542
Letters to the Editor
[6] Cortigiani L, Bigi R, Bovenzi F, et al. Prognostic implication of appropriateness criteria for pharmacologic stress echocardiography performed in an outpatient clinic. Circ Cardiovasc Imaging 2012;5:298–305.
[7] Mansour IN, Lang RM, Aburuwaida WM, Bhave NM, Ward RP. Evaluation of the clinical application of the ACCF/ASE appropriateness criteria for stress echocardiography. J Am Soc Echocardiogr 2010;23(11):1199–204.
http://dx.doi.org/10.1016/j.ijcard.2014.03.084 0167-5273/© 2014 Elsevier Ireland Ltd. All rights reserved.
Cystatin-C serum levels and vascular function in heart failure Dimitris Tousoulis a,⁎,1, Stavroula Michalea a,1, Gerasimos Siasos a,b,1, Evangelos Oikonomou a, Dimitris Athanasiou a, Panagiotis Tourikis a, Eleni Kokkou a, Savvas Mazaris a, Theodosia Konsola a, Nikolaos Papageorgiou a, Christodoulos Stefanadis a a b
1st Department of Cardiology, University of Athens Medical School, “Hippokration” Hospital, Athens, Greece Department of Biological Chemistry, University of Athens Medical School, Athens, Greece
a r t i c l e
i n f o
Article history: Received 24 January 2014 Accepted 12 March 2014 Available online 20 March 2014 Keywords: Cystatin-C Vascular function Heart failure
Heart failure (HF) is defined as the inability of the heart to meet the metabolic needs of the tissues. It is a complex clinical syndrome with high morbidity and mortality, and with an increasing incidence worldwide. This disorder of cardiac function is accompanied by hemodynamic disorders, endothelial dysfunction [1], atherosclerosis, inflammation and activation of neurohormone and the sympathetic nervous system, subsequently accelerating the disease progression. The prolonged activation of these mechanisms leads to further deterioration of cardiac function and dysfunction of other organs including the progressive stiffening of large arteries [2] and the renal impairment [3] which subsequently participate in the evolution of the syndrome of HF [3]. Recently, new biomarkers might have an additional contribution to reveal an early decline in renal function and to improve the prognostic assessment in patients with HF. In this study we aimed to examine the association between cystatin-C and indices of vascular function in patients with chronic heart failure (CHF). The study population consisted of 79 consecutive subjects with stable CHF of ischemic etiology, recruited from the outpatient clinic of Hippokration Hospital in Athens and 79 healthy subjects adjusted for age and sex. All patients had clinical signs of CHF and left ventricular ejection fraction (EF) ≤ 40% determined by echocardiography. Coronary artery disease was determined based on coronary angiography examination with at least one vessel disease with N75% narrowing of the luminal diameter or based on the history of previous myocardial infarction. All subjects were clinically stable – New York Heart Association functional class (NYHA) II–III – for at least 3 months before enrollment. Participants were under optimal medical treatment with diuretics, angiotensin converting enzyme inhibitors or angiotensin receptor inhibitors, aldosterone receptor inhibitors, and beta blockers for at least 3 months prior to study begin. ⁎ Corresponding author at: University of Athens Medical School, Vas. Sophias 114, Athens, Greece. E-mail address: [email protected] (D. Tousoulis). 1 The first two authors (D.T., S.M.) equally contributed in this study.
From the analysis we excluded individuals aged N80 years old, with evidence of acute coronary syndromes during the last 6 months, malignancy, rheumatoid arthritis, infections, pulmonary disease, thyroid disease, abnormal liver function tests (bilirubin, aspartate aminotransferase, or alanine aminotransferase N2 times the upper limit of normal), and severe hyperlipidemia (cholesterol N300 mg/dl or triglycerides N600 mg/dl). The participants refrained from caffeine, alcohol, smoking and any food for 12 h before each study. Patients' baseline characteristics are presented in Table 1. Augmentation index (AIx) of the central (aortic) pressure waveform and aortic pressures was calculated, as a composite index of wave reflections and arterial stiffness, using a validated, commercially available system (SphygmoCor®, AtCor Medical, Sydney, Australia), which employs the principle of applanation tonometry as previously described [4]. Because augmentation index is influenced by changes in heart rate, it was corrected accordingly (corrected for a steady heart rate of 75 beats/min-AI75). A fasting venous blood sample was taken at each visit by venipuncture between 8.00 and 10.00 a.m. Venous blood samples were centrifuged at 3000 rpm and serum/plasma was collected and stored at −80 °C until assayed. Serum levels of cystatin-C were measured by commercially available ELISA kits. Creatinine clearance was estimated using the Cockcroft–Gault formula (eCcl). All variables were tested for normal distribution of the data using the P-P plots. The values of Urea, cystatin-C, were skewed and they were log transformed to improve normality. Normally distributed data were
Table 1 Baseline characteristics of heart failure patients. Subjects (n) Age (years) Gender (male) (%) Body mass index (kg/m2) Ejection fraction (%) Pulse wave velocity (m/s) AI75 Serum urea (mg/dl) Serum creatinine (mg/dl) NGAL (ng/ml) Cystatin-C (ng/ml) BNP (pg/ml) TNFα (ng/ml) MMP-9 (ng/ml) Creatinine clearance (ml/min)
79 65 ± 13 87 27.95 ± 4.61 30 (25–35) 9.95 ± 2.80 23.35 ± 9.54 46 (33–63) 1.0 (0.9-1.35) 150.2 (106.6–201.8) 2181 (1679–3383) 172 (84–365) 1.30 (1.00–1.77) 897 ± 386 83 ± 38
AI75: Augmentation index corrected for a steady heart rate of 75 beats/min; NGAL: neutrophil gelatinase-associated lipocalin; BNP: b type natriuretic peptide; TNFα: Tumor necrosis factor alpha; MMP-9: Matrix metalloproteinase 9. Categorical variables are presented as valid percentages. Continuous variables with normal distribution are presented as means ± standard deviation, otherwise as median with first and third quartile.
Letters to the Editor
543
Fig. 1. Panel A: Box-plots showing the difference in AI75, between HF and control subjects. AI75: augmentation index corrected for a steady heart rate of 75 beats/min. Panel B: Scatter dot of logCystatin-C levels against augmentation index adjusted for a steady heart rate of 75 beats per minute.
expressed as means ± s.d., not normally distributed data as median with first and third quartiles and categorical variables were presented as frequencies. Student's t-test was used to test for differences between different categories of the same normally distributed continuous values. Correlation between normally distributed quantitative variables was tested with Pearson's r coefficient. All reported p-values were based on two-sided tests. Exact values of p b 0.05 were considered statistically significant. Data analysis was performed with SPSS software, version 18.0 (SPSS Inc., Chicago, IL). All subjects were informed about the aims of the study and gave written informed consent. The study was approved by the local Ethics Committee of our institution and was carried out in accordance with the Declaration of Helsinki. There was no significant difference between HF patients and control subjects in age (65 ± 13 years vs. 64 ± 9 years, p = 0.68), male gender (87% vs. 81%, p = 0.26), and body mass index (27.95 ± 4.61 kg/m2 vs. 27.10 ± 3.45 kg/m2, p = 0.26). Patients with HF, compared with control subjects, had significant higher AI75 (23.56 ± 9.54% vs. 20.38 ± 6.89%, p = 0.04) (Fig. 1, panel A). Patients with HF, compared to control subjects, had significantly increased levels of logCystatin-C (3.38 ± 0.21 ng/ml vs. 3.27 ± 0.25 ng/ml, p = 0.005). Interestingly, in HF patients AI75 was correlated with logCystatin-C levels (r = 0.26, p = 0.03) (Fig. 1, panel B). Levels of logCyctatin-C were inversely associated with creatinine clearance (r = −0.21, p = 0.04). The present study demonstrated that HF patients had significantly impaired vascular function. Moreover, patients with HF, compared to control subjects, had significantly increased levels of logCystatin-C. Interestingly, in HF patients AI75 was correlated with cystatin-C levels. These findings suggest a possible common pathophysiologic link of arterial stiffness and novel biomarkers of renal function. Cystatin-C predicts independently adverse events in chronic HF and also is an independent risk factor in the prognosis of patients with HF [5]. Previous studies demonstrated that cystatin-C has a significant prognostic value in patients with HF and ejection fraction (EF) N 40% [6]. Moreover, another study showed the prognostic value of cystatin-C in stable HF patients who had lower EF b35% [6]. Arterial stiffness predicts independently all-cause and cardiovascular mortality in patients with cardiovascular risk. Augmentation index (AIx) is a practical non-invasive indicator for early detection of arterial stiffness. Evidence suggests that vascular function significantly involved in the development of the syndrome of HF [7]. Arterial stiffness is known to be increased in patients with kidney failure, an association that has been partially attributed to an increase in the calcium content of the arterial
wall [8]. Furthermore, it is now believed that increased arterial stiffness is an important risk factor for long-term outcomes in patients with kidney failure [9]. There are several potential mechanisms to explain the link between kidney function and arterial stiffness. Kidney disease may directly promote arterial stiffness through its effect on hypertension and salt retention. Salt retention, in addition to affecting volume status and hypertension, may have direct effects on the vasculature [10]. It has also been suggested that sodium may modify vascular tone by affecting the sympathetic nervous system [11]. Moreover, kidney disease may cause an increase in other risk factors for arterial stiffness, such as anemia, vascular calcification or inflammation [9]. Finally, it is possible that increased pulse pressure and arterial stiffness lead to kidney damage, creating a cycle whereby each promotes the other. Novel biomarkers of renal function are associated with arterial stiffness in patients with HF. These findings highlight a possible common pathogenetic mechanism of vascular, cardiac, renal dysfunction in HF. We are particularly grateful to Professor Gerasimos Filippatos MD, PhD, FESC, FACC, FCCP, for his valuable contribution in the manuscript preparation. References [1] Chong AY, Freestone B, Patel J, et al. Endothelial activation, dysfunction, and damage in congestive heart failure and the relation to brain natriuretic peptide and outcomes. Am J Cardiol 2006;97:671–5. [2] Arnold JM, Marchiori GE, Imrie JR, Burton GL, Pflugfelder PW, Kostuk WJ. Large artery function in patients with chronic heart failure. Studies of brachial artery diameter and hemodynamics. Circulation 1991;84:2418–25. [3] Metra M, Cotter G, Gheorghiade M, Dei Cas L, Voors AA. The role of the kidney in heart failure. Eur Heart J 2012;33:2135–42. [4] Siasos G, Tousoulis D, Oikonomou E, et al. Effects of omega-3 fatty acids on endothelial function, arterial wall properties, inflammatory and fibrinolytic status in smokers: a cross over study. Int J Cardiol 2013;166:340–6. [5] Gao C, Zhong L, Gao Y, Li X, Zhang M, Wei S. Cystatin C levels are associated with the prognosis of systolic heart failure patients. Arch Cardiovasc Dis 2011;104:565–71. [6] Shlipak MG, Katz R, Sarnak MJ, et al. Cystatin C and prognosis for cardiovascular and kidney outcomes in elderly persons without chronic kidney disease. Ann Intern Med 2006;145:237–46. [7] Domanski MJ, Mitchell GF, Norman JE, Exner DV, Pitt B, Pfeffer MA. Independent prognostic information provided by sphygmomanometrically determined pulse pressure and mean arterial pressure in patients with left ventricular dysfunction. J Am Coll Cardiol 1999;33:951–8. [8] LeBoeuf A, Mac-Way F, Utescu MS, et al. Impact of dialysate calcium concentration on the progression of aortic stiffness in patients on haemodialysis. Nephrol Dial Transplant 2011;26:3695–701. [9] Szeto CC, Kwan BC, Chow KM, Leung CB, Law MC, Li PK. Prognostic value of arterial pulse wave velocity in peritoneal dialysis patients. Am J Nephrol 2012;35:127–33.
544
Letters to the Editor
[10] Safar ME, Thuilliez C, Richard V, Benetos A. Pressure-independent contribution of sodium to large artery structure and function in hypertension. Cardiovasc Res 2000;46:269–76.
[11] Brooks VL, Scrogin KE, McKeogh DF. The interaction of angiotensin II and osmolality in the generation of sympathetic tone during changes in dietary salt intake. An hypothesis. Ann N Y Acad Sci 2001;940:380–94.
http://dx.doi.org/10.1016/j.ijcard.2014.03.083 0167-5273/© 2014 Elsevier Ireland Ltd. All rights reserved.
Relation of socioeconomic status to hypertension occurrence Zhida Wang a,b,1, Xiaofei Yue a,1, Huili Wang a, Cuiping Bao c, Weili Xu a,d, Liming Chen b, Xiuying Qi a,⁎ a
Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China 2011 Collaborative Innovation Center of Tianjin for Medical Epigenetics, the Key Laboratory of Hormones and Development (Ministry of Health), Metabolic Diseases Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China c Haihe Hospital, Tianjin, China d Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institute and Stockholm University, Stockholm, Sweden b
a r t i c l e
i n f o
Article history: Received 24 January 2014 Accepted 12 March 2014 Available online 20 March 2014 Keywords: Socioeconomic status Prevalence Hypertension
In recent years, along with economic development, nutritional improvements and advances in medical technology, the prevalence of chronic noncommunicable diseases including hypertension, which is the major factor of chronic diseases, continues to increase, especially in developing countries [1]. Extensive research has shown that socioeconomic status (SES) was associated with health outcomes [2]. However, studies on the relationship between SES and hypertension have been sparse, and results are inconclusive and conflicting. Further investigations with large sample are needed. The present study aimed to examine the relationship between SES and hypertension, using data from a large population-based cross-sectional study in Tianjin, China, in July, 2005, which has been described in detail elsewhere [3,4]. After exclusion of 496 subjects aged 15–19 years, 252 students due to no stable income and occupation and 324 participants due to no information of blood pressure status, 7037 participants aged 20 to 79 years were left for the current analysis. Informed consent was obtained from all participants. The ethics committee at the Tianjin Medical University approved the study. Data on age, gender, marital status, SES (including average monthly income, education, and occupation), lifestyle and health status were collected from participants through the interview following a structured questionnaire. Average monthly income was categorized as b1000 Yuan ($121.70 according to the Yuan-Dollar rate in 2005), 1000 to 1999 Yuan ($121.70 to $243.20), and ≥2000 Yuan ($243.30). Education level was categorized as ≤6 years (illiterate and primary school), 7–9 years (junior high school), and N9 years (senior high school and higher). Occupation was classified into four categories, i.e. non-manual work, manual work, retirement and unemployment. In addition, height, weight, blood pressure and blood glucose were measured by trained examiners. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. Hypertension was defined as systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg, having a history of hypertension, or the use of anti-hypertensive ⁎ Corresponding author. Tel./fax: + 86 22 83336727. E-mail address: [email protected] (X. Qi). 1 These two authors contributed equally to this study.
medication. Type 2 diabetes mellitus was assessed as having previous diagnosed diabetes, or fasting plasma glucose ≥7.0 mmol/L or postprandial 2-h plasma glucose ≥11.1 mmol/L according to the WHO criteria (1999). The characteristics of participants between two groups were compared using Chi-square tests for categorical variables and independent-samples t tests for continuous variables. Binary logistic regression analysis was performed to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of hypertension in relation to SES adjusting for potential confounders. All statistical analyses were performed using SPSS 17.0 (SPSS Inc., Chicago, IL, USA). Among the 7037 participants, 2415 (34.3%) participants had hypertension. Compared to those without hypertension, patients with hypertension were significantly older (52.53 ± 12.57 years vs. 46.08 ± 13.80 years, P b 0.001) and more likely to be married currently (91.4% vs. 88.4%, P b 0.001), have higher BMI (25.09 ± 3.54 kg/m2 vs. 23.87 ± 3.26 kg/m2, P b 0.001) and fasting plasma glucose (5.87 ±1.84 mmol/L vs. 5.25 ± 1.30 mmol/L, P b 0.001), more smokers and type 2 diabetes. Furthermore, there was a significant difference in education, monthly Table 1 Characteristics of the study participants by hypertension. Characteristics Age (years) Male sex Married currentlya Education (years)a ≤6 7–9 N9 Monthly income ()a b1000 1000– 2000– Occupationa Manual work Non-manual work Unemployment Retirement Cigarette smokinga Alcohol drinkinga Type 2 diabetes mellitus Hyperlipidemiaa Body mass index (kg/m2) Fasting plasma glucose (mmol/L) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg)
Non-hypertension (n = 4622)
Hypertension (n = 2415)
46.08 (13.80) 2223 (48.1) 4069 (88.4)
52.53 (12.57) 1184 (49.0) 2197 (91.4)
1225 (26.5) 1736 (37.6) 1656 (35.9)
1046 (43.4) 799 (33.2) 564 (23.4)
1117 (24.3) 1984 (43.1) 1499 (32.6)
872 (36.4) 982 (41.0) 541 (22.6)
P value b 0.001 0.458 b 0.001 b 0.001
b 0.001
b 0.001 1621 (35.2) 1331 (28.9) 827 (17.9) 830 (18.0) 2144 (46.4) 1293 (28.6) 294 (6.4) 2172 (50.6) 23.87 (3.26) 5.25 (1.30) 115.65 (10.92) 75.79 (6.99)
722 (30.0) 426 (17.7) 528 (22.0) 727 (30.3) 1226 (50.8) 703 (30.1) 404 (16.7) 1122 (49.0) 25.09 (3.54) 5.87 (1.84) 141.49 (18.49) 88.93 (10.89)
0.001 0.208 b 0.001 0.205 b 0.001 b 0.001 b 0.001 b 0.001
Data are mean/number (SD or %). a Numbers of subjects with missing values were 27 for marital status, 11 for education, 42 for monthly income, 25 for occupation, 6 for cigarette smoking, 180 for alcohol drinking, and 452 for hyperlipidemia.
Letters to the Editor
[6] Cortigiani L, Bigi R, Bovenzi F, et al. Prognostic implication of appropriateness criteria for pharmacologic stress echocardiography performed in an outpatient clinic. Circ Cardiovasc Imaging 2012;5:298–305.
[7] Mansour IN, Lang RM, Aburuwaida WM, Bhave NM, Ward RP. Evaluation of the clinical application of the ACCF/ASE appropriateness criteria for stress echocardiography. J Am Soc Echocardiogr 2010;23(11):1199–204.
http://dx.doi.org/10.1016/j.ijcard.2014.03.084 0167-5273/© 2014 Elsevier Ireland Ltd. All rights reserved.
Cystatin-C serum levels and vascular function in heart failure Dimitris Tousoulis a,⁎,1, Stavroula Michalea a,1, Gerasimos Siasos a,b,1, Evangelos Oikonomou a, Dimitris Athanasiou a, Panagiotis Tourikis a, Eleni Kokkou a, Savvas Mazaris a, Theodosia Konsola a, Nikolaos Papageorgiou a, Christodoulos Stefanadis a a b
1st Department of Cardiology, University of Athens Medical School, “Hippokration” Hospital, Athens, Greece Department of Biological Chemistry, University of Athens Medical School, Athens, Greece
a r t i c l e
i n f o
Article history: Received 24 January 2014 Accepted 12 March 2014 Available online 20 March 2014 Keywords: Cystatin-C Vascular function Heart failure
Heart failure (HF) is defined as the inability of the heart to meet the metabolic needs of the tissues. It is a complex clinical syndrome with high morbidity and mortality, and with an increasing incidence worldwide. This disorder of cardiac function is accompanied by hemodynamic disorders, endothelial dysfunction [1], atherosclerosis, inflammation and activation of neurohormone and the sympathetic nervous system, subsequently accelerating the disease progression. The prolonged activation of these mechanisms leads to further deterioration of cardiac function and dysfunction of other organs including the progressive stiffening of large arteries [2] and the renal impairment [3] which subsequently participate in the evolution of the syndrome of HF [3]. Recently, new biomarkers might have an additional contribution to reveal an early decline in renal function and to improve the prognostic assessment in patients with HF. In this study we aimed to examine the association between cystatin-C and indices of vascular function in patients with chronic heart failure (CHF). The study population consisted of 79 consecutive subjects with stable CHF of ischemic etiology, recruited from the outpatient clinic of Hippokration Hospital in Athens and 79 healthy subjects adjusted for age and sex. All patients had clinical signs of CHF and left ventricular ejection fraction (EF) ≤ 40% determined by echocardiography. Coronary artery disease was determined based on coronary angiography examination with at least one vessel disease with N75% narrowing of the luminal diameter or based on the history of previous myocardial infarction. All subjects were clinically stable – New York Heart Association functional class (NYHA) II–III – for at least 3 months before enrollment. Participants were under optimal medical treatment with diuretics, angiotensin converting enzyme inhibitors or angiotensin receptor inhibitors, aldosterone receptor inhibitors, and beta blockers for at least 3 months prior to study begin. ⁎ Corresponding author at: University of Athens Medical School, Vas. Sophias 114, Athens, Greece. E-mail address: [email protected] (D. Tousoulis). 1 The first two authors (D.T., S.M.) equally contributed in this study.
From the analysis we excluded individuals aged N80 years old, with evidence of acute coronary syndromes during the last 6 months, malignancy, rheumatoid arthritis, infections, pulmonary disease, thyroid disease, abnormal liver function tests (bilirubin, aspartate aminotransferase, or alanine aminotransferase N2 times the upper limit of normal), and severe hyperlipidemia (cholesterol N300 mg/dl or triglycerides N600 mg/dl). The participants refrained from caffeine, alcohol, smoking and any food for 12 h before each study. Patients' baseline characteristics are presented in Table 1. Augmentation index (AIx) of the central (aortic) pressure waveform and aortic pressures was calculated, as a composite index of wave reflections and arterial stiffness, using a validated, commercially available system (SphygmoCor®, AtCor Medical, Sydney, Australia), which employs the principle of applanation tonometry as previously described [4]. Because augmentation index is influenced by changes in heart rate, it was corrected accordingly (corrected for a steady heart rate of 75 beats/min-AI75). A fasting venous blood sample was taken at each visit by venipuncture between 8.00 and 10.00 a.m. Venous blood samples were centrifuged at 3000 rpm and serum/plasma was collected and stored at −80 °C until assayed. Serum levels of cystatin-C were measured by commercially available ELISA kits. Creatinine clearance was estimated using the Cockcroft–Gault formula (eCcl). All variables were tested for normal distribution of the data using the P-P plots. The values of Urea, cystatin-C, were skewed and they were log transformed to improve normality. Normally distributed data were
Table 1 Baseline characteristics of heart failure patients. Subjects (n) Age (years) Gender (male) (%) Body mass index (kg/m2) Ejection fraction (%) Pulse wave velocity (m/s) AI75 Serum urea (mg/dl) Serum creatinine (mg/dl) NGAL (ng/ml) Cystatin-C (ng/ml) BNP (pg/ml) TNFα (ng/ml) MMP-9 (ng/ml) Creatinine clearance (ml/min)
79 65 ± 13 87 27.95 ± 4.61 30 (25–35) 9.95 ± 2.80 23.35 ± 9.54 46 (33–63) 1.0 (0.9-1.35) 150.2 (106.6–201.8) 2181 (1679–3383) 172 (84–365) 1.30 (1.00–1.77) 897 ± 386 83 ± 38
AI75: Augmentation index corrected for a steady heart rate of 75 beats/min; NGAL: neutrophil gelatinase-associated lipocalin; BNP: b type natriuretic peptide; TNFα: Tumor necrosis factor alpha; MMP-9: Matrix metalloproteinase 9. Categorical variables are presented as valid percentages. Continuous variables with normal distribution are presented as means ± standard deviation, otherwise as median with first and third quartile.
Letters to the Editor
543
Fig. 1. Panel A: Box-plots showing the difference in AI75, between HF and control subjects. AI75: augmentation index corrected for a steady heart rate of 75 beats/min. Panel B: Scatter dot of logCystatin-C levels against augmentation index adjusted for a steady heart rate of 75 beats per minute.
expressed as means ± s.d., not normally distributed data as median with first and third quartiles and categorical variables were presented as frequencies. Student's t-test was used to test for differences between different categories of the same normally distributed continuous values. Correlation between normally distributed quantitative variables was tested with Pearson's r coefficient. All reported p-values were based on two-sided tests. Exact values of p b 0.05 were considered statistically significant. Data analysis was performed with SPSS software, version 18.0 (SPSS Inc., Chicago, IL). All subjects were informed about the aims of the study and gave written informed consent. The study was approved by the local Ethics Committee of our institution and was carried out in accordance with the Declaration of Helsinki. There was no significant difference between HF patients and control subjects in age (65 ± 13 years vs. 64 ± 9 years, p = 0.68), male gender (87% vs. 81%, p = 0.26), and body mass index (27.95 ± 4.61 kg/m2 vs. 27.10 ± 3.45 kg/m2, p = 0.26). Patients with HF, compared with control subjects, had significant higher AI75 (23.56 ± 9.54% vs. 20.38 ± 6.89%, p = 0.04) (Fig. 1, panel A). Patients with HF, compared to control subjects, had significantly increased levels of logCystatin-C (3.38 ± 0.21 ng/ml vs. 3.27 ± 0.25 ng/ml, p = 0.005). Interestingly, in HF patients AI75 was correlated with logCystatin-C levels (r = 0.26, p = 0.03) (Fig. 1, panel B). Levels of logCyctatin-C were inversely associated with creatinine clearance (r = −0.21, p = 0.04). The present study demonstrated that HF patients had significantly impaired vascular function. Moreover, patients with HF, compared to control subjects, had significantly increased levels of logCystatin-C. Interestingly, in HF patients AI75 was correlated with cystatin-C levels. These findings suggest a possible common pathophysiologic link of arterial stiffness and novel biomarkers of renal function. Cystatin-C predicts independently adverse events in chronic HF and also is an independent risk factor in the prognosis of patients with HF [5]. Previous studies demonstrated that cystatin-C has a significant prognostic value in patients with HF and ejection fraction (EF) N 40% [6]. Moreover, another study showed the prognostic value of cystatin-C in stable HF patients who had lower EF b35% [6]. Arterial stiffness predicts independently all-cause and cardiovascular mortality in patients with cardiovascular risk. Augmentation index (AIx) is a practical non-invasive indicator for early detection of arterial stiffness. Evidence suggests that vascular function significantly involved in the development of the syndrome of HF [7]. Arterial stiffness is known to be increased in patients with kidney failure, an association that has been partially attributed to an increase in the calcium content of the arterial
wall [8]. Furthermore, it is now believed that increased arterial stiffness is an important risk factor for long-term outcomes in patients with kidney failure [9]. There are several potential mechanisms to explain the link between kidney function and arterial stiffness. Kidney disease may directly promote arterial stiffness through its effect on hypertension and salt retention. Salt retention, in addition to affecting volume status and hypertension, may have direct effects on the vasculature [10]. It has also been suggested that sodium may modify vascular tone by affecting the sympathetic nervous system [11]. Moreover, kidney disease may cause an increase in other risk factors for arterial stiffness, such as anemia, vascular calcification or inflammation [9]. Finally, it is possible that increased pulse pressure and arterial stiffness lead to kidney damage, creating a cycle whereby each promotes the other. Novel biomarkers of renal function are associated with arterial stiffness in patients with HF. These findings highlight a possible common pathogenetic mechanism of vascular, cardiac, renal dysfunction in HF. We are particularly grateful to Professor Gerasimos Filippatos MD, PhD, FESC, FACC, FCCP, for his valuable contribution in the manuscript preparation. References [1] Chong AY, Freestone B, Patel J, et al. Endothelial activation, dysfunction, and damage in congestive heart failure and the relation to brain natriuretic peptide and outcomes. Am J Cardiol 2006;97:671–5. [2] Arnold JM, Marchiori GE, Imrie JR, Burton GL, Pflugfelder PW, Kostuk WJ. Large artery function in patients with chronic heart failure. Studies of brachial artery diameter and hemodynamics. Circulation 1991;84:2418–25. [3] Metra M, Cotter G, Gheorghiade M, Dei Cas L, Voors AA. The role of the kidney in heart failure. Eur Heart J 2012;33:2135–42. [4] Siasos G, Tousoulis D, Oikonomou E, et al. Effects of omega-3 fatty acids on endothelial function, arterial wall properties, inflammatory and fibrinolytic status in smokers: a cross over study. Int J Cardiol 2013;166:340–6. [5] Gao C, Zhong L, Gao Y, Li X, Zhang M, Wei S. Cystatin C levels are associated with the prognosis of systolic heart failure patients. Arch Cardiovasc Dis 2011;104:565–71. [6] Shlipak MG, Katz R, Sarnak MJ, et al. Cystatin C and prognosis for cardiovascular and kidney outcomes in elderly persons without chronic kidney disease. Ann Intern Med 2006;145:237–46. [7] Domanski MJ, Mitchell GF, Norman JE, Exner DV, Pitt B, Pfeffer MA. Independent prognostic information provided by sphygmomanometrically determined pulse pressure and mean arterial pressure in patients with left ventricular dysfunction. J Am Coll Cardiol 1999;33:951–8. [8] LeBoeuf A, Mac-Way F, Utescu MS, et al. Impact of dialysate calcium concentration on the progression of aortic stiffness in patients on haemodialysis. Nephrol Dial Transplant 2011;26:3695–701. [9] Szeto CC, Kwan BC, Chow KM, Leung CB, Law MC, Li PK. Prognostic value of arterial pulse wave velocity in peritoneal dialysis patients. Am J Nephrol 2012;35:127–33.
544
Letters to the Editor
[10] Safar ME, Thuilliez C, Richard V, Benetos A. Pressure-independent contribution of sodium to large artery structure and function in hypertension. Cardiovasc Res 2000;46:269–76.
[11] Brooks VL, Scrogin KE, McKeogh DF. The interaction of angiotensin II and osmolality in the generation of sympathetic tone during changes in dietary salt intake. An hypothesis. Ann N Y Acad Sci 2001;940:380–94.
http://dx.doi.org/10.1016/j.ijcard.2014.03.083 0167-5273/© 2014 Elsevier Ireland Ltd. All rights reserved.
Relation of socioeconomic status to hypertension occurrence Zhida Wang a,b,1, Xiaofei Yue a,1, Huili Wang a, Cuiping Bao c, Weili Xu a,d, Liming Chen b, Xiuying Qi a,⁎ a
Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China 2011 Collaborative Innovation Center of Tianjin for Medical Epigenetics, the Key Laboratory of Hormones and Development (Ministry of Health), Metabolic Diseases Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China c Haihe Hospital, Tianjin, China d Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institute and Stockholm University, Stockholm, Sweden b
a r t i c l e
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Article history: Received 24 January 2014 Accepted 12 March 2014 Available online 20 March 2014 Keywords: Socioeconomic status Prevalence Hypertension
In recent years, along with economic development, nutritional improvements and advances in medical technology, the prevalence of chronic noncommunicable diseases including hypertension, which is the major factor of chronic diseases, continues to increase, especially in developing countries [1]. Extensive research has shown that socioeconomic status (SES) was associated with health outcomes [2]. However, studies on the relationship between SES and hypertension have been sparse, and results are inconclusive and conflicting. Further investigations with large sample are needed. The present study aimed to examine the relationship between SES and hypertension, using data from a large population-based cross-sectional study in Tianjin, China, in July, 2005, which has been described in detail elsewhere [3,4]. After exclusion of 496 subjects aged 15–19 years, 252 students due to no stable income and occupation and 324 participants due to no information of blood pressure status, 7037 participants aged 20 to 79 years were left for the current analysis. Informed consent was obtained from all participants. The ethics committee at the Tianjin Medical University approved the study. Data on age, gender, marital status, SES (including average monthly income, education, and occupation), lifestyle and health status were collected from participants through the interview following a structured questionnaire. Average monthly income was categorized as b1000 Yuan ($121.70 according to the Yuan-Dollar rate in 2005), 1000 to 1999 Yuan ($121.70 to $243.20), and ≥2000 Yuan ($243.30). Education level was categorized as ≤6 years (illiterate and primary school), 7–9 years (junior high school), and N9 years (senior high school and higher). Occupation was classified into four categories, i.e. non-manual work, manual work, retirement and unemployment. In addition, height, weight, blood pressure and blood glucose were measured by trained examiners. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. Hypertension was defined as systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg, having a history of hypertension, or the use of anti-hypertensive ⁎ Corresponding author. Tel./fax: + 86 22 83336727. E-mail address: [email protected] (X. Qi). 1 These two authors contributed equally to this study.
medication. Type 2 diabetes mellitus was assessed as having previous diagnosed diabetes, or fasting plasma glucose ≥7.0 mmol/L or postprandial 2-h plasma glucose ≥11.1 mmol/L according to the WHO criteria (1999). The characteristics of participants between two groups were compared using Chi-square tests for categorical variables and independent-samples t tests for continuous variables. Binary logistic regression analysis was performed to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of hypertension in relation to SES adjusting for potential confounders. All statistical analyses were performed using SPSS 17.0 (SPSS Inc., Chicago, IL, USA). Among the 7037 participants, 2415 (34.3%) participants had hypertension. Compared to those without hypertension, patients with hypertension were significantly older (52.53 ± 12.57 years vs. 46.08 ± 13.80 years, P b 0.001) and more likely to be married currently (91.4% vs. 88.4%, P b 0.001), have higher BMI (25.09 ± 3.54 kg/m2 vs. 23.87 ± 3.26 kg/m2, P b 0.001) and fasting plasma glucose (5.87 ±1.84 mmol/L vs. 5.25 ± 1.30 mmol/L, P b 0.001), more smokers and type 2 diabetes. Furthermore, there was a significant difference in education, monthly Table 1 Characteristics of the study participants by hypertension. Characteristics Age (years) Male sex Married currentlya Education (years)a ≤6 7–9 N9 Monthly income ()a b1000 1000– 2000– Occupationa Manual work Non-manual work Unemployment Retirement Cigarette smokinga Alcohol drinkinga Type 2 diabetes mellitus Hyperlipidemiaa Body mass index (kg/m2) Fasting plasma glucose (mmol/L) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg)
Non-hypertension (n = 4622)
Hypertension (n = 2415)
46.08 (13.80) 2223 (48.1) 4069 (88.4)
52.53 (12.57) 1184 (49.0) 2197 (91.4)
1225 (26.5) 1736 (37.6) 1656 (35.9)
1046 (43.4) 799 (33.2) 564 (23.4)
1117 (24.3) 1984 (43.1) 1499 (32.6)
872 (36.4) 982 (41.0) 541 (22.6)
P value b 0.001 0.458 b 0.001 b 0.001
b 0.001
b 0.001 1621 (35.2) 1331 (28.9) 827 (17.9) 830 (18.0) 2144 (46.4) 1293 (28.6) 294 (6.4) 2172 (50.6) 23.87 (3.26) 5.25 (1.30) 115.65 (10.92) 75.79 (6.99)
722 (30.0) 426 (17.7) 528 (22.0) 727 (30.3) 1226 (50.8) 703 (30.1) 404 (16.7) 1122 (49.0) 25.09 (3.54) 5.87 (1.84) 141.49 (18.49) 88.93 (10.89)
0.001 0.208 b 0.001 0.205 b 0.001 b 0.001 b 0.001 b 0.001
Data are mean/number (SD or %). a Numbers of subjects with missing values were 27 for marital status, 11 for education, 42 for monthly income, 25 for occupation, 6 for cigarette smoking, 180 for alcohol drinking, and 452 for hyperlipidemia.
