher (p < 0.001) in patients with mild symptoms compared to more severe course of disease, and inversely had changed from 1 to 90 days after recovery. In patients with mild COVID-19, ACE2 level significantly decreased over time, while among critical patients, it increased by 34.1percent. Such results could be explained by ACE2 shedding from tissues into circulation. Loss of the membrane-bound form of the enzyme decreases the virus entry into cells. Our studies did not identify any sex-related ACE2 serum levels correlation. The most common comorbidities were hypertension, cardiovascular diseases, respiratory diseases and diabetes mellitus. All comorbidities except respiratory diseases contribute to the severity of disease and correlate with ACE2 blood serum level.