Abstract
Background
Correlations between increased copeptin levels and various cardiovascular diseases have been described. In this study, we aimed to investigate the correlation between increased copeptin levels and paroxysmal atrial fibrillation (PAF) in rheumatic mitral stenosis (MS).
Methods
Patients with mild/moderate rheumatic MS and sinus rhythm were consecutively recruited from an echocardiography laboratory. Patients with a history of PAF and those with PAF on 24-48-hour ambulatory electrocardiography (ECG) monitoring constituted the study group, and those without PAF on ambulatory ECG monitoring constituted the control group. Clinical characteristics, echocardiographic parameters and levels of copeptin, plasma N-terminal proBNP (NT-proBNP) and high-sensitivity C-reactive protein (hs-CRP) were evaluated.
Results
Twenty-nine patients with PAF and 124 control MS patients were studied. Patients in the PAF group were older, but the mitral valve areas and transmitral gradients were not different between the groups. In the PAF group, hs-CRP (1.2 vs. 0.8 mg/L, p < 0.001), NT-proBNP (335 vs. 115 pg/mL, p < 0.001) and copeptin (6.9 vs. 4.0 pmol/L, p < 0.001) levels were significantly higher than in the control group. Multivariable logistic regression analysis revealed that age [odds ratio (OR) 1.19, 95% confidence interval (CI) 1.04-1.38; p = 0.024], left atrial volume index (OR 1.23, 95% CI 1.06-1.41; p = 0.032), copeptin levels (OR 2.81, 95% CI 1.30-5.29; p < 0.001) and hs-CRP levels (OR 15.5, 95% CI 1.41-71.5; p = 0.012) were independent predictors of PAF.
Conclusions
In patients with mild/moderate rheumatic MS, higher copeptin and hs-CRP levels predicted a higher risk of developing atrial fibrillation.
Keywords: Atrial fibrillation, Predictor, Valvular heart disease
INTRODUCTION
Mitral stenosis (MS) is the most common form of rheumatic heart disease (RHD) and is still a major cause of cardiovascular surgery, morbidity and mortality in developing countries.1,2 MS usually presents with exertional dyspnea and/or decreased exercise tolerance; however, nearly 15% of patients develop embolic episodes that are usually associated with atrial fibrillation (AF). Left atrial (LA) dilatation, inflammatory and fibrotic changes in the atria and aging are the main factors associated with the risk of AF in this group of patients.3-6
In MS, a chronic inflammatory state and increased wall tension secondary to increased LA pressure lead to depletion of contractile elements, glycogen particle accumulation and the development of collagen bundles in the interstitium, which causes electrical remodeling and subsequent atrial arrhythmias.5 Accordingly, elevated levels of inflammatory markers [C-reactive protein (CRP)], adipokines (resistin, adiponectin) and neuroendocrine hormones [N-terminal pro-brain natriuretic peptide (NT-proBNP)] have been shown to predict incident AF as well as AF recurrence.7-11 Arginine vasopressin (AVP) is a hormone synthesized in the hypothalamus and stored in the hypophysis. AVP is an important regulator of fluid homeostasis and is secreted secondary to hyperosmolality, low cardiac output and falls in extracellular volume. Copeptin is the C-terminal part of pro-AVP, is released in equimolar amounts to AVP, and is accepted to be a surrogate marker of AVP. Recent studies have revealed the prognostic value of high copeptin levels in the general population, in patients with cerebrovascular disease, renal failure and heart failure, and as an early marker of cardiac ischemia.12-14 In addition, copeptin has been reported to predict recurrent cerebrovascular events after stroke.15,16
Silent brain infarcts have been reported in 25% of patients with MS, especially in those with AF.17 Thus, it is important to identify patients who may have a higher risk of developing AF. In this study, we investigated the correlation between copeptin and NT-proBNP levels with the risk of AF in MS patients.
MATERIALS AND METHODS
Study population
Consecutive patients with a diagnosis of RHD who underwent transthoracic echocardiographic examinations between January 2015 and January 2018 were prospectively recruited. Patients older than 65 years and those with chronic AF, severe valvular stenosis or regurgitation, heart failure with reduced left ventricular ejection fraction (EF < 40%), left ventricular hypertrophy, coronary artery disease, hypo- or hyperthyroidism, hypo- or hypernatremia, acute or chronic inflammatory diseases, malignancy, chronic obstructive pulmonary disease and/or chronic renal failure were excluded from the study. Patients with a documented episode of paroxysmal AF (PAF) were included in the study if they were in sinus rhythm at the time of recruitment. For these cases, 24-48-hour electrocardiographic (ECG) monitoring was not performed. In total, 153 patients were included in the study. The demographic data, clinical properties and 12-lead ECG of the participants were recorded. All participants provided written informed consent, and the study protocol was approved by the local ethics committee.
Definitions
Hypertension (HT) was defined as a systolic pressure of ≥ 140 mmHg and/or a diastolic pressure of 90 mmHg, or if the individual was taking antihypertensive medications. Diabetes mellitus (DM) was defined as a fasting glucose level of ≥ 126 mg/dl and/or if the patient was taking anti-diabetic medication. Individuals who reported smoking at least one cigarette per day during the year before the examination were classified as being smokers. The functional capacity of the subjects was defined according to the New York Heart Association’s (NYHA) classification of heart failure. Body mass index (BMI) was calculated as weight (kg) / height (m2), and body surface area (BSA) was calculated as [(height (cm) × weight (kg))/ 3600]1/2.
Echocardiographic examination
All of the patients were examined during sinus rhythm by two experienced echocardiographers who were blind to the laboratory data and clinical properties of the patients. The examinations were performed using a Philips IE33 xMATRIX Echocardiography System. The standard evaluation included M-mode, two-dimensional and Doppler studies according to the recommendations of the American Society of Echocardiography.18 LA volume was calculated using the biplane Simpson method, and the LA volume index was calculated in terms of ml/m2 by dividing LA volume by BSA.
The severity of MS was evaluated using the peak and mean gradients obtained at the mitral inflow velocities with continuous wave Doppler ultrasound scanning from the apical view. The mitral valve area was calculated using the pressure half-time (PHT) method and planimetry of the mitral valve orifice in early diastole from the short-axis view. Patients with a valve area of < 1.0 cm2 (either by PHT or the planimetry method) or a mean gradient of > 10 mmHg were considered to have severe MS and were excluded from the study. Disagreements about the severity of MS were resolved through discussion and consensus with a third investigator.
Laboratory analyses
Venous blood samples were obtained from the subjects after overnight fasting. The complete blood count and routine biochemical laboratory parameters were analyzed. In addition, high-sensitivity (hs)-CRP levels were measured with the enzyme-linked immunosorbent assay (ELISA) method using an Immunodiagnostic CRP Elisa Kit (Immundiagnostik AG, Bensheim, Germany). Serum copeptin concentrations were measured using a competitive enzyme immunoassay (ELISA) (EİAab Wuhan EIAab Science Co. Ltd, Wuhan, China). Serum NT-proBNP levels were measured using an immunoassay with detection by electrochemiluminescence (Roche Diagnostics, São Paulo, SP, Brazil) using 20 μL of serum and polyclonal antibodies to detect epitopes in the N-terminal region (amino acids 1-76) of proBNP (108 amino acids). The assay was fully automated using an Elecsys 2010 automated analyzer (Roche Diagnostics).
Ambulatory ECG monitoring
To define arrhythmic episodes, the patients underwent a single 24-48-hour period of ambulatory ECG monitoring using a portable three-channel ECG recorder (Spiderview, Sorin Group Company, ELA medical, Milan, Italy). Antiarrhythmic medications were stopped for at least two half-lives before the examination. During the monitoring, the patients continued to carry out their normal daily activities. The recordings were analyzed using SyneScope Ambulatory ECG Software (Sorin Group). Atrial fibrillation was defined by irregular ventricular responses in the absence of p-waves or with fibrillatory waves lasting longer than 30 seconds. 24-48-hour ECG monitoring was not performed for patients with a prior diagnosis of PAF documented by either 12-lead ECG or hospital records. All medications before the study were recorded. For patients with a new diagnosis of PAF, anticoagulation was recommended, and other treatment decisions were left to the discretion of the attending physicians.
Statistical analysis
All data are presented as a mean ± standard deviation or median (interquartile range) for parametric variables and as percentages for categorical variables. Continuous variables were checked for normal distribution using Kolmogorov-Smirnov or Shapiro-Wilk statistics. Categorical variables were tested using Pearson’s χ2 test and Fisher’s exact test. Differences between patients and control subjects were evaluated using the Mann-Whitney U test or Student t-test when appropriate. Relationships among the parameters were assessed using Pearson’s or Spearman’s correlation analysis according to normality of the data. Binary logistic regression analysis was used to identify the univariate and multivariable predictors of PAF, which were reported as odds ratios (ORs) and 95% confidence intervals (CI) for one unit increase in each numerical parameter. For the laboratory parameters including copeptin, hs-CRP and NT-proBNP, receiver operating characteristic (ROC) curves were plotted and the optimal values with the greatest total sensitivity and specificity in the prediction of PAF were selected. Reproducibility was assessed by reanalyzing data from 15 randomly selected patients examined by two echocardiographers and reported as inter-observer correlation coefficients. A p-value of < 0.05 was considered to be statistically significant. All statistical studies were carried out using Statistical Package for Social Sciences software (SPSS 21.0 for Windows, SPSS Inc., Chicago, Illinois).
RESULTS
A total of 153 patients with mild/moderate MS were recruited. PAF was diagnosed by 24-hour ECG monitoring in 18 patients, and according to previous medical records in 11 patients. The control group consisted of 124 patients with MS but without PAF. The demographic and clinical properties of the study groups are presented in Table 1. Most of the patients were female, but the gender distributions were similar between the groups. Patients in the PAF group were older (54.3 ± 5.2 vs. 43.4 ± 7.5 years, p < 0.001). The frequency of HT, DM and BMI were not significantly different between the groups. The vital signs and medications were also comparable between the two groups.
Table 1. Comparison of demographic and clinical properties between PAF and control groups in the study population.
| PAF group (n = 29) | Control (n = 124) | p value | |
| Age (years) | 54.3 ± 5.2 | 43.4 ± 7.5 | < 0.001 |
| Male, n (%) | 10 (36) | 31 (25) | 0.325 |
| Hypertension, n (%) | 9 (31) | 29 (24) | 0.451 |
| Diabetes mellitus, n (%) | 6 (22) | 17 (14) | 0.298 |
| Hyperlipidemia, n (%) | 2 (8) | 13 (11) | 0.781 |
| Stroke, n (%) | 2 (5) | - | - |
| Smoking, n (%) | 6 (22) | 24 (20) | 0.685 |
| Previous PAF diagnosis | 11 (38) | - | - |
| BMI, kg/m2 | 28.9 ± 5.2 | 27.2 ± 4.9 | 0.082 |
| BSA, m2 | 1.8 ± 0.2 | 1.7 ± 0.1 | 0.188 |
| NYHA ≥ 2 symptoms | 6 (20) | 17 (14) | 0.441 |
| SBP, mmHg | 123.5 ± 14.7 | 120.8 ± 12.6 | 0.265 |
| DBP, mmHg | 76.8 ± 8.8 | 74.9 ± 7.4 | 0.542 |
| HR, beats/min | 69.6 ± 12.8 | 73.6 ± 14.1 | 0.254 |
| Antiarrhythmic drug, n (%) | 11 (38) | 27 (21.7) | 0.069 |
| BB, n (%) | 7 (24) | 20 (16) | 0.308 |
| CCB, n (%) | 3 (10) | 5 (4) | 0.169 |
| Amiodarone, n (%) | 4 (13) | - | - |
BB, beta-blocker; BMI, body mass index; BSA, body surface area; CCB, calcium channel blocker; DBP, diastolic blood pressure; HR, hearth rate; NYHA, New York Heart Association; PAF, paroxysmal atrial fibrillation; SBP, systolic blood pressure.
The echocardiographic properties of the study groups are depicted in Table 2. The left ventricular dimensions and EFs were similar between the groups. Left atrium antero-posterior diameter, LA volume and LA volume index were significantly higher in the PAF group (48.4 mm ± 5.0 vs. 45.9 mm ± 4.3, p < 0.001; 64.1 ml ± 10.1 vs. 53.1 ml ± 8.8, p < 0.001; and 35.2 mL/m2 ± 4.3 vs. 29.9 mL/m2 ± 5.2, p < 0.001, respectively). However, in the PAF group, the planimetric mitral valve area (MVA) (1.6 ± 0.1 vs. 1.6 ± 0.1 cm2, p = 0.208) and mean transmitral gradients (7.9 ± 2.2 vs. 7.1 ± 2.8 mmHg, p = 0.104) were not significantly different from the control group.
Table 2. Comparison of echocardiographic parameters and NT-proBNP and copeptin levels in PAF and control groups in the study population.
| PAF group (n = 29) | Control (n = 124) | p value | |
| Echocardiography | |||
| LVDD, mm | 49.2 ± 3.2 | 48.9 ± 3.4 | 0.870 |
| LVSD, mm | 32.1 ± 3.6 | 32.9 ± 4.4 | 0.611 |
| EF, % | 61.9 ± 4.1 | 62.7 ± 2.8 | 0.415 |
| LA-AP diameter, mm | 48.4 ± 5.0 | 45.9 ± 4.3 | < 0.001 |
| LA volume, mL | 64.1 ± 10.1 | 53.1 ± 8.8 | < 0.001 |
| LA volume index, mL/m2 | 35.2 ± 4.3 | 29.9 ± 5.2 | < 0.001 |
| Mean transmitral gradient, mmHg | 7.9 ± 2.2 | 7.1 ± 2.8 | 0.104 |
| MVA (planimetry), cm2 | 1.6 ± 0.1 | 1.6 ± 0.1 | 0.208 |
| MVA (pressure half time), cm2 | 1.6 ± 0.1 | 1.7 ± 0.1 | 0.751 |
| Mitral regurgitation, n (%) | |||
| +1 | 10 (36) | 55 (45) | 0.561 |
| +2 | 6 (20) | 18 (15) | 0.392 |
| +3 | 2 (6) | 5 (4) | 0.849 |
| Aortic valve involvement, n (%) | 7 (25) | 26 (21) | 0.682 |
| Laboratory parameters | |||
| WBC, 103/μl | 7.5 ± 1.8 | 7.7 ± 1.5 | 0.652 |
| Hemoglobin, g/dL | 13.9 ± 1.9 | 11.7 ± 1.5 | 0.421 |
| Glucose, mg/dL | 115.0 ± 14.0 | 107.0 ± 19.0 | 0.337 |
| Creatinine, mg/dL | 0.7 ± 0.1 | 0.7 ± 0.1 | 0.741 |
| Na, mEq/L | 135.1 ± 2.9 | 137.9 ± 2.4 | 0.546 |
| K, mEq/L | 4.5 ± 0.8 | 4.9 ± 0.5 | 0.492 |
| Hs-CRP, mg/L | 1.2 [0.7-1.5] | 0.8 [0.4-1.3] | < 0.001 |
| Copeptin, pmol/L | 6.9 [5.2-9.9] | 4.0 [2.9-6.8] | < 0.001 |
| NT-proBNP, pg/mL | 335 [212-699] | 115 [88-326] | < 0.001 |
EF, ejection fraction; Hs-CRP, high sensitive C-reactive protein; LA-AP, left atrium anteroposterior; LVDD, left ventricular diastolic diameter; LVSD, left ventricular systolic diameter; MVA, mitral valve area; NT-proBNP, N-terminal pro brain natriuretic peptide; PAF, paroxysmal atrial fibrillation; WBC, white blood cell.
Comparisons of the laboratory parameters are summarized in Table 2. There were no significant differences in the biochemical parameters between the two groups. However, in the PAF group, hs-CRP [1.2 (0.7-1.5) vs. 0.8 (0.4-1.3) mg/L, p < 0.001], NT-proBNP [335 (212-699) vs. 115 (88-326) pg/mL, p < 0.001] and copeptin levels [6.9 (5.2-9.9) vs. 4.0 (2.9-6.8) pmol/L, p < 0.001] were significantly higher. In the univariate correlation analysis, copeptin levels were significantly correlated with MVA (r = -0.289, p < 0.01), LA volume (r = 0.327, p < 0.01), LA volume index (r = 0.282, p < 0.01), hs-CRP level (r = 0.312, p < 0.01) and NT-proBNP level (r = 0.371, p < 0.01). In addition, NT-proBNP levels were significantly associated with MVA (r = -0.216, p < 0.01), LA volume (r = 0.284, p < 0.01) and LA volume index (r = 0.330, p < 0.01).
In the univariate binary logistic regression analysis, age, LA volume index, copeptin, NT-proBNP and hs-CRP levels were found to predict PAF in Table 3. The multivariable logistic regression analysis adjusted for these variables showed that age (OR 1.19, 95% CI 1.04-1.38; p = 0.024), LA volume index (OR 1.23, 95% CI 1.06-1.41; p = 0.032), copeptin levels (OR 2.81, 95% CI 1.30-5.29; p < 0.001) and hs-CRP levels (OR 15.5, 95% CI 1.41-71.5; p = 0.012) were independent predictors of PAF. NT-proBNP levels did not independently predict PAF (OR 1.005, p = 0.245). In the multivariable model adjusted only for age and LA volume index, NT-proBNP levels (OR 1.003, p = 0.588) did not predict PAF.
Table 3. Univariate and multivariate regression analysis for the predictors of paroxysmal atrial fibrillation in the study population.
| Variables | Univariate | Multivariate | ||
| OR (95% CI) | p | OR (95% CI) | p | |
| Age | 1.28 (1.11-1.46) | < 0.001 | 1.19 (1.04-1.38) | 0.024 |
| Male gender | 1.58 (0.66-3.75) | 0.302 | - | - |
| Hypertension | 1.47 (0.60-3.59) | 0.393 | - | - |
| Diabetes mellitus | 1.64 (0.58-4.61) | 0.347 | - | - |
| Body mass index | 1.11 (0.97-1.23) | 0.151 | - | - |
| LA volume index | 1.20 (1.05-1.34) | < 0.001 | 1.23 (1.06-1.41) | 0.032 |
| MVA (planimetry) | 0.13 (0.06-2.99) | 0.251 | - | - |
| Mean transmitral gradient | 1.13 (0.85-1.30) | 0.755 | - | - |
| Glucose | 1.01 (0.71-1.42) | 0.782 | - | - |
| Creatinine | 1.73 (0.78-38.24) | 0.73 | - | - |
| Hemoglobin | 1.04 (0.66-1.63) | 0.876 | - | - |
| WBC | 0.79 (0.61-1.05) | 0.125 | - | - |
| Hs-CRP | 11.32 (2.41-51.14) | < 0.001 | 15.54 (1.41-71.52) | 0.012 |
| Copeptin | 2.66 (1.81-3.92) | < 0.001 | 2.81 (1.30-5.29) | < 0.001 |
| NT-proBNP | 1.002 (1.001-1.004) | 0.027 | 1.005 (0.975-1.011) | 0.245 |
Hs-CRP, high sensitive C-reactive protein; LA, left atrium; MVA, mitral valve area; NT-proBNP, N-terminal pro brain natriuretic peptide; PAF, paroxysmal atrial fibrillation; WBC, white blood cell.
ROC curve analysis was performed to assess the predictive value of copeptin levels for PAF. The optimal cut-off value of copeptin was > 4.7 pmol/L with a sensitivity of 91% and a specificity of 79% [area under the ROC curve (AUC) = 0.84, 95% CI 0.76-0.94, p < 0.001]. In addition, the ROC curve analysis revealed an AUC of 0.68 (95% CI 0.58-0.78, p < 0.001) for hs-CRP with an optimal cut-off level of > 0.5 mg/L, and 0.70 (95% CI 0.60-0.80, p < 0.001) for NT-proBNP with an optimal cut-off level of > 255 pg/mL (Figure 1).
Figure 1.
Diagram for receiver operating characteristics (ROC) curve analysis and comparison of copeptin, hs-CRP and NT-proBNP levels to predict paroxysmal atrial fibrillation.
The inter-observer correlation coefficients were 0.90 (95% CI 0.85-0.95) for mean transmitral gradient measurements, 0.88 (95% CI 0.80-0.95) for planimetric MVA measurements and 0.87 (95% CI 0.77-0.96) for MVAs calculated with PHT.
DISCUSSION
The major findings of this study are: 1) in patients with MS and sinus rhythm, higher copeptin levels independently predicted the development of PAF; 2) the other predictors of PAF were increased age, LA volume index and hs-CRP levels; and 3) copeptin levels were correlated with the severity of MS, LA volume, NT-proBNP levels and hs-CRP levels.
The pathophysiological mechanism of AF is complex and includes morphological changes in the atria, chronic inflammation, oxidative stress and neurohumoral activation.19 Atrial stretch is also thought to play a role in the development of AF in patients with HT, mitral valve disease and heart failure.20 A longer disease period and a longer inflammatory process in older patients have been suggested to be causative factors predisposing patients to AF. AF is a major complication in MS patients, and it contributes to both morbidity and mortality in patients with RHD.21 We found that in mild/moderate MS patients, age, increased LA volume and hs-CRP levels could predict PAF, which is consistent with previous studies on the risk factors of AF.
Copeptin and AVP are produced in the hypothalamus and released from the neurohypophysis in response to a drop in blood pressure, changes in osmotic pressure and endogenous stress. The physiological relevance of copeptin is unknown, however AVP can lead to the release of adrenocorticotropic hormone (ACTH), water retention and vasoconstriction as part of the volume regulation in which AVP plays a major role. However, vasopressin has not been widely used in clinical practice due to its rapid clearance and in vitro instability. The C-terminal fragment of pro-vasopressin (copeptin) is released in equimolar amounts to AVP and is accepted to be a surrogate marker for AVP secretion. Both the clinical use and prognostic importance of copeptin levels have been reported in various cardiovascular diseases, including HT, hypertrophic cardiomyopathy, acute coronary syndromes and pulmonary embolism.22-25
In this study, we found that higher copeptin and NT-proBNP levels were correlated with MVA and LA volume index, which is consistent with previous studies.26-29 NT-proBNP and copeptin levels have been shown to decrease significantly within 24 hours after percutaneous balloon mitral valvuloplasty, which indicates the strong correlation between copeptin levels with atrial pressure and stretch. Increased levels of vasoactive peptides such as NT-proBNP, copeptin, mid-regional pro-atrial natriuretic peptide (MR-proANP), mid-regional pro-adrenomedullin (MR-proADM) and copeptin have also been shown to have predictive value in AF patients.7,8,14 Schnabel et al.9 reported that, in the general population with various cardiovascular diseases, NT-proBNP was a strong correlate of AF, but that copeptin levels were modestly elevated in patients with AF. Latini et al.8 investigated the correlation of NT-proBNP and copeptin with the risk of AF recurrence in 382 patients with PAF, and found that NT-proBNP, MR-proADM, MR-proANP and copeptin levels were higher in the patients who had AF recurrence during 1 year of follow-up. To the best of our knowledge, our study is first to investigate the correlation between vasoactive peptides and the risk of AF in RHD patients. We found that increased copeptin and hs-CRP levels independently predicted PAF. Even though NT-proBNP levels were higher in the PAF group in the multivariable regression analysis, the correlation did not remain significant when age and LA volume index were considered as covariates. In Schnabel et al.’s study,9 LA dilatation was not evaluated, which is a major risk factor for AF. In Latini et al.’s study,8 a high proportion of the patients were using antiarrhythmic drugs during the follow-up period, which may have affected the rate of AF recurrence. In our study, antiarrhythmic medications were stopped before ambulatory ECG monitoring.
Arginine vasopressin exerts a wide variety of effects on the heart, vascular smooth muscle, vascular endothelium, platelets and kidneys.30 V1a receptors mediate vasoconstriction, platelet aggregation, myocardial hypertrophy and fibrosis, whereas the activation of V2 receptors in renal collecting ducts mediates the antidiuretic effects of AVP. AVP levels have been independently associated with greater LA volume due to chronically increased LA pressure.31 A recent study reported that AVP has direct effects on electrical activity and Ca2+ homeostasis in pulmonary veins (PV) cardiomyocytes. AVP increases PV arrhythmogenesis with dysregulated Ca2+ homeostasis through vasopressin V1 signaling, and arginine vasopressin has been shown to modulate electrical activity and calcium homeostasis in pulmonary vein cardiomyocytes.32 These reports support the hypothesis that higher copeptin levels indicate higher atrial pressure, atrial stretch, chronic changes in the atria, and a propensity for arrhythmia and AF in RHD patients.
Limitations
The main limitation of this study is the relatively small number of patients with PAF. As 24-48-hour ambulatory ECG monitoring was used in our study, a longer monitoring period would increase the chance of a PAF diagnosis. Even though our results are hypothesis generating, large-scale studies are warranted to determine the clinical use of copeptin measurements in the prediction of AF in different patient populations.
CONCLUSION
Copeptin is a novel biochemical parameter that has clinical application in many cardiovascular diseases. In this study, we found that higher copeptin levels may predict PAF episodes in MS patients with sinus rhythm. The clinical use of copeptin measurements to predict PAF and stroke risk in patients with MS should be further investigated in larger prospective studies.
CONFLICTS OF INTEREST
The authors have nothing to declare.
REFERENCES
- 1.Carapetis JR, Steer AC, Mulholland EK, et al. The global burden of group A streptococcal diseases. Lancet Infect Dis. 2005;5:685–694. doi: 10.1016/S1473-3099(05)70267-X. [DOI] [PubMed] [Google Scholar]
- 2.Seckeler MD, Hoke TR. The worldwide epidemiology of acute rheumatic fever and rheumatic heart disease. Clin Epidemiol. 2011;3:67–84. doi: 10.2147/CLEP.S12977. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Moreyra AE, Wilson AC, Deac R, et al. Factors associated with atrial fibrillation in patients with mitral stenosis: a cardiac catheterization study. Am Heart J. 1998;135:138–145. doi: 10.1016/s0002-8703(98)70354-0. [DOI] [PubMed] [Google Scholar]
- 4.Ozaydin M, Turker Y, Varol E, et al. Factors associated with the development of atrial fibrillation in patients with rheumatic mitral stenosis. Int J Cardiovasc Imaging. 2010;26:547–552. doi: 10.1007/s10554-010-9609-0. [DOI] [PubMed] [Google Scholar]
- 5.Sharma S, Sharma G, Hote M, et al. Light and electron microscopic features of surgically excised left atrial appendage in rheumatic heart disease patients with atrial fibrillation and sinus rhythm. Cardiovasc Pathol. 2014;23:319–326. doi: 10.1016/j.carpath.2014.07.008. [DOI] [PubMed] [Google Scholar]
- 6.Selcuk MT, Selcuk H, Maden O, et al. Relationship between inflammation and atrial fibrillation in patients with isolated rheumatic mitral stenosis. J Heart Valve Dis. 2007;16:468. [PubMed] [Google Scholar]
- 7.Smith JG, Newton-Cheh C, Almgren P, et al. Assessment of conventional cardiovascular risk factors and multiple biomarkers for the prediction of incident heart failure and atrial fibrillation. J Am Coll Cardiol. 2010;56:1712–1719. doi: 10.1016/j.jacc.2010.05.049. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Latini R, Masson S, Pirelli S, et al. Circulating cardiovascular biomarkers in recurrent atrial fibrillation: data from the GISSI-atrial fibrillation trial. J Intern Med. 2011;269:160–171. doi: 10.1111/j.1365-2796.2010.02287.x. [DOI] [PubMed] [Google Scholar]
- 9.Schnabel RB, Wild PS, Wilde S, et al. Multiple biomarkers and atrial fibrillation in the general population. PLoS One. 2014;9:e112486. doi: 10.1371/journal.pone.0112486. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Ozcan KS, Gungor B, Altay S, et al. Increased level of resistin predicts development of atrial fibrillation. J Cardiol. 2014;63:308–312. doi: 10.1016/j.jjcc.2013.10.008. [DOI] [PubMed] [Google Scholar]
- 11.Ucer E, Gungor B, Erdinler IC, et al. High sensitivity CRP levels predict atrial tachyarrhythmias in rheumatic mitral stenosis. Ann Noninvasive Electrocardiol. 2008;13:31–38. doi: 10.1111/j.1542-474X.2007.00198.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Tasevska I, Enhorning S, Persson M, et al. Copeptin predicts coronary artery disease cardiovascular and total mortality. Heart. 2016;102:127–132. doi: 10.1136/heartjnl-2015-308183. [DOI] [PubMed] [Google Scholar]
- 13.Raskovalova T, Twerenbold R, Collinson PO, et al. Diagnostic accuracy of combined cardiac troponin and copeptin assessment for early rule-out of myocardial infarction: a systematic review and meta-analysis. Eur Heart J Acute Cardiovasc Care. 2014;3:18–27. doi: 10.1177/2048872613514015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Lipinski MJ, Escarcega RO, D'Ascenzo F, et al. A systematic review and collaborative meta-analysis to determine the incremental value of copeptin for rapid rule-out of acute myocardial infarction. Am J Cardiol. 2014;113:1581–1591. doi: 10.1016/j.amjcard.2014.01.436. [DOI] [PubMed] [Google Scholar]
- 15.Katan M, Nigro N, Fluri F, et al. Stress hormones predict cerebrovascular re-events after transient ischemic attacks. Neurology. 2011;76:563–566. doi: 10.1212/WNL.0b013e31820b75e6. [DOI] [PubMed] [Google Scholar]
- 16.Greisenegger S, Segal HC, Burgess AI, et al. Copeptin and long-term risk of recurrent vascular events after transient ischemic attack and ischemic stroke: population-based study. Stroke. 2015;46:3117–3123. doi: 10.1161/STROKEAHA.115.011021. [DOI] [PubMed] [Google Scholar]
- 17.Akdemir I, Dagdelen S, Yuce M, et al. Silent brain infarction in patients with rheumatic mitral stenosis. Jpn Heart J. 2002;43:137–144. doi: 10.1536/jhj.43.137. [DOI] [PubMed] [Google Scholar]
- 18.Lang RM, Badano LP, Mor-Avi V, et al. Recommendations for cardiac chamber quantifcation by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging. 2015;16:233–270. doi: 10.1093/ehjci/jev014. [DOI] [PubMed] [Google Scholar]
- 19.Schotten U, Verheule S, Kirchhof P, et al. Pathophysiological mechanisms of atrial fibrillation: a translational appraisal. Physiol Rev. 2011;91:265–325. doi: 10.1152/physrev.00031.2009. [DOI] [PubMed] [Google Scholar]
- 20.Lubitz SA, Benjamin EJ, Sc M, Ellinor PT. Atrial fibrillation in congestive heart failure. Heart Fail Clin. 2010;6:187–200. doi: 10.1016/j.hfc.2009.11.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Noubiap JJ, Nyaga UF, Ndoadoumgue AL, et al. Meta-analysis of the incidence, prevalence, and correlates of atrial fibrillation in rheumatic heart disease. Global Heart. 2020;15:38. doi: 10.5334/gh.807. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Afsar B. Pathophysiology of copeptin in kidney disease and hypertension. Clin Hypertens. 2017;23:13. doi: 10.1186/s40885-017-0068-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Sahin I, Gungor B, Ozkaynak B, et al. Higher copeptin levels are associated with worse outcome in patients with hypertrophic cardiomyopathy. Clin Cardiol. 2017;40:32–37. doi: 10.1002/clc.22602. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Konstantinides SV, Meyer G, Becattini C, et al. 2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS): The Task Force for the diagnosis and management of acute pulmonary embolism of the European Society of Cardiology (ESC). Eur Respir J. 2020;41:543–603. doi: 10.1093/eurheartj/ehz405. [DOI] [PubMed] [Google Scholar]
- 25.Roffi M, Patrono C, Collet JP, et al. Acute coronary syndromes (ACS) in patients presenting without persistent ST-segment elevation (management of) guidelines. Eur Heart J. 2016;37:267–315. [PubMed] [Google Scholar]
- 26.Ranganayakulu KP, Rajasekhar D, Vanajakshamma V, et al. N-terminal-pro-brain natriuretic peptide, a surrogate biomarker of combined clinical and hemodynamic outcomes following percutaneous transvenous mitral commissurotomy. J Saudi Heart Assoc. 2016;28:81–88. doi: 10.1016/j.jsha.2015.07.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Gunebakmaz O, Celik A, Inanc MT, et al. Copeptin level and copeptin response to percutaneous balloon mitral valvuloplasty in mitral stenosis. Cardiology. 2011;120:221–226. doi: 10.1159/000335888. [DOI] [PubMed] [Google Scholar]
- 28.Chadha DS, Karthikeyan G, Goel K, et al. N-terminal pro-BNP plasma levels before and after percutaneous transvenous mitral commissurotomy for mitral stenosis. Int J Cardiol. 2010;144:238–240. doi: 10.1016/j.ijcard.2009.01.001. [DOI] [PubMed] [Google Scholar]
- 29.Shang Y, Lai L, Chen J, et al. Effects of percutaneous balloon mitral valvuloplasty on plasma B-type natriuretic peptide in rheumatic mitral stenosis with and without atrial fibrillation. J Heart Valve Dis. 2005;14:453–459. [PubMed] [Google Scholar]
- 30.Holmes CL, Landry DW, Granton JT. Science review: vasopressin and the cardiovascular system part 2—clinical physiology. Crit Care. 2004; 8:15–23. doi: 10.1186/cc2338. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Chirinos JA, Sardana M, Oldland G, et al. Association of arginine vasopressin with low atrial natriuretic peptide levels, left ventricular remodelling, and outcomes in adults with and without heart failure. ESC Heart Fail. 2018;5:911–919. doi: 10.1002/ehf2.12319. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Huang JH, Chen YC, Lu YY, et al. Arginine vasopressin modulates electrical activity and calcium homeostasis in pulmonary vein cardiomyocytes. J Biomed Sci. 2019;26:71. doi: 10.1186/s12929-019-0564-3. [DOI] [PMC free article] [PubMed] [Google Scholar]