Evaluation of Index of Cardio-Electrophysiological Balance in Patients With Atrial Fibrillation on Antiarrhythmic-Drug Therapy
Background
Index of cardio-electrophysiological balance (iCEB) has been described as a novel risk marker for predicting malignant ventricular arrhythmia. There remains limited evidence on the effects of amiodarone and propafenone used for sinus rhythm maintenance on iCEB in patients with atrial fibrillation (AF). The aim of this study was to evaluate iCEB in patients with AF on antiarrhythmic-drug therapy.
Methods
A total of 108 patients with AF (68 patients using amiodarone and 40 patients using propafenone) and 50 healthy subjects were included in the study. All groups underwent a standard 12-lead surface electrocardiogram. QRS duration, QT, T wave peak-to-end (Tp-e) intervals, iCEB (QT/QRS) and iCEBc (heart rate-corrected QT (QTc)/QRS) rates were calculated from the electrocardiogram and compared between groups.
Results
QT, Tp-e intervals and Tp-e/QT ratio were significantly longer in the amiodarone group than the propafenone and control groups (P < 0.001, for all). iCEB was similar in the amiodarone and control groups (4.4 ± 0.6 and 4.2 ± 0.4; P > 0.05), while iCEB values in the propafenone group were significantly lower than the amiodarone group and control groups (3.9 ± 0.5; P < 0.001). There was a significantly difference in iCEBc values among the amiodarone, control and propafenone groups (4.8 ± 0.6, 4.6 ± 0.4 and 4.3 ± 0.6; P < 0.001, respectively).
Conclusions
In this study, higher iCEBc parameters were observed in patients using amiodarone, while iCEBc values were lowest among patients with AF using propafenone. Further studies are needed to determine whether these electrophysiological changes are associated with ventricular arrhythmias for patients with AF on antiarrhythmic-drug therapy.
Introduction
Atrial fibrillation (AF) is the most common heart rhythm disorder in clinical practice and is a significant risk factor for stroke and heart failure [1]. The prevalence of AF in the general population is 1-2%, and its incidence and prevalence increase with age. In older adults aged 65 years and older, the prevalence of AF increases to over 10%. In AF treatment, the goal is to reduce cardiovascular mortality and morbidity. The two basic principles of AF treatment are preventing thromboembolic events and ensuring rhythm control or controlling the ventricular rate. The use of antiarrhythmic drugs (AADs) or catheter ablation is often required to maintain sinus rhythm in patients with recurrent paroxysmal AF and in patients with persistent AF to maintain sinus rhythm following cardioversion. The primary concerns associated with the use of AADs are proarrhythmia and consequent ventricular tachyarrhythmia as well as bradycardia. Regular 12-lead electrocardiogram (ECG) monitoring is required to assess the risk for proarrhythmia in patients taking AADs. Current guidelines recommend careful evaluation of the heart rhythm, heart rate, QRS duration, QT interval (i.e., the period of ventricular depolarization and repolarization) and QTc interval (i.e., QT interval corrected for heart rate) in ECG. Despite their poor predictive value, QT interval and QRS duration are widely used in the clinical practice to assess the risk for drug-induced ventricular arrhythmia and sudden cardiac death (SCD).
Many ECG parameters have been developed in an effort to predict ventricular arrhythmias. One example is transmural dispersion of repolarization (TDR), which is measured using the T wave peak-to-end (Tp-e) interval and Tp-e/QT ratio. TDR is a potential marker for ventricular arrhythmias and SCD in patients with acquired long QT syndrome, congenital long QT syndrome, Brugada syndrome, acute myocardial infarction and heart failure. Recently, the index of the cardio-electrophysiological balance (iCEB), which is calculated as QT interval divided by QRS duration (QT/QRS), was identified as a potential marker for predicting drug-induced ventricular arrhythmias in an animal model . iCEB is equivalent to the cardiac wavelength λ, which plays an important role in ventricular arrhythmias and is measured via invasive electrophysiology (EP). Previous studies have suggested that iCEB may offer a non-invasive and readily measurable marker to detect increased arrhythmic risk in patients. To date, there remains limited evidence on the effects of amiodarone and propafenone used for sinus rhythm maintenance on iCEB in patients with AF. This study assessed the iCEB and TDR values in AF patients on amiodarone and propafenone therapy.
Materials and Methods
Study population
The study included patients who attended the cardiology outpatient clinic of two different centers between January 2019 and December 2019. Eligible patients included those who were using propafenone (150 mg three times daily) or amiodarone (200 mg once a day) for paroxysmal or persistent AF with sinus rhythm detected in ECG. The control group included healthy individuals with sinus rhythm assessed using ECGs. Volunteers were recruited from hospital staffs. The healthy controls who had diagnosed cardiac or other organic disease, or who were using medications, were excluded.
Paroxysmal AF was defined as AF that developed suddenly and ended spontaneously within 7 days, whereas persistent AF was defined as AF with medicated or electrical cardioversion lasting more than 7 days. Hypertension (HT) was defined as blood pressure ≥ 140/90 mm Hg or receiving antihypertensive treatment. Diabetes mellitus (DM) was defined as fasting blood glucose level ≥ 126 mg/dL or known DM diagnosis. Coronary artery disease (CAD) was defined as the presence of an angiographic lesion occupying ≥ 50% of the coronary artery, a history of coronary bypass surgery, or percutaneous coronary intervention. Stroke was diagnosed on the identification of ischemia or bleeding in the brain through clinical assessments and imaging methods in patients presenting with neurological dysfunction whose symptoms lasted more than 24 h. Transient ischemic attack was defined as temporary neurological dysfunction that lasted less than 24 h, which caused symptoms but did not result in death or disability. Vascular disease diagnoses included CAD, peripheral artery disease, or aortic plaque. The CHA2DS2-VASc (congestive heart failure/left ventricular dysfunction, HT, aged ≥ 75 years, DM, stroke/transient ischemic attack/systemic embolism, vascular disease, aged 65 – 74 years, sex category) scores of patients were recorded.
We excluded patients with the following cardiac conditions: permanent AF, long-standing persistent AF, atrial flutter, previous AF ablation, acute decompensated heart failure and hereditary long QT syndrome. Also excluded were patients who were using medications that could affect the QRS, QT and Tp-e interval, including antibiotics, tricyclic antidepressants, antihistamines, or antipsychotics; patients with implantable cardioverter-defibrillators; those with previously known branch block and atrioventricular nodal block; and those with negative and/or biphasic T wave on their ECGs. Non-cardiac exclusion criteria were the presence of any severe non-cardiac illness limiting life expectancy, pregnancy, breast-feeding, a calculated glomerular filtration rate of < 60 mL/min at baseline, patients with liver failure and patients with thyroid gland disease. Patients who developed liver and/or thyroid disease due to amiodarone use were included in the study. The study methodology complied with the Declaration of Helsinki and the study protocol was approved by the Institutional Ethics Committee of Adiyaman University (26/06/2019, 2019/5-12).
ECG and echocardiographic examination
All participants underwent a 12-lead ECG (CardioFax S; Nihon Kohden, Tokyo, Japan) while at rest in the supine position. The ECG was set to the paper speed of 50 mm/s and calibrated such that 10 mm equals 1 mV. During the ECG recordings, all of the participants were in sinus rhythm. Resting heart rate was measured using the ECG data. ECG measurements of QRS duration, QT intervals and Tp-e intervals were manually calculated by two cardiologists who were blinded to patient data using calipers and a magnifying glass to decrease measurement errors. The measurements were performed on lead II and lead V5, and the longest QT interval and QRS complex duration were used for the analyses. The QT interval was measured from the beginning of the QRS complex to the end of the T wave, and the QT interval was corrected for heart rate using the Bazett formula: QTc = QT√(R-R interval). Using these measurements, Tp-e/QT, Tp-e/QTc, QT/QRS (iCEB) and QTc/QRS (iCEBc) ratios were calculated. The interobserver and intraobserver variation coefficients were 2.3% and 2.4%, respectively.
All echocardiographic examinations were performed using a Vivid 5 Pro device (General Electric, Horten, Norway) with a 2.5 MHz transducer. The measurements were performed in the left lateral decubitus position as recommended by the current American Society of Echocardiography guidelines, and three consecutive cycles were averaged for each parameter. Ejection fraction (EF) was calculated using the modified Simpson method. Left ventricular systolic dysfunction was defined as a left ventricular EF of < 50%. Left atrium (LA) anteroposterior diameter, diastolic interventricular septum (IVS) thickness and diastolic posterior wall thickness (PWT) were measured from parasternal long-axis views using M-mode.
Laboratory findings were collected from the hospital database. Following a 12 h fasting period, blood samples were collected for complete blood count analyses. Aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine, potassium and calcium levels were analyzed using the Architect c8000 Chemistry System (Abbott Diagnostics, USA) commercial kits. Thyroid-stimulating hormone (TSH) was measured using the UniCel DxI 800 Access Immunoassay System (Beckman Coulter, USA).
Statistical analyses
Continuous variables are reported as means ± standard deviations or medians. Categorical variables are expressed as counts and percentages. Kolmogorov-Smirnov tests and histograms were used to test for normality and to assess the distribution of the numerical variables, respectively. Demographic and clinical features, including ECG and echocardiography parameters, comorbidities, medications, risk scores and laboratory parameters, were compared between groups. One-way analysis of variance (ANOVA) and Kruskal-Wallis tests were used for intergroup comparisons when variables were normally and non-normally distributed, respectively. Intergroup differences were evaluated using parametric and non-parametric tests including the Tukey test and the Dwass-Steel-Critchlow-Fligner test, respectively. Differences in categorical variables were assessed using the Pearson Chi-square, Fisher exact, or Fisher-Freeman-Halton tests, depending on the sample size. The analyses compared patients with and without AF. For variables that showed a normal distribution, independent samples t-tests were used, whereas Mann-Whitney U tests were used to compare variables with non-normally distributed data. For categorical variables, the Pearson Chi-square and Fisher exact tests were used. All statistical analyses were performed using the Jamovi (Version 1.0.7) and JASP (Version 0.11.1) software programs. P values ≤ 0.05 were considered statistically significant.
Results
A total of 173 patients were eligible for study inclusion. Patients with unanalyzable ECG (n = 6) were excluded. In addition, patients who were taking sotalol (n = 9) were excluded due to their small sample size. After exclusions, 158 participants were included in the study. Demographic characteristics, comorbid conditions and laboratory parameters are shown in Table 1. The study groups included patients with persistent AF (n = 17), patients with paroxysmal AF (n = 91) and healthy individuals without AF (n = 50). Among the patients with AF, 68 (63%) were using amiodarone treatment and 40 (37%) were using propafenone treatment at baseline. There were no differences between the groups in terms of age and sex (P > 0.05). The amiodarone treatment group included 57 (83.8%) patients with paroxysmal AF and 11 (16.2%) with persistent AF, whereas the propafenone treatment group included 34 (85.0%) with paroxysmal AF and six (15.0%) with persistent AF. More than half (51.5%) of the patients in the amiodarone group had heart failure compared to only 2.5% in the propafenone group. The prevalence of CAD and stroke were significantly higher in patients using amiodarone compared to those using propafenone (both P < 0.05).
Table 1
Demographic Features, Comorbidities, Drug Use and Some Laboratory Parameters of the Amiodarone, Propafenone and Control Groups
| Amiodarone (n = 68) | Propafenone (n = 40) | Control (n = 50) | P value | |
|---|---|---|---|---|
| Sex (%) | ||||
| Female, n (%) | 30 (44.1) | 21 (52.5) | 26 (52.0) | 0.600a |
| Male, n (%) | 38 (55.9) | 19 (47.5) | 24 (48.0) | |
| Age (years) | 65.3 ± 7.3 | 62.9 ± 5.5 | 62.7 ± 4.4 | 0.051b |
| Smoking (%) | 16 (23.5) | 6 (15.0) | 8 (16.0) | 0.445a |
| Duration of drug use (median (IQR)) | 20.5 (16.0 – 29.0) | 19.0 (13.8 – 23.0) | – | 0.034c |
| Type of atrial fibrillation | ||||
| Paroxysmal | 57 (83.8) | 34 (85) | – | 0.087a |
| Persistent | 11 (16.2) | 6 (15) | – | 0.088a |
| Comorbidities | ||||
| Heart failure (%) | ||||
| Ischemic heart failure | 25 (36.8) | 0 (0.0) | – | < 0.001a |
| Non-ischemic heart failure | 10 (14.7) | 1 (2.5) | – | 0.043a |
| Hypertension (%) | 48 (70.6) | 20 (50.0) | – | 0.053a |
| Coronary artery disease (%) | 38 (55.9) | 8 (20.0) | – | 0.001a |
| Stroke (%) | 12 (17.6) | 1 (2.5) | – | 0.029a |
| Diabetes mellitus (%) | 23 (33.8) | 15 (37.5) | – | 0.859a |
| Concurrent medication use | ||||
| Beta-blocker (%) | 55 (80.9) | 37 (92.5) | – | 0.174a |
| Calcium channel blocker (%) | 7 (10.3) | 3 (7.5) | – | 0.742a |
| ACE inhibitor/ARB (%) | 59 (86.8) | 22 (55.0) | – | 0.001a |
| Spironolactone (%) | 13 (19.1) | 0 (0.0) | – | 0.002a |
| NOAC (%) | 30 (44.1) | 16 (40) | – | 0.676a |
| Warfarin (%) | 14 (20) | 5 (12) | – | 0.286a |
| Aspirin (%) | 20 (29) | 9 (22.0) | – | 0.434a |
| Clopidogrel (%) | 6 (8.8) | 2 (5) | – | 0.707a |
| Laboratory parameters | ||||
| Serum calcium (mg/dL) | 9.5 ± 0.6 | 9.8 ± 0.5 | 9.7 ± 0.5 | 0.158b |
| Serum potassium (mEq/L) | 4.2 ± 0.3 | 4.2 ± 0.3 | 4.2 ± 0.3 | 0.783b |
| Aspartate aminotransferase (U/L) | 22.2 ± 5.3 | 24.7 ± 5.8 | 23.9 ± 6.6 | 0.068b |
| Alanine aminotransferase (U/L) | 23.3 ± 6.2 | 25.0 ± 5.9 | 24.0 ± 7.2 | 0.374b |
| TSH (µU/mL) (median (IQR)) | 2.4 (1.6 – 3.5) | 2.5 (1.9 – 3.5) | 2.3 (1.7 – 3.1) | 0.493 |
| Risk score | ||||
| CHA2DS2-VASc score (median (IQR)) | 3.0 (2.8 – 4.0) | 2.0 (1.0 – 3.0) | – | < 0.001c |
aDepending on the expected count, Pearson Chi-square, Fisher exact or Fisher-Freeman-Halton test was used. Descriptive statistics were presented as number (%). bOne-way ANOVA was used. Descriptive statistics were presented as mean ± standard deviation. cMann-Whitney U test was used. Descriptive statistics were presented as median (IQR). ACE: angiotensin-converting enzyme; ARB: angiotensin receptor blocker; NOAC: new oral anticoagulants; TSH: thyroid-stimulating hormone; IQR: interquartile range.