This cross-sectional study was conducted in the Department of Clinical and experimental Medicine, University of Catania, Italy. The aim was to investigate the association between RHF and early markers of cardiovascular disease in subjects with prediabetes.
Study Population: 435 subjects with no previous history of diabetes and cardiovascular disease attending our University Hospital for cardiometabolic risk evaluation were consecutively screened based on inclusion/exclusion criteria. The inclusion criteria were the following: age range between 35 and 65 years; body mass index (BMI) between 18.2–40 kg/m2.
The exclusion criteria were: a previous history of diabetes, previous history of overt cardiovascular events (stroke, ischemic heart disease, chronic obstructive peripheral arteriopathy, or heart failure), chronic kidney disease (eGFR < 60 ml/min/1.73 m2), anemia, or hemoglobinopathies, use of medications known to affect glucose metabolism, positivity for antibodies to hepatitis C virus or hepatitis B surface antigen, clinical evidence of advanced liver disease, chronic inflammatory disease or other chronic diseases and/or recent history of acute illness, malignant disease, and drug or alcohol abuse.
All subjects underwent a complete evaluation of glycemic status including fasting glucose, oral glucose tolerance test (OGTT) and glycated hemoglobin A1c (HbA1c). Only subjects with prediabetes participated in the study.
75-g OGTT was performed with basal, 1-h and 2-h sampling for plasma and insulin as previously described [13, 14]. Glucose tolerance status was defined on the basis of fasting glycemia, OGTT and HbA1c according to American Diabetes Association recommendations . Prediabetes was defined as a fasting glycemia between 100–125 mg/dL and/or a 120-min after OGTT glycemia between 140–199 mg/dL and/or a HbA1c between 5.7–6.4%. Homeostatic model assessment for insulin resistance (HOMA-IR) and Matsuda index were calculated as previously described . Body weight and height were measured, and BMI was calculated as weight (kg)/[height (m)]2. Blood pressure (BP) was measured with a calibrated sphygmomanometer after the subject had rested in the supine position for 10 min. Venous blood samples were drawn from the antecubital vein on the morning after an overnight fast. Baseline venous blood samples were obtained for the measurement of plasma glucose, total cholesterol, high density lipoprotein (HDL) cholesterol, triglycerides, and high sensitivity C-reactive protein (hs-CRP). Low density lipoprotein (LDL) cholesterol concentrations were estimated using the Friedewald formula
Plasma glucose, serum creatinine, total cholesterol, triglycerides, HDL cholesterol, and hs-CRP were measured using available enzymatic methods.
HbA1c was measured via high performance liquid chromatography using a National Glycohemoglobin Standardization Program and standardized to the Diabetes Control and Complications Trial assay reference . Chromatography was performed using a certified automated analyzer (HPLC; HLC-723G7 hemoglobin HPLC analyzer; Tosoh Corp.) (normal range 4.25–5.9% [23–41 mmol/mol]).
Pulse wave analysis
Arterial stiffness evaluation was performed with the patients in fasting status and the explicitly expressed recommendation to avoid smoking and coffee intake in the morning of the procedure. All measurements were performed from the right radial artery by applanation tonometry using a Millar tonometer (SPC-301; Millar instruments, Houston, TX.) as previously described . Data were collected directly into a desk-top computer and processed with the SphygmoCor CvMS (Atcor Medical, Sidney, Australia), which allows continuous on-line recording of the radial artery pressure waveform. The integral system software was used to calculate an average radial artery waveform, and generate the corresponding ascending aortic pressure waveform.
The aortic waveform was subjected to further analysis for calculation of aortic pressure augmentation pressure (Aug), the augmentation Index (AugI, calculated by dividing augmentation by pulse pressure) and Buckberg’s subendocardial viability ratio (SEVR, area of diastole divided by area of systole during one cardiac cycle in the aorta). Pulse pressure is the difference between systolic and diastolic blood pressures.
Pulse wave velocity
The SphygmoCor CvMS (AtCor Medical, Sydney, Australia) system was used for the determination of the pulse wave velocity (PWV) as previously described . This system uses a tonometer and two different pressure waves obtained at the common carotid artery (proximal recording site) and at the femoral artery (distal recording site). The distance between the recording sites and suprasternal notch was measured using a tape measure. An electrocardiogram was used to determine the start of the pulse wave. The PWV was determined as the difference in travel time of the pulse wave between the two different recording sites and the heart, divided by the travel distance of the pulse waveform. The PWV was calculated on the mean of 10 consecutive pressure waveforms to cover a complete respiratory cycle.
Carotid Ultrasound examination
Ultrasound scans were performed using a high-resolution B-mode ultrasound system (MyLab 50 Xvision; Esaote Biomedica SpA, Florence, Italy) equipped with a 7.5-MHz linear array transducer as previously described . To exclude interobserver variability, a single physician who was blinded to the clinical and laboratory characteristics of the patients performed all ultrasound examinations. The subjects were examined in the supine position. Longitudinal scans were performed, and measurements were conducted at a total of six plaque-free sites 1 cm proximal to the carotid bulb. The obtained values were averaged and are presented as the mean of the intima media thickness (IMT) of the common carotid artery. Plaques, defined as a clearly isolated focal thickening of the intima-media layer with a thickness of 1.4 mm, were not observed in any individuals. All measurements were obtained in diastole, assessed as the phase in which the lumen diameter is at its smallest and the IMT is at its largest.
The sample size was calculated based on Aug using a level of significance (α) set to 5% and power (1- β) to 80%. We based the power calculation on previous studies examining Aug among patients with early alteration of glucose homeostasis and controls. The estimated sample size was 60 patients per group. Statistical comparisons of clinical and biomedical parameters were performed using Stat View 6.0 for Windows. Data are given as means ± SD or median (IQR). Each variable’s distributional characteristics including normality were assessed by the Kolmogorov-Smirnov test. Statistical analysis consisted of ANOVA followed by Bonferroni post-hoc test for continued variables and χ2 test for non-continuous variables. All analyses were adjusted for age and sex. A P value less than 0.05 was considered statistically significant. When necessary, numerical variables were logarithmically transformed to reduce skewness, and values were expressed as median and interquartile range.
In order to identify variables independently associated with variations of Aug and SEVR, we performed three multivariate regression models: the first model included cardiovascular risk factors (age, BMI, sex, smoking status, systolic and diastolic BP, total cholesterol, HDL cholesterol, triglycerides, LDL cholesterol, and uric acid); the second model included variables related to glycemic status (fasting glucose, HbA1c, 1-h glucose and 2-h glucose, and HOMA-IR). Subsequently, variables reaching significance were inserted into a multiple regression model including eGFR. The variance inflation factor was used to check for the problem of multi-collinearity among the predictor variables in multiple regression analysis.
The local ethics committee approved the study. Informed consent was obtained from each participant.