ABC | Volume 114, Nº1, January 2019

Original Article Adar et al. Aortic calcification and non-dipper blood pressure Arq Bras Cardiol. 2020; 114(1):109-117 drugs or lipid-lowering drugs, respectively. The institutional ethics committee approved the study protocol. Patients were divided into two groups according to circadian BP pattern; non-dipper and dipper group. Ambulatory blood pressure monitoring ABPM studies were carried out using a Mobil-O-Graph (M-o-G; I.E.M, Germany) monitoring device. The first hour was discarded from the analysis. BP readings were obtained automatically at the 30-min interval and if >85% of the measurements were valid then it was included in the analyses. Daytime, nighttime and 24-hour BP data and the percentage of the decrease in nighttime systolic BP vs. daytime systolic BP were recorded. The default setting for daytime (07:00 to 23:00) and nighttime (23:00 to 07:00) hours were modified appropriately based on the patient’s feedback. NDBP pattern was defined as the reduction of ≤ 10 % in nighttime systolic BP as compared to the daytime systolic BP. Evaluation of AAC All patients had chest radiography in the PA view. The standard PA chest radiograph (40 cm×40 cm; Curix HT 1.000G Plus, Agfa, Mortsel, Belgium) was acquired with the patient standing up (Thoramat, Siemens, Erlangen, Germany). The focus–patient distance was 150 cm. An automated exposure control with a fixed tube voltage of 117 kV was used. We noted the presence of calcification in the aortic knob. AAC was graded as follows: Grade 0, no visible calcification; Grade 1, small spots of calcification or thin calcification; Grade 2, one or more areas of thickened calcification, and Grade 3, circular calcification on the aortic knob 13 (Figure 1). One hundred randomly selected chest radiography for evaluation of AAC were independently evaluated by two cardiologists, who was unaware of the result of the patient’s ABPM data to assess the reliability of AAC diagnosis and Kappa value was detected as 0.812 and p < 0.001. Laboratory tests A venous blood sample was collected from each participant under fasting conditions. Fasting blood glucose, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglyceride and creatinine were measured by standard laboratory methods. Glomerular filtration rate (GFR) was calculated using CKD-EPI Creatinine Equation. 14 Echocardiographic examination All patients were examined in the left lateral decubitus position using by a commercially available system (Vivid 4 GE Medical System, Horten, Norway) with a phased-array 3.5-MHz transducer. The conventional M-mode and B-mode parameters were measured in accordance with the American Society of Echocardiography guidelines. Left ventricular end-diastolic (LVEDD) and end-systolic (LVESD) diameters, and posterior (PWT) and septal (IVST) wall thicknesses were measured. Left ventricular ejection fraction was measured by using the Teichholz method. Left ventricular mass (LVM) was calculated using the Devereux equation: LVM = 0.8{1.04[([LVEDD + IVST +PWT] 3 – LVEDD 3 )]} + 0.6. 15 Left ventricular mass index (LVMI) was calculated by dividing the LVMby body surface area. LVH was defined as LVMI > 115 g/m 2  for men and 95 g/m 2 for women. 16 Based on relative wall thickness (2 x PWT/LVEDD) and the presence or absence of LVH various types of the left ventricular geometrical pattern were defined (normal geometry, concentric LVH, eccentric LVH, and concentric remodeling). Statistical analysis Continuous variables were expressed as mean (standard deviation) or median (interquartile range (IQR)), and categorical variables as number (percentage). The distributions of the continuous variables across the study groups were tested with the Kolmogorov–Smirnov test. Normally distributed data were compared using the Independent Samples t-test and data with non-normal distribution were compared using the Mann-Whitney U test. Categorical data were compared using the chi-square or Fisher’s exact tests when needed. Univariate and multivariate logistic regression analyses were conducted to assess the association of AAC and NDBP pattern. In multivariate regression analysis (Enter method), the effect size was adjusted for variables with a univariate significance level of < 0.1. Adjusted odds ratios (OR), along with their 95%CIs were presented. A 2-tailed p-value < 0.05 was considered statistically significant. All statistical analyses were performed using the IBM SPSS software (IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.) Results A total of 406 patients (mean age 51.3 female 58%) were included. Two hundred sixty-one (64%) had NDBP pattern and classified as non-dipper group. The remaining 145 (36%) patients who had dipper BP pattern were classified as dipper group. As compared to the dipper group, the non-dipper group was older (p<0.001), had higher LVMI (p=0.007), prevalence of LVH (p = 0.013), prevalence of HT (p = 0.049) and higher serum triglyceride level (p = 0.013). GFR was significantly lower in the non-dipper group (p < 0.0001). Groups were similar with respect to the remaining baseline characteristics shown in Table 1. There was no difference in daytime DBP, 24-hour SBP and 24-h DBP values between non-dipper and dipper groups. However, daytime SBP was lower in non-dipper groups (p = 0.012). In addition, nighttime SBP (p < 0.0001) and DBP (p < 0.0001) values were significantly higher in non-dipper group (Table 2). Prevalence of AAC was 57% in our study population. Non-dipper group had significantly higher prevalence of AAC (grade ≥ 1) on chest radiography (p < 0.0001) as compared to the dipper group (Table 3). Age, body mass index, female gender, HT, GFR, LVMI, presence of LVH, LV geometric pattern of concentric hypertrophy and AAC were associated with the presence of NDBP pattern in univariate logistic regression analysis with a p-value of less than 0.1 (Table 4). Of these; age, body mass index, female gender, HT, GFR, LVMI, presence of LVH and AAC were entered in multivariate regression model. In the multivariate regression analysis, presence of AAC on chest radiography (OR 3.919, 95%CI 2.392 to 6.421) was the only independent predictors of NDBP pattern (Table 5). 110