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 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 31  |  Issue : 4  |  Page : 696-702

Serum copeptin as a diagnostic and prognostic biomarker of coronary artery disease among patients with type 2 diabetes mellitus


1 Department of Internal Medicine, Faculty of Medicine, Zagazig University, Zagazig, Egypt
2 Department of Clinical Pathology, Faculty of Medicine, Zagazig University, Zagazig, Egypt
3 Department of Physiology, Faculty of Medicine, Zagazig University, Zagazig, Egypt
4 Department of Cardiology, Faculty of Medicine, Zagazig University, Zagazig, Egypt

Date of Submission25-Jul-2019
Date of Acceptance01-Aug-2019
Date of Web Publication18-Aug-2020

Correspondence Address:
MD Nearmeen M Rashad
Internal Medicine Department, Faculty of Medicine, Zagazig University, Zagazig
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ejim.ejim_102_19

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  Abstract 


Background Diabetes is one of the major risk factors for coronary artery disease (CAD); hormones implicated in cardiac diseases may play a role in diabetes development. Increased activities of the arginine-vasopressin (AVP) system were shown to be associated with type 2 diabetes mellitus (T2DM). The aim of this study was to estimate the values of serum copeptin as a predictive biomarker of CAD and to assess the correlation between copeptin and cardiometabolic risk factors in patients with T2DM.
Patients and methods The case–control study included 110 patients with T2DM and 80 age-matched and sex-matched control group. All the participants were subjected to B-mode ultrasonography of both common carotid arteries to measure carotid intima-media thickness (mm), echocardiography, and coronary arteriography. Serum copeptin levels were measured with a new sandwich immunoassay by using a human copeptin enzyme‐linked immunosorbent assay kit.
Results Patients with T2DM had significantly higher serum copeptin levels (7.64±1.98 pmol/l) compared with control groups (4.64±1.11 pmol/l). Serum copeptin levels were significantly higher in patients with CAD (8.64±2.55 pmol/l) compared with patients without CAD (6.36±0.86 pmol/l). Interestingly, copeptin was positively correlated with cardiometabolic risks. The area under the curve of serum copeptin levels in differentiating patient with T2DM from control was 0.768 (P<0.001) and differentiating patient with CAD from the nonischemic group was 0.818 (P<0.001).
Conclusion The higher serum level of copeptin in patients with T2DM especially in the patient with CAD is strongly correlated with cardiometabolic risk factors.

Keywords: arginine vasopressin, coronary artery disease, copeptin, type 2 diabetes mellitus


How to cite this article:
Rashad NM, Ezzat TM, Allam RM, Ashour WM, Ali AE, Soliman MH. Serum copeptin as a diagnostic and prognostic biomarker of coronary artery disease among patients with type 2 diabetes mellitus. Egypt J Intern Med 2019;31:696-702

How to cite this URL:
Rashad NM, Ezzat TM, Allam RM, Ashour WM, Ali AE, Soliman MH. Serum copeptin as a diagnostic and prognostic biomarker of coronary artery disease among patients with type 2 diabetes mellitus. Egypt J Intern Med [serial online] 2019 [cited 2024 Mar 28];31:696-702. Available from: http://www.esim.eg.net/text.asp?2019/31/4/696/292184




  Introduction Top


Cardiovascular disease (CVD) is the leading cause of death and disability worldwide [1],[2]. Obesity and type 2 diabetes mellitus (T2DM) are considered as one of the major risk factors for coronary heart disease development [3],[4].

Arginine-vasopressin (AVP) is a neurohormone released from the neurohypophysis for maintaining fluid homeostasis [5]. Copeptin is the metabolic product of AVP precursor, and it is more stable than AVP and has a long half-life [6]. Mounting evidence indicates that elevated copeptin was significantly associated with a higher risk of diabetes, independent of other risks.

Compelling evidence suggests that the primary prevention of CVD is dependent upon the ability to identify high-risk individuals long before the development of overt events. Biomarkers play a critical role in the definition, prognostication, and decision making regarding the management of cardiovascular events. Thus, the aim of this study was to estimate the values of serum copeptin as a predictive biomarker of coronary artery disease (CAD) and to assess the correlation between copeptin and cardiometabolic risk factors in patients with T2DM.


  Patients and methods Top


A case–control study was conducted that included 110 patients with T2DM. The diagnosis of diabetes was done according to ADA 2017. The enrolled diabetic patients were classified into two groups: 63 with CAD and 47 without CAD. Moreover, the study included 90 age-matched and sex-matched healthy individuals as a control group.

The patients with type 1 diabetes mellitus, patients with estimated glomerular filtration ratio less than 60 ml/min/1.73 m2, patients with decompensated liver disease, patients with rheumatic valvular heart diseases, patients with decompensated heart failure, patients with previous myocardial infarction or patients with recent cerebrovascular events (such as brain infarction or hemorrhage) within the prior 6 months were excluded from this study. All patients were subjected to thorough history taking and full clinical assessment including blood pressure and anthropometric variables. BMI was calculated as weight in kg/height (m)2. The patients underwent elective coronary angiography for suspected CAD in the Cardiology Department of Zagazig University Hospitals. All patients were investigated using a 12-lead standard ECG and echocardiography. Coronary arteriography was performed for all patients by the Judkins technique for assessment of the lesion’s distribution and description. CAD was considered significant if there was at least 50% diameter stenosis in at least one coronary artery. The Ethical Committee of the Faculty of Medicine, Zagazig University approved our study protocol, and all participants provided written informed consent.

We evaluated our participants in the outpatient clinic of Diabetes and Endocrinology Unit, Internal Medicine Department, Zagazig University Hospitals. All participants provided written informed consent. The study has been conducted according to the guidelines of the Ethical Committee of the Faculty of Medicine, Zagazig University.

Blood sampling and laboratory assessments

Blood samples were drawn from all patients after an overnight fast and divided into two portions: 1 ml of whole blood was collected into evacuated tubes containing EDTA, for hemoglobin A1c (HbA1c), and 1 ml of whole blood was collected into evacuated tubes containing potassium oxalate and sodium fluoride (2 : 1) for fasting plasma glucose (FPG). Sera were separated immediately from remaining part of the sample and stored at −20°C until analysis. We measured FPG using the glucose oxidase method (Spinreact, Girona, Spain). Total cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides were measured by routine enzymatic methods (Spinreact). LDL cholesterol was calculated using the Friedewald formula [7]. Fasting serum insulin (FSI) levels were estimated by an enzyme‐linked immunosorbent assay kits (Ray Bio, Norcross, Georgia, USA). Insulin resistance was assessed using the homeostasis model assessment method, homeostasis model assessments of insulin resistance, and was calculated as FSI (µU/ml)×FBG (mg/dl)/405, and В-cell function (HOMA-B) was calculated. C-peptide concentration was measured in serum by ELISA kit according to the manufacturer’s instructions (Wkea Med Supplies Corp., Jilin, China) [8].

Measurement of serum copeptin levels

The level of copeptin in samples was determined using a double-antibody sandwich ELISA kit supplied by Elabscience Co. Ltd (Donghu Hi-Tech Development Area, Wuhan, China).

Carotid ultrasonography

Ultrasonography of the carotid arteries was done in the Radiodiagnosis Department of Zagazig University Hospitals for elective patients. Carotid artery atherosclerosis was determined by two examiners for all patients across all six sites, using high-resolution B-mode ultrasound (M-Turbo; SonoSite, Washington, Bothell, USA), according to the protocol. The B-mode ultrasound examination is performed with a linear array transducer of 7.5–12 MHz on the selected patients in supine position with the head slightly extended and turned to the opposite direction of the common carotid artery (CCA) being studied. Both sides were imaged at three places, that is, at the proximal part, mid part, and the bulb. The means of the three maximum right and three maximum left far wall measurements were calculated for each CCA. On a longitudinal, two-dimensional ultrasound image of CCA, each anterior (near) and posterior (far) wall of the CCA was displayed as two bright white lines separated by a hypoechogenic space. The distance between the leading edge of the first bright line (the blood–intima interface) of the far wall and the leading edge of the second bright line (media–adventitia interface) indicates the intima-media thickness. A reading of more than 0.8 mm is considered to be abnormal and taken as the earliest marker of atherosclerosis [9].

Statistical analysis

Data were analyzed on the SPSS (version 21, SPSS Inc., Chicago, Illinois, USA). Pearson correlation was used to assess the association between serum copeptin, carotid intima-media thickness (CIMT), clinical, biochemical tests, and other studied metabolic parameters. Receiver operating characteristic analysis was performed to assess the potential accuracy of serum copeptin, for the diagnosis of T2DM.


  Results Top


Among the studied participants, in the control group, 55% were male and 45% were female, and their mean age was 49.94±5.56 years. In the diabetic group, 61% were male and 38% were female, and their mean age was 45.11±6.3 years. Control and T2DM groups were matched for age, ethnicity, and sex.

Clinical and biochemical characteristics of the studied groups

Patient with T2DM had significantly higher values of diastolic blood pressure, BMI, waist/hip ratio, postprandial plasma glucose, FPG, HbA1c, FSI, HOMAR-IR, triglycerides (TG), high-sensitivity C-reactive protein (hs-CRP), and CIMT than the control group (P<0.05). On the contrary, there was a significantly lower value of HDL in patients with T2DM compared with the control group (P<0.001; [Table 1]).
Table 1 Clinical, anthropometric, and laboratory characteristics of all studied participants

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Clinical and biochemical characteristics of patients with type 2 diabetes mellitus

Among patients with T2DM, patients with CAD had significantly higher values of systolic blood pressure, diastolic blood pressure, postprandial plasma glucose, FPG, HbA1c, FSI, HOMAR-IR, TG, hs-CRP, and CIMT than normal glucose tolerance (NGT) group (P<0.05). On the contrary, there were significant higher values of FPG, postprandial plasma glucose, FSI, HOMAR-IR, HbA1c, and hs-CRP in impaired glucose tolerance group compared with NGT group (P<0.05). On the contrary, there was a significantly lower value of HDL in the impaired glucose tolerance group compared with NGT group (P<0.001; [Table 2]).
Table 2 Laboratory and anthropometric parameters in obese patients stratified according to fasting plasma glucose

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Comparison of serum copeptin in the studied population

Patients with T2DM had significantly higher values of serum copeptin (7.64±1.98) compared with control (4.64±1.11; [Figure 1]a). Among patients with T2DM, patients with CAD had significantly higher values of serum copeptin (8.64±2.55) compared with control (6.36±0.86; [Figure 1]b).
Figure 1 (a): Serum copeptin (pmol/l) levels in the studied groups. (b) Serum copeptin (pmol/l) levels in patients with type 2 diabetes mellitus.

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The Pearson correlation between serum copeptin with other parameters is shown in [Table 3].
Table 3 Pearson correlations between copeptin (pmol/l) and other parameters of studied groups

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The accuracy of serum copeptin for discriminating patients with diabetes from the control group

Using the receiver operating characteristic curve, at the cutoff value of 5.7 and area under the curve of 0.768 [95% confidence interval (CI)=0.673–0.863], the sensitivity and the specificity of serum copeptin for discriminating patients with diabetes from the control group were 87.2 and 60.7%, respectively ([Figure 2]).
Figure 2 Receiver operating characteristic (ROC) for serum copeptin (pmol/l) in discriminating patients with type 2 diabetes mellitus from control group.

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The accuracy of serum copeptin for discriminating patients with coronary artery disease from those without coronary artery disease

At the cutoff values of 4.5 and area under the curve of 0.818 (95% CI=0.721–0.914), the sensitivity and the specificity of serum copeptin for discriminating patients with CAD from those without CAD were 90 and 63.3%, respectively ([Figure 3]).
Figure 3 Receiver operating characteristic (ROC) for serum copeptin (pmol/l) in discriminating patients with coronary artery disease (CAD) from patient without CAD.

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Logistic regression analysis evaluating the association of serum copeptin with type 2 diabetes mellitus among the studied patients

After adjusting for the traditional risk factors, logistic regression analysis test was done to evaluate the predictor of cardiovascular risk. Copeptin was a statistically significant predictor of cardiovascular risk among the patients (odds ratio=0.001, 95% CI=0.000–0.407, P<0.05; [Table 4]).
Table 4 Logistic regression analysis evaluating the association of carotid intima-media thickness (mm) and serum copeptin with type 2 diabetes mellitus among the studied patients

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Multiple stepwise linear regression analysis to test the influence of the main independent variables against copeptin (pmol/l) (dependent variable)

The stepwise linear regression analysis test revealed that CIMT and postprandial plasma glucose were independently correlated with copeptin (P<0.001; [Table 5]).
Table 5 Multiple stepwise linear regression analysis to test the influence of the main independent variables against copeptin (pmol/l) (dependent variable)

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  Discussion Top


There has been great evidence that the prevalence of T2DM is increasing since decades. Interestingly, CAD represents a major burden on public health. Although considerable research effort has been focused on CAD, the pathophysiology of the disease remains incompletely understood [10].

Regarding the importance and efficacy of prevention strategies by identifying the susceptible populations, this study was designed to investigate the association of serum copeptin with susceptibility of CAD. To address this need, we have focused on evaluating the value of serum copeptin as a predictive biomarker of CAD, and to assess the correlation between copeptin and cardiometabolic risk factors in patients with T2DM.

The results presented herein are innovative, as this study performs a robust evaluation of copeptin as a diagnostic marker of CAD. Our results confirmed that copeptin was significantly higher in patients with T2DM than the control group, in particular patients with CAD compared with those without CAD. Interestingly, copeptin was positively correlated with FPG, postprandial plasma glucose, FSI, HOMAR-IR, hs-CRP, and HbA1c.

Similar to our results, the study by Enhörning et al. [7] showed copeptin independently predicts T2DM and abdominal obesity but not the cluster of metabolic syndromes.

In agreement with our results, Schink et al. [11] observed higher levels of copeptin in the obese group compared with the lean one.

In accordance with our finding, the study by Enhörning suggested that elevated copeptin level predicts increased risk for diabetes mellitus independent of the established clinical risk factors, including fasting glucose and insulin. In addition, they observed that copeptin increased concomitantly with T2DM. However, the copeptin levels were not correlated with the parameters of insulin resistance [12].

An interesting experimental study reported that AVP infusion leads to increased blood glucose levels [13].

There is compelling evidence suggesting an important association of copeptin with impaired glucose tolerance, as in the study conducted by Aoyagi et al. [14], which found that mice lacking V1aR display impaired glucose tolerance, insulin resistance, and elevated AVP levels.

In another experimental study conducted by Fujiwara et al. [15], it was observed that mice that lack V1bR have the opposite phenotype of lower fasting plasma glucose and increased insulin sensitivity. These findings suggest a model in which impaired signaling through V1aR leads to elevated levels of AVP, which in turn stimulates V1bR and contributes to insulin resistance and the development of diabetes mellitus [16].

We in this study attempted to examine the association between serum copeptin and cardiometabolic risk factors. After adjusting for the traditional risk factors, logistic regression analysis test detected that serum copeptin level was a statistically significant predictor of cardiovascular risk among diabetic patients.

In agreement with our results, Tasevska et al. [17] observed that copeptin could predict CAD development and cardiovascular mortality in both diabetics and nondiabetics. In addition, Boeckel et al. [18] found a significant increase of copeptin in patients having acute myocardial infarction.

Even more importantly, for further evaluation, we analyzed our results using stepwise linear regression analysis and found that CIMT and postprandial plasma glucose were independently correlated with copeptin.

Our findings are in concordance with the study by Enhörning et al. [12], in which they found that FPG was the strongest risk factor for new-onset diabetes mellitus, but after adjusting for FPG and all other available diabetes risk factors, copeptin had a 2–3-fold excess risk of developing diabetes mellitus.

The interesting study by Wannamethee et al. [19] found that copeptin was independently associated with an increased risk of incident stroke and CVD mortality in men with diabetes, but not in men without diabetes.

Recent evidence indicates that copeptin was elevated in acute coronary syndrome [20],[21],[22]. Interestingly, a study conducted by Khan et al. [23] suggested that the high level of serum copeptin measured immediately after Percutaneous coronary intervention (PCI) was associated with major adverse cardiac events (MACE) in patients with AMI during long-term follow-up.

Emerging evidence demonstrated that copeptin is a marker of insulin resistance and a possible surrogate measure of cardiovascular risk. Mounting evidence indicates that the AVP system contributes to the development of insulin resistance through a variety of mechanisms including the stimulation of glucagon, Adrenocorticotropic hormone (ACTH) secretion, glycogenolysis, etc. [24].


  Conclusion Top


The high level of copeptin in obesity and T2DM is strongly correlated with CIMT and other cardiometabolic risk factors such as hypertension, dyslipidemia, insulin resistance, hyperglycemia, and obesity. Therefore, copeptin seems to be a marker of endothelial dysfunction and predictor of early atherosclerosis among patient with or without diabetes.

Author contribution

Nearmeen M. Rashad, Ayman E. Ali, and TME and MHS collected patients’ samples and clinical data. Wesam M.R. Ashour and Reem M. Allam prepared the samples for laboratory investigations. Nearmeen M. Rashad wrote the paper. Statistical analysis, interpretation of data, and preparation of the paper for submitting internationally was done by Nearmeen M. Rashad. Critical revision of the manuscript was performed by all of the authors. All authors have read and approved the final manuscript.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Clark H, Arnett DK, Blaha MJ, Cushman M et al. NCDs: a challenge to sustainable human development. Lancet. 2013; 381:510–511.  Back to cited text no. 1
    
2.
Mozaffarian D, Benjamin EJ, Go AS et al. Heart disease and stroke statistics-2015 update: a report from the American Heart Association. Circulation 2015; 131:e29–322.  Back to cited text no. 2
    
3.
Forouzanfar MH, Alexander L, Anderson HR, Bachman VF, Biryukov S, Brauer M. Global, regional, and national comparative risk assessment of 79 behavioral, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the global burden of disease study2013. Lancet 2015; 386:2287–2323.  Back to cited text no. 3
    
4.
Hozawa A, Folsom AR, Sharrett AR, Chambless LE. Absolute and attributable risks of cardiovascular disease incidence in relation to optimal and borderline risk factors: comparison of African American with white subjects − atherosclerosis risk in communities study. Arch Intern Med 2007; 167:573–579.  Back to cited text no. 4
    
5.
Barrett LK, Singer M, Clapp LH. Vasopressin: mechanisms of action on the vasculature in health and in septic shock. Crit Care Med 2007; 35:33–40.  Back to cited text no. 5
    
6.
Morgenthaler NG, Struck J, Jochberger S, Dünser MW. Copeptin: clinical use of a new biomarker. Trends Endocrinol Metab 2008; 19:43–49.  Back to cited text no. 6
    
7.
7.Enhörning S, Bankir L, Bouby N, Struck J, Hedblad B, Persson M et al. Copeptin, a marker of vasopressin, in abdominal obesity, diabetes and microalbuminuria: the prospective Malmö Diet and Cancer Study cardiovascular cohort. Int J Obes (Lond) 2013; 37:598–603.  Back to cited text no. 7
    
8.
8.Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28:412–419.  Back to cited text no. 8
    
9.
Stein JH, Korcarz CE, Hurst RT et al. Use of carotid ultrasound to identify subclinical vascular disease and evaluate cardiovascular disease risk: a consensus statement from the American Society of Echocardiography Carotid Intima-Media Thickness Task Force.Endorsed by the Society for Vascular Medicine. J Am Soc Echocardiogr 2008; 21:93–111.  Back to cited text no. 9
    
10.
Krishnaswamy B, Raja N, Deepa S. A study of peripheral vascular disease in elderly and its association with coronary artery disease. J Indian Acad Geriatr 2006; 2:10–13.  Back to cited text no. 10
    
11.
Schink C, Hesse S, Stoppe M, Meyer K, Schmidt E. Post-dexamethasone serum copeptin corresponds to HPA axis responsiveness in human obesity. Psychoneuroendocrinology 2017; 78:39–47.  Back to cited text no. 11
    
12.
Enhörning S, Wang TJ, Nilsson PM, Almgren P, Hedblad B, Berglund G. Plasma copeptin and the risk of diabetes mellitus. Circulation 2010; 121:2102–2108.  Back to cited text no. 12
    
13.
Spruce BA, McCulloch AJ, Burd J, Orskov H, Heaton A, Baylis PH, Alberti KG. The effect of vasopressin infusion on glucose metabolism in man. Clin Endocrinol (Oxf) 1985; 22:463–468.  Back to cited text no. 13
    
14.
Aoyagi T, Birumachi J, Hiroyama M, Fujiwara Y, Sanbe A, Yamauchi J, Tanoue A. Alteration of glucose homeostasis in V1a vasopressin receptor-deficient mice. Endocrinology 2007; 148:2075–2084.  Back to cited text no. 14
    
15.
Fujiwara Y, Hiroyama M, Sanbe A, Aoyagi T, Birumachi J, Yamauchi J et al. Insulin hypersensitivity in mice lacking the V1b vasopressin receptor. J Physiol 2007; 584:235–244.  Back to cited text no. 15
    
16.
Mellbin LG, Ryden L, Brismar K. Copeptin, IGFBP-1, and cardiovascular prognosis in patients with type 2 diabetes and acute myocardial infarction: a report from the DIGAMI 2 trial. Diabetes Care 2010; 33:1604–1606.  Back to cited text no. 16
    
17.
Tasevska I, Enhörning S, Persson M, Nilsson PM, Melander O. Copeptin predicts coronary artery disease cardiovascular and total mortality. Heart 2016; 102:127–132.  Back to cited text no. 17
    
18.
Boeckel JN, Oppermann J, Anadol R, Fichtlscherer S, Andreas M, Zeiher AM, Kellera T. Analyzing the release of copeptin from the heart in acute myocardial infarction using a transcoronary gradient model. Sci Rep 2016; 6:20812.  Back to cited text no. 18
    
19.
Wannamethee SG, Welsh P, Lennon L, Papacosta O, Whincup PH, Sattar N. Copeptin and the risk of incident stroke, CHD and cardiovascular mortality in older men with and without diabetes: The British Regional Heart Study. Diabetologia 2016; 59:1904–1912.  Back to cited text no. 19
    
20.
Reichlin T, Hochholzer W, Stelzig C, Laule K, Freidank H et al. Incremental value of copeptin for rapid rule out of acute myocardial infarction. J Am Coll Cardiol 2009; 54:60–68.  Back to cited text no. 20
    
21.
Keller T, Tzikas S, Zeller T, Czyz E, Lillpopp L, Ojeda FM. Copeptin improves early diagnosis of acute myocardial infarction. J Am Coll Cardiol 2010; 55:2096–2106.  Back to cited text no. 21
    
22.
Gu YL, Voors AA, Zijlstra F, Hillege HL, Struck J, Masson S. Comparison of temporal release pattern of copeptin with conventional biomarkers in acute myocardial infarction. Clin Res Cardiol 2011; 100:1069–1076.  Back to cited text no. 22
    
23.
Khan SQ, Dhillon OS, O’Brien RJ, Struck J, Quinn PA, Morgenthaler NG. C-terminal pro-vasopressin (copeptin) as a novel and prognostic marker in acute myocardial infarction: leicester acute myocardial infarction peptide (LAMP) study. Circulation 2007; 115:2103–2110.  Back to cited text no. 23
    
24.
Von Haehling S, Papassotiriou J, Morgenthaler NG, Hartmann O, Doehner W et al. Copeptin as a prognostic factor for major adverse cardiovascular events in patients with coronary artery disease. Int J Cardiol 2012; 162:27–32.  Back to cited text no. 24
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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