Cardiovascular Risk Estimated by UKPDS Risk Engine Algorithm in Diabetes

Cardiometabolic Risk: Characteristics of the Intestinal Microbiome and the Role of Polyphenols

Cardiometabolic diseases like hypertension, type 2 diabetes mellitus, atherosclerosis, and obesity have been associated with changes in the gut microbiota structure, or dysbiosis. The beneficial effect of polyphenols on reducing the incidence of this chronic disease has been confirmed by numerous studies. Polyphenols are primarily known for their anti-inflammatory and antioxidant properties, but they can also modify the gut microbiota. According to recent research, polyphenols positively influence the gut microbiota, which regulates metabolic responses and reduces systemic inflammation. This review emphasizes the prebiotic role of polyphenols and their impact on specific gut microbiota components in patients at cardiometabolic risk. It also analyzes the most recent research on the positive effects of polyphenols on cardiometabolic health. While numerous in vitro and in vivo studies have shown the interaction involving polyphenols and gut microbiota, additional clinical investigations are required to assess this effect in people.

Endocan is Related to Increased Cardiovascular Risk in Type 2 Diabetes Mellitus Patients

Aim: Type 2 diabetes mellitus (T2D) patients have an increased risk for cardiovascular disease (CVD). Different algorithms are used for the CVD risk quantification and United Kingdom Prospective Diabetes Study (UKPDS) score was among the most validated. Endocan is a novel endothelial dysfunction marker. The aim was to explore the potential relationship between serum endocan level and UKPDS risk engine score [which enables calculation of the 10-year risk of nonfatal and fatal coronary heart disease (eCHD) and stroke] in T2D patients. Materials and Methods: The study included a cohort of 104 patients with T2D (of them 52.8% men), with median age 66 years and body mass index (BMI) = 30.7 kg/m2. Patients were divided into: low (<15%), moderate (≥15% and <30%), and high-risk UKPDS category (≥30%). Results: In multivariable regression analysis (when adjusted for sex, BMI and/or hip circumference), endocan was the independent predictor for moderate and high estimated risks (nonfatal eCHD, fatal eCHD, and nonfatal stroke risk). In the Model for high nonfatal eCHD [areas under curve (AUC) = 0.895] and high fatal eCHD (AUC = 0.860) endocan indicated good clinical accuracy, and an excellent accuracy in discriminating patients with high risk for nonfatal stroke risk (AUC = 0.945). Conclusion: Endocan was the independent predictor for moderate and high estimated risks (i.e., nonfatal and fatal CHD and nonfatal stroke risk scores) in T2D patients. When included in models with sex and obesity indices endocan demonstrated good clinical accuracy in discriminating T2D patients with high risk for nonfatal and fatal eCHD and nonfatal stroke risk from those patients with low risk.

Relationship between Adipocytokines, Nontraditional Anthropometric Indices and Coronary Heart Disease Risk in Diabetic Patients

INTRODUCTION

Diabetes mellitus type 2 (T2DM) significantly increase the risk of cardiovascular (CV) disease morbidity and mortality. This study aimed to evaluate the potential of some novel anthropometric indices and adipocytokines to evaluate CV risk among T2DM patients.

METHODS

A total of 112 patients (men, 57; women, 55) with T2DM visiting Family Medicine and Endocrine counseling in the area of Health centers of Sarajevo Canton were included in this study. The sera samples were analyzed for fasting blood glucose (FBG), HbA1c, lipid profile parameters, adiponectin, and resistin levels. The Adiponectin/Resistin Index (A/R Index) was estimated using the formula. The novel anthropometric measurements, including the Conicity index (CI), Lipid Accumulation Product (LAP), visceral adiposity index (VAI), abdominal volume index (AVI), and Body adiposity index (BAI) were estimated. The 10-year risk for coronary heart disease (CHD) and fatal coronary heart disease (fCHD) is calculated by using UKPDS Risk software.

RESULTS

The adiponectin was shown as a statistically significant negative association with CHD in female subjects, and the A/R index as a statistically significant association with CHD and fCHD in male subjects. The AVI is superior to the CI, LAP, VAI, and BAI in assessing cardiometabolic risk in T2DM patients.

CONCLUSIONS

Our study indicated that measuring adiponectin and A/R index, together with measuring AVI as a measure of general volume, can be used as surrogates in the evaluation of high cardiovascular risk among T2DM patients.

Development and validation of a model to predict cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke in patients with type 2 diabetes mellitus and established atherosclerotic cardiovascular disease

Background

Among individuals with atherosclerotic cardiovascular disease (ASCVD), type 2 diabetes mellitus (T2DM) is common and confers increased risk for morbidity and mortality. Differentiating risk is key to optimize efficiency of treatment selection. Our objective was to develop and validate a model to predict risk of major adverse cardiovascular events (MACE) comprising the first event of cardiovascular death, myocardial infarction (MI), or stroke for individuals with both T2DM and ASCVD.

Methods

Using data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS), we used Cox proportional hazards models to predict MACE among participants with T2DM and ASCVD. All baseline covariates collected in the trial were considered for inclusion, although some were excluded immediately because of large missingness or collinearity. A full model was developed using stepwise selection in each of 25 imputed datasets, and comprised candidate variables selected in 20 of the 25 datasets. A parsimonious model with a maximum of 10 degrees of freedom was created using Cox models with least absolute shrinkage and selection operator (LASSO), where the adjusted R-square was used as criterion for selection. The model was then externally validated among a cohort of participants with similar criteria in the ACCORD (Action to Control Cardiovascular Risk in Diabetes) trial. Discrimination of both models was assessed using Harrell’s C-index and model calibration by the Greenwood-Nam-D’Agostino statistic based on 4-year event rates.

Results

Overall, 1491 (10.2%) of 14,671 participants in TECOS and 130 (9.3%) in the ACCORD validation cohort (n = 1404) had MACE over 3 years’ median follow-up. The final model included 9 characteristics (prior stroke, age, chronic kidney disease, prior MI, sex, heart failure, insulin use, atrial fibrillation, and microvascular complications). The model had moderate discrimination in both the internal and external validation samples (C-index = 0.65 and 0.61, respectively). The model was well calibrated across the risk spectrum—from a cumulative MACE rate of 6% at 4 years in the lowest risk quintile to 26% in the highest risk quintile.

Conclusion

Among patients with T2DM and prevalent ASCVD, this 9-factor risk model can quantify the risk of future ASCVD complications and inform decision making for treatments and intensity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01603-8.

Implication of Salivary Biochemical Parameters for Diagnosis and Prognosis of Type 2 Diabetes Mellitus

Background. Clinical laboratory diagnosis and prognosis for diabetes mellitus is performed using blood as a major specimen; however, saliva may represent as an alternative noninvasive specimen of choice. This study aims to evaluate salivary biochemical parameters in diabetic and healthy individuals to substantiate saliva’s role in the diagnosis and prognosis of type 2 diabetes mellitus (T2DM). Methods. This case-control study included 150 T2DM patients and 150 apparently healthy individuals. Socio-demographic data and anthropometric measurements were recorded using a standard questionnaire. Correlation between salivary and blood levels for each parameter was determined using Pearson correlation. Linear regression was performed to estimate the blood levels of the parameters from their salivary levels. Receiver operating characteristics (ROC) analysis was done to determine the diagnostic ability of salivary glucose and establish a sensitivity, specificity, and cut-off value. Results. Salivary glucose, TC, LDL-C, urea, and creatinine were significantly higher in people with diabetes than in the control population ( $p<0.05$ ). A significant positive correlation was found between salivary and blood parameters including glucose, TC, TG, LDL-C, urea, and creatinine except for HDL-C in both case and control groups. The linear relationship for each parameter, except glucose in case population and HDL-C in case, control, and the total population was observed between blood and saliva. ROC analysis gave a cut-off value of 1.9 mg/dl for salivary glucose with 71.4% sensitivity and 72.3% specificity. Conclusion. Salivary estimation significantly reflects the blood parameters in this study, indicating that saliva can be a noninvasive specimen for the diagnosis and prognosis of T2DM.

Associations of Chronic Diabetes Complications and Cardiovascular Risk with the Risk of Obstructive Sleep Apnea in Patients with Type 2 Diabetes

Background: Type 2 diabetes mellitus (T2DM) is associated with increased mortality and morbidity, including cardiovascular diseases and obstructive sleep apnea (OSA). The aim of this study was to assess the associations between cardiovascular risk, chronic diabetes complications and the risk of OSA in adult patients with T2DM. Methods: The study included 529 patients with T2DM in whom moderate-to-severe OSA risk was assessed using the STOP-Bang questionnaire, dividing the subjects into two groups: group 1: STOP-Bang score <5, and group 2: STOP-Bang score ≥5, respectively. In all the subjects, cardiovascular risk was assessed using the UKPDS risk engine. Statistical analysis was performed using SPSS 26.0, the results being statistically significant if p value was <0.05. Results: 59% of the subjects scored ≥5 on the STOP-Bang questionnaire. We recorded statistically significant differences between the two groups regarding diabetes duration, HbA1c, HOMA-IR, albuminuria, as well as cardiovascular risk at 10 years for both coronary heart disease (CHD) and stroke (p < 0.05). Furthermore, through logistic regression, adjusting for confounding factors, we demonstrated that the STOP-Bang score ≥ 5 is a risk factor for 10-year fatal and nonfatal CHD risk. Conclusions: It is extremely important to screen and diagnose OSA in patients with T2DM, in order to improve the primary and secondary prevention of cardiovascular events in these patients.

The Evaluation of Cardiovascular Risk in Diabetic Patients

AIM

The aim of the study was to evaluate cardiovascular risk in patients with diabetes mellitus type 2 according to gender.

METHODS

The monitoring was designed as a retrospective analysis of data obtained from the documentation of the diabetic outpatients treated with the dipeptidyl peptidase-4 inhibitors (DPP4is) or sodium–glucose co-transporter-2 (SGLT2). Cardiovascular risk was assessed according to UKPDS risk engine.

RESULTS

The levels of HbA1c decreased throughout the whole study. Sixty per cent of patients achieved an HbA1c level <8% after 18 months. Both men and women had similar glycaemic compensation. Men had a significantly higher risk of fatal coronary heart disease (CHD) (p < 0.001), stroke (p < 0.01) and fatal stroke (p < 0.01) compared to women. We found the risk of fatal CHD to be 38-fold higher in men compared to women (p < 0.01).

CONCLUSION

Potential cardiovascular effects of antidiabetic treatment should be clearly defined with possible different effects according to gender. We found a much higher risk in men than women, even when their glycaemic compensation was comparable.

Cardiovascular Biomarkers and Calculated Cardiovascular Risk in Orally Treated Type 2 Diabetes Patients: Is There a Link?

The aim of the study was to test the correlation of serum levels of asymmetric dimethylarginine (ADMA), endothelin 1 (ET-1), N-terminal brain natriuretic pro-peptide (NT-proBNP), and placental growth factor (PIGF-1) with estimated cardiovascular (CV) risk. The study group was composed of 102 women and 67 men with type 2 diabetes, having their glycemic and metabolic parameters assessed. All were on oral antidiabetic drugs. Serum levels of NT-proBNP and PIGF-1 were measured by electro-hemi-luminescence on an Elecsys 2010 analyzer. Enzymatic immunoassays were used for ADMA and ET-1. The Framingham Risk Score (FRS), the UKPDS 2.0 and the ADVANCE risk engines were used to calculate cardiovascular risks while statistical analysis was performed on SPSS. Levels of PIGF-1 showed no correlation with the calculated CV risks. The same was true for ADMA, except for a weak correlation with the UKPDS-based 10-year risk for stroke (Pearsons's R=0.167, p=0.039). Plasma levels of ET-1 were correlated with the UKPDS-based 10-year risk for stroke (R=0.184, p=0.032) and fatal stroke (R=0.215, p=0.012) only. NT-proBNP was significantly correlated with all CV risk calculations: ADVANCE-based 4-yr risk (Spearman's Rho=0.521, p<0.001); UKPDS-based 10-year risk for: CHD (Rho=0.209, p=0.01), fatal CHD (Rho=0.282, p<0.001), stroke (Rho=0.482, p<0.001), fatal stroke (Rho=0.505, p<0.001); and 10-year FRS risk (Rho=0.246, p=0.002). In conclusion, ADMA and PIGF-1 did not seem useful in stratifying CV risk while ET-1 is linked to the risk of stroke, and NT-proBNP to all CV risk estimations.