CARDIOVASCULAR RISK FACTORS & TARGET ORGAN DAMAGE IN GREEK HYPERTENSIVES C. Liakos, 1 G. Vyssoulis, 1 E. Karpanou, 2 S-M. Kyvelou, 1 V. Tzamou, 1 A. Michaelides, 1 A. Triantafyllou, 1 P. Spanos, 1 C. Stefanadis 1 (1) 1 st Cardiology Depart., University of Athens Medical School, Hippokration Hospital, Athens, Greece (2) 1 st Cardiology Depart., Antihypertension Center, Onassis Cardiac Surgery Center, Athens, Greece Vyssoulis G, Karpanou E, Liakos C et al. J Hum Hypertens 2012; 26: 443-451.
Declaration of Conflicting Interest The authors have no conflict of interest to declare.
Cardiovascular risk factors in hypertensive patients Arterial hypertension (AH) often coexists with other metabolic and cardiovascular (CV) risk factors (RFs), such as: Diabetes Obesity Dyslipidemia Smoking The presence of RFs and target organ damage (TOD) should be ascertained to assess global CV risk and determine the urgency, intensity and type of treatment required. Mancia et al. J Hypertens 2007; 25: 1105-1187. Mancia et al. J Hypertens 2009; 27: 2121-2158.
CV risk factors in hypertensive patients in USA 20% of hypertensive patients do not have any concomitant RF. A cluster of 2 additional CV risk factors occurs in about 50% of hypertensive persons. 40% of coronary events in hypertensive men and 68% in hypertensive women are attributed to the clustering of 2 additional RFs. Belletti et al. Cardiovasc Diabetol 2010; 9: 7-18. Kannel. Am J Hypertens 2000; 13: S3-S10.
CV risk factors in hypertensive patients in USA 40% of US adult hypertensives are obese. 15% also have diabetes. 48% of hypertensive men, and 61% of hypertensive women, have dyslipidemia as well. Giles et al. J Clin Hypertens 2007; 9: 345-354. Ong et al. Hypertension 2008; 51: 1142-1148.
CV risk factors in hypertensive patients in Europe The GOOD survey 3370 patients from 289 sites in 4 European regions (Northwest, Mediterranean, Atlantic European Mainland, Central Europe) T2DM: 44% in Central Europe, 33% in Atlantic European Mainland, and 26% in Northwest and Mediterranean regions. MS: 68% in Central Europe, 60% in Atlantic European Mainland, 50% in Northwest and 52% in Mediterranean regions. Glu, TC and TG levels: were all highest in Central Europe. Farsang et al. J Hum Hypertens 2009; 23: 316-324.
CV risk factors in hypertensive patients in Europe Physical activity: was lowest in Central Europe. The prevalence of LVH: was highest in Central Europe. GOOD survey Conclusion: Hypertensive patients have multiple cardiometabolic RFs with the prevalence higher in Central Europe and the Atlantic European Mainland compared with Northwest and Mediterranean regions. Farsang et al. J Hum Hypertens 2009; 23: 316-324.
Purpose of the present study Such epidemiologic data are not currently available in Greek patients diagnosed with AH. The aim of this retrospective epidemiologic study was to determine cardiovascular (CV) risk factors (RFs) and target organ damage (TOD) clustering in Greek hypertensives stratified by gender and age.
Methods Study Population Inclusion Criteria The study comprised 21280 Caucasian adult ( 20 years) patients with uncomplicated arterial hypertension who were referred or self-referred to the outpatient hypertensive clinics of our institutions from 1985 to 2010. Exclusion Criteria Secondary hypertension Recent cerebrovascular event CAD Pregnant females T1DM Malignancy Renal failure Heart failure
Methods Material Patients under: Antihypertensive Rx (42.8%) or Hypolipidemic Rx (3.9%) underwent wash out for at least 15 days.
Methods Blood pressure measurements Hypertension was defined (JNC7 and ESH/ESC guidelines), using the average BP > 140/90 mmhg on at least 3 different office visits or the previous antihypertensive Rx. At each visit, office BP was measured and the average of 3 consecutive measurements was calculated, with the patient resting comfortably, back supported in the sitting position with the arm at the heart level, after a 10-15 min relaxation period. Patients with borderline office BP were subjected to 24-hour ambulatory BP monitoring (ABPM). Chobanian et al. Hypertension 2003; 42: 1206-1252. Mancia G et al. J Hypertens 2007; 25: 1105-1187. Mancia G et al. J Hypertens 2009; 27: 2121-2158.
Methods Anthropometric measurements Body weight and height Waist (W) and hip (H) circumference were measured Waist to hip circumference ratio (WHR) Body mass index (BMI) Body surface area (BSA) were calculated
Methods Laboratory measurements Total cholesterol (TC) Serum glucose (Glu) HDL cholesterol (HDL) Triglycerides (TG) LDL cholesterol (LDL) Apolipoprotein A 1 (ApoA 1 ) Plasma renin activity (PRA) Serum Creatinine (Cr) Estimated glomerular filtration rate (egfr) (MDRD formula) Apolipoprotein B (ApoB) Levey et al. Ann Intern Med 1999; 130: 461-470. Marcovina et al. Clin Chem 1994; 40: 586-592.
Methods Echocardiographic measurements Left Ventricular End-Systolic Diameter (LVESD) Left Ventricular End-Diastolic Diameter (LVEDD) Posterior Wall Thickness (PWT) Interventricular Septum Thickness (IVST) Left Ventricular Mass (LVM) Left Ventricular Mass Index (LVMI) Relative Wall Thickness (RWT) ASE/EAE recommendations Lang et al. Eur J Echocardiogr 2006; 7: 79-108.
Methods RFs determined Dyslipidemia Smoking Diabetes Obesity
Methods TOD determined LV hypertrophy Renal impairment
Methods Total 10-year CV risk calculation 2010 ACC/AHA guidelines Framingham Risk Score (FRS) - risk for CV events (coronary heart disease, stroke, peripheral artery disease and heart failure) - high if > 20%. HeartScore (HS) for low-risk countries (Greek version) - risk for fatal CV events - high if > 5%. Algorithms take into account traditional RFs: Age, sex, systolic BP, TC, smoking (FRS & HS) HDL, presence of DM or/and antihypertensive Rx (FRS) Greenland et al. J Am Coll Cardiol 2010; 56: e50-e103. D Agostino et al. Circulation 2008; 117: 743-753. Conroy et al. Eur Heart J 2003; 24: 987-1003.
Results
Results Clinical & Biochemical characteristics p < 0.001* Males Females All (n=11309) (n=9971) (n=21280) Age (years) 56.1 ± 13.5 59.2 ± 12.5 57.6 ± 13.1 Office SBP (mm Hg) 164.1 ± 12.9 166.2 ± 12.8 165.1 ± 12.9 Office DBP (mm Hg) 101.7 ± 8.0 99.0 ± 8.5 100.4 ± 8.4 Office HR (bpm) 73.7 ± 8.2 74.9 ± 8.0 74.3 ± 8.1 TC (mg/dl) 214 ± 41 226 ± 43 220 ± 42 TG (mg/dl) 131 ± 65 122 ± 61 127 ± 63 HDL (mg/dl) 45 ± 10 55 ± 13 49 ± 13 LDL (mg/dl) 143 ± 38 148 ± 40 145 ± 39 ApoA 1 (mg/dl) 141 ± 21 157 ± 25 149 ± 24 ApoB (mg/dl) 124 ± 34 128 ± 36 126 ± 35 * p remains statistical significant even after adjustment for age and BP
Results Biochemical characteristics & CV risk p < 0.001* Males Females All (n=11309) (n=9971) (n=21280) Glu (mg/dl) 103 ± 24 101 ± 24 102 ± 24 PRA (ng/ml/h) 1.25 ± 1.23 1.01 ± 1.02 1.14 ± 1.14 BMI (kg/m 2 ) 28.1 ± 3.8 28.4 ± 5.1 28.3 ± 4.5 WHR 0.92 ± 0.06 0.83 ± 0.07 0.88 ± 0.08 egfr (ml/min/1.73m 2 ) 78 ± 19 69 ± 17 74 ± 19 LVMI (g/m 2 ) 125 ± 17 116 ± 15 121 ± 17 CV Risk according to FRS (%) 35.0 ± 23.1 24.1 ± 16.6 29.9 ± 21.0 High risk (FRS>20%) patients (%) 68.7 50.7 60.2 CV Risk according to HS (%) 8.4 ± 10.3 6.2 ± 8.8 7.4 ± 9.7 High risk (HS>5%) patients (%) 48.6 36.2 42.8 * p remains statistical significant even after adjustment for age and BP
Results Prevalence of additional RFs Dyslipidemia Dyslipidemia only n:10392(48.8%) Additional RFs: 0 10.2% 1 53.1% n:5529(26.0%) 2 32.9% 3 3.7% Smoking Smoking only n:733(3.4%) n:790(3.7%) n:65(0.3%) n:1401(6.6%) Diabetes Diabetes only n:198(0.9%) Hypertension only n:2172(10.2%)
Results RF & TOD prevalence % of patients (n=21280) 100 90 85 80 70 60 50 49 40 30 33 30 38 24 20 12 10 0 Dyslipidemia Smoking DM Obesiy MS Low egfr LVH
Results RF & TOD prevalence according to Gender % of patients % of patients (n=21280) (n=21280) Males Females 100,0 100,0 90,0 90,0 80,0 80,0 70,0 70,0 60,0 60,0 50,0 50,0 40,0 40,0 30,0 30,0 20,0 20,0 10,0 10,0 0,0 0,0 85,285,2 85,285,2 38,1 38,1 28,1 28,1 11,9 11,1 11,911,1 p < 0.001 for all 33,3 27,0 33,3 27,0 36,7 39,4 36,7 39,4 Dyslipidemia Smoking DM Obesiy MS Low egfr LVH 17,6 31,8 17,6 31,8 45,4 53,3 45,4 Dyslipidemia DM MS LVH 53,3
Results Lipid & Glycemic profile in the 2 Genders % of patients % of patients (n=21280) (n=21280) 100,0 90,0 80,0 70,0 100 90 80 85,285,2 70,8 70 80,3 Males Females p < 0.001 for all Lipid profile 77,1 79,2 Glycemic profile 60,0 50,0 40,0 30,0 20,0 10,0 60 50 40 30 20 38,1 28,1 29,6 25,7 34,0 24,9 11,911,1 33,3 27,0 36,7 39,4 17,6 31,8 20,2 15,8 15,8 16,7 11,9 11,1 45,4 53,3 0,0 10 Dyslipidemia DM MS LVH 0 High TC High TG Low HDL High LDL IFG IGT DM
Results RF prevalence in Greece vs USA % of patients 100 USA Greece 90 85 80 70 60 55 50 40 30 40 30 33 20 15 12 11 10 0 T2DM Obesity Dyslipidemia Smoking Giles et al. J Clin Hypertens 2007; 9: 345-354. Ong et al. Hypertension 2008; 51: 1142-1148. Belletti et al. Cardiovasc Diabetol 2010; 9: 7-18.
Results CV risk according to Age & Gender 80 80 70 70 Framingham - males 60 60 Framingham - females 22.8% CV Risk (%) 50 40 30 CV Risk (%) 50 40 30 Heart -- males Heart -- females 19.5% 4.9% 20 20 10 10 5.9% 0 0 <30 <30-34 30-34 35-39 35-39 40-44 45-49 50-54 55-59 60-64 60-64 65-69 65-69 70-74 70-74 75-79 80-84 75-79 85+ 80-84 85+ Age (years)
Results Effect of menopause on CV risk Females of age: 45-54 years Pre-menopausal Post-menopausal p (n=1076) (n=1271) value Age (years) 49.0 ± 2.4 51.0 ± 2.9 < 0.0001 CV Risk according to FRS (%) 13.8 ± 8.1 16.9 ± 10.6 < 0.0001* CV Risk according to HS (%) 0.7 ± 0.5 1.1 ± 0.7 < 0.0001* * p remains statistical significant even after adjustment for age
Results Correlation of Age to RFs & CV risk Pearson r-values SBP DBP PP Glu PRA egfr LVMI FRS HS Age P < 0.01 for all Males 0.454-0.492 0.632 0.218-0.305-0.410 0.386 0.748 0.764 Females 0.491-0.594 0.689 0.175-0.242-0.398 0.359 0.655 0.759
Conclusions To our knowledge, this is the 1st large-scale study that determines RFs, TOD and CV risk in 21280 Greek hypertensives indicating the realworld situation in Greece. Almost 9 out of 10 patients of our hypertensive study population had 1 additional RFs. Mean CV risk (as calculated both with FRS and HS) was high (>20% and >5% respectively). Ageing does not seem to equalize CV risk between the two genders. Although prevalence of most RFs is higher in females, their CV risk is lower compared to males, pointing out the necessity of incorporating additional parameters in the algorithms of risk assessment.
Limitations Patients in this study came mostly from Athens representing an urban population. Other regions of the country (e.g. islands, north part of Greece) are less so represented. Residents of these regions may have a different life style that may alter CV risk and the prevalence of CV RFs. Total CV risk is highly dependent on age. Younger adults are unlikely to reach high risk levels even when they have 1 major RFs. If ineffectively treated, however, this condition may lead to a partly irreversible high risk condition years later. Elderly men (e.g. > 70 years) will often reach a high total risk level whilst being at very little increased risk relative to their peers.
Limitations The age spectrum of the studied population in the Framingham study (in which FRS is based) was 30-74 years while in the SCORE project (in which HS is based) was 40-64 years. Thus, it is recommended to use these algorithms only in patients of these age spectrums. Extreme values (<1% or >30% for FRS and <1% or >15% for HS) of CV risk should be excluded. FRS and HS are based on a population of US and Europe respectively. Thus, it could be disputable if they are suitable for use in other nations like Greek.
Limitations Models for CV risk assessment do not consider the duration of exposure to a RF and their quantification is usually based on some RFs only, while paying limited attention to other variables linked to cardiovascular outcome (e.g. physical activity, stress, abdominal obesity, LVH, TG, family history). Other potential factors, including duration of hypertension, duration of antihypertensive Rx use, prior antihypertensive Rx failure, seasonal effects on BP and the fact that our patient sample is a healthcare-seeking population were not taken into account for the analysis in this study.