Signal averaged electrocardiography and renal function in hypertensive patients

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1 Signal averaged electrocardiography and renal function in hypertensive patients IOANA MOZOS 1, MIRCEA HANCU 1, LELIA SUSAN 2 1 Department of Functional Sciences 2 1 st Department of Internal Medicine Victor Babes University of Medicine and Pharmacy T. Vladimirescu Str. 14, Timisoara ROMANIA ioana_mozos@yahoo.com Abstract: - Abnormal signal averaged electrocardiograms (SAECGs) and late ventricular potentials (LVPs) are predictors of sudden cardiac death. The present study hypothesized that SAECGs are impaired in hypertensive patients with renal failure. A total of 30 patients with grade 2 hypertension underwent SAECG. Serum level of creatinine and glomerular filtration rate (GFR) were also assessed. At least one SAECG time-domain criteria was positive in 20 patients (67%) and 13 patients had at least two positive criteria (43%). Significant correlations and associations were obtained between SAECG criteria and creatinine and GFR, respectively. Impaired renal function was a sensitive and specific predictor of abnormal SAECGs and LVPs. An impaired renal function is significantly associated and predicts abnormal SAECGs and LVPs in hypertensive patients. Key-Words: - Signal averaged electrocardiography, late ventricular potentials, hypertension, renal function 1 Introduction Patients with chronic kidney disease are at a high risk of cardiovascular death [1,2]. Ventricular arrhythmias are related, in patients with end-stage renal failure, to hemodynamic status and fluctuations in electrolytes [3]. A high risk of sudden cardiac death was previously demonstrated in hypertensive patients, related to left ventricular hypertrophy, interstitial fibrosis, myocardial or subendocardial scars, silent myocardial ischemia, diastolic dysfunction and disturbances in cardiac autonomic balance [4]. Signal averaged electrocardiography (SAECG) is a non-invasive method, used to evaluate sudden cardiac death risk. Late ventricular potentials (LVPs) can be recorded as low amplitude, high frequency waves, appearing in the terminal part of the ECG QRS complex; they represent slowed conduction through a diseased myocardium and may form the substrate for life-threatening reentry ventricular arrhythmias [4].. 2 Problem Formulation The present study hypothesized that signal averaged electrocardiograms are impaired in hypertensive patients with renal failure. 2.1 Patients The most important inclusion criteria were hypertension, diagnosed considering the criteria of the European Society of Cardiology [5]. The most important exclusion criteria were: atrial flutter, electrolyte imbalances, active infections, peripheral edema and chronic obstructive pulmonary disease. The investigations conformed to the principles outlined in the Declaration of Helsinki (Cardiovascular Research 1997; 35:2-4) and were approved by the Ethics Committee of the University. A written informed consent was obtained from each patient Renal function Serum levels of creatinine were assessed in the entire study population. The glomerular filtration rate, the best index of kidney function, was calculated according to estimated glomerular filtration rate using the Modification of Diet in Renal Disease (MDRD) equation (GFRMD) [6], Cockroft Gault equation (GFRCG) [7] and Salazar-Corcoran equation for obese patients (GFRSC) [8] Signal averaged electrocardiography Each patient underwent signal averaged electrocardiography (SAECG). SAQRS (signal averaged ECG QRS duration), the duration of the ISBN:

2 low-amplitude signal (LAS40) and the root mean square of the terminal 40 ms of the filtered QRS (RMS40) were assessed [9]. The following timedomain criteria were positive: SAQRS >120 ms, LAS40 >38 ms and RMS40<20 µv [9]. SAECG was considered abnormal if at least one criteria was positive [10], and late ventricular potentials were present if at least two criteria were positive [11]. SAECG methodology was previously described [12] Standard 12-lead ECG was recorded using the same Siemens-Megacart electrocardiograph used to detect LVPs, at a paper speed of 25 mm/sec. Left ventricular hypertrophy (LVH) was diagnosed considering at least one of the following 6 ECG criteria: the Romhilt-Estes scoring system (a score of 5 diagnoses LVH and a score of 4 diagnoses probable LVH ) [13], the Sokolow-Lyon index (SV1/V2 + RV5/V6 >35 mm) [14], the Cornell voltage criteria (R in a VL + S in V3: >28 mm in men, >20 mm in women), the Cornell product (Cornell voltage x QRS duration>2436 mm.ms) [15, 16], the Mazzaro score ((highest R x deepest S) x QRS duration>2800 mm.ms) [17], the Gubner Ungerleider voltage (RI+SIII>25 mm) [18] Statistical analysis Continuous variables are presented as means ± SD (standard deviation). Linear and multiple regression analysis, Bravais-Pearson correlation coefficient (r), the t Student test, sensitivity and specificity were used as statistical methods. A p<0.05 was considered statistically significant. 3 Problem Solution 3.1. Characteristics of study population A total of 30 consecutive patients with grade 2 hypertension, aged 62±11 years, were enrolled in the study. The clinical characteristics of the patients are included in table 1. Serum creatinine was elevated >1.2 mg/dl in 7 patients (23%), GFRMD was <60 ml/min in 12 patients (40%) and 9 patients (30%) had low GFRCG and GFRSC (<60 ml/min), respectively Late ventricular potentials At least one time-domain criteria was positive in 20 patients (67%) (SAECG1) and 13 patients had at least two positive criteria (43%) (LVPs) Left ventricular hypertrophy was detected in 16 patients (53%) (table 1) Correlations According to the Bravais-Pearson correlation coefficient (r), significant correlations (p<0.05) were obtained between SAECG criteria and creatinine and GFR, respectively (table 2). The best correlations were obtained between LAS40 and GFRMD (r=-0.304) and GFRSC (r=-0.306), respectively Linear regression analysis Significant associations were found between SAECG s and serum creatinine and GFR, respectively (table 3). The most important association was: SAQRS - serum creatinine (multiple R = 0.847, R square = 0.709) Sensitivity and specificity Impaired renal function was a sensitive and specific predictor of abnormal SAECGs and LVPs (table 5-8). Table 1. Characteristics of the patients Clinical characteristics Age (mean±standard 62±11 years deviation) Gender 21(70%) male Cardiovascular risk 1-2 risk factors: 4 (13%) factors Three or more risk factors: 26 (87%) Dyslipidemia: 9 (30%) Obesity: 16(53%) Diabetes mellitus: 6 (20%) History of premature cardiovascular disease: 5 (17%) Associated pathology Coronary heart disease: 8 (27%) Congestive heart failure: 4 (13%) Peripheral artery disease: 1 (3%) Chronic hepatitis: 1 (3%) Liver cirrhosis: 1 (3%) Therapy Beta blockers: 14 (45%) Calcium-blockers: 9 (30%) Angiotensin converting enzyme inhibitors: 20 ISBN:

3 (65%) Angiotensin II receptor blockers: 4 (13%) Diuretics: 6 (20%) Nitrates: 8 (27%) SAQRS (ms) 109±21 LAS40 (ms) 44±21 RMS40 (microv) 21±12 Body mass index 30±4.67 (kg/m 2 ) Serum creatinine (mg/dl) 1.24±0.16 GFRMD (ml/min) 68±5.8 GFRCG (ml/min) 84±7.56 GFRSC (ml/min) 76±6 Left ventricular 16 (53%) hypertrophy Gubner-Ungerleider 21±4.63 voltage (mm) Sokolov-Lyon index 44±7.52 (mm) Cornell voltage index 23±4.81 (mm) Cornell product 1643±608 (mm.ms) Mazzaro score 2708±936 Romhilt-Estes score 3.1±1.4 SAECG = signal averaged electrocardiography QRS duration RMS40 = the root mean square of the terminal 40 ms of the filtered QRS GFR = glomerular filtration rate GFRMD = estimated glomerular filtration rate using GFRCG = GFR calculated using the Cockroft Gault equation GFRSC = GFR calculated using the Salazar- Corcoran equation Table 2. Correlations between signal averaged s and serum creatinine and glomerular filtration rate (GFR), respectively; r = Bravais Pearson correlation coefficient, p<0.05 SAQRS RMS40 LAS40 Serum r = r = r = creatinine GFRMD r = r = 0.06 r = GFRCG r = r = 0.08 r = GFRSC r = -0.2 r = 0.03 r = SAECG = signal averaged ECG QRS duration RMS40 = the root mean square of the terminal 40 ms of the filtered QRS GFRMD = estimated glomerular filtration rate using GFRCG = GFR calculated using the Cockroft Gault equation GFRSC = GFR calculated using the Salazar- Corcoran equation Table 3. Linear regression analysis SAQRScreatinine RMS40- creatinine LAS40- creatinine LAS40- GFRSC MR R 2 Adj. Signif. R 2 F < < < <0.01 SAECG = signal averaged ECG QRS duration RMS40 = the root mean square of the terminal 40 ms of the filtered QRS GFRSC = glomerular filtration rate calculated using the Salazar-Corcoran equation MR = multiple R = multiple correlation coefficient R 2 = R square = coefficient of determination Adj R 2 = adjusted R square = the coefficient of determination adjusted for the number of independent variables in the regression model Signif. F = significance of the association Table 4. Multiple regression analysis. Significance F<0.01. Parameter Assoc. MR R 2 Adj. GFRMD GFRCG SAQRS (p<0.01) LAS40 (p=0.007) SAQRS (p<0.01) LAS40 (p=0.015) R < <0.01 Assoc. = associated with MR = multiple R = multiple correlation coefficient R 2 = R square = coefficient of determination F ISBN:

4 Adj. R 2 = adjusted R square = the coefficient of determination adjusted for the number of independent variables in the regression model GFRMD = estimated glomerular filtration rate using GFRSC = GFR calculated using the Salazar- Corcoran equation SAECG = signal averaged ECG QRS duration Table 5. Elevated serum creatinine (>1.2 mg/dl) as predictor of abnormal signal averaged electrocardiography results (SAECG1) and late ventricular potentials (LVPs). SAECG1 sensitivity specificity LVPs sensitivity specificity The most sensitive predictor of SAECG1 and LVPs was the impaired estimated glomerular filtration rate calculated using the Modification of Diet in Renal Disease equation: GFRMD (sensitivity = 0.4 and 0.38, respectively) (table 6). Elevated serum creatinine was the most specific predictor of SAECG1 and LVPs (specificity = 0.8 and 0.7, respectively) (table 5). High specificity in predicting SAECG1 and LVPs was also obtained for GFR calculated using the Salazar-Corcoran equation: GFRSC (table 8). Table 6. Decreased estimated glomerular filtration rate using the Modification of Diet in Renal Disease equation (GFRMD) (<60 ml/min) as predictor of abnormal signal averaged electrocardiography results (SAECG1) and late ventricular potentials (LVPs). SAECG1 sensitivity specificity LVPs sensitivity specificity Table 7. Decreased glomerular filtration rate calculated using the Cockroft Gault equation (GFRCG) as predictor of abnormal signal averaged electrocardiography results (SAECG1) and late ventricular potentials (LVPs). SAECG1 sensitivity specificity LVPs sensitivity specificity Table 8. Decreased glomerular filtration rate calculated using the Salazar-Corcoran equation (GFRSC) as predictor of abnormal signal averaged electrocardiography results (SAECG1) and late ventricular potentials (LVPs). SAECG1 sensitivity specificity LVPs sensitivity specificity Left ventricular hypertrophy (LVH) was not a sensitive and specific predictor of abnormal signal averaged ECGs and late ventricular potentials, despite the high prevalence of SAECG abnormalities in patients with LVH (71%) (Table 9). Table 9. Left ventricular hypertrophy as predictor of abnormal signal averaged ECGs (SAECG1) and late ventricular potentials (LVPs) SAECG1 sensitivity specificity LVPs sensitivity specificity The t Student test found significantly higher glomerular filtration rates in patients without LVH compared to those with LVH (table 10) Discussions The main finding of the present study is the relation between an impaired renal function and late ISBN:

5 ventricular potentials and abnormal SAECGs in hypertensive patients. LVPs were found by several authors in hypertensive patients, related to eccentric left ventricular hypertrophy and disorganized ventricular activation, E/A ratios, dippers and nondippers [4]. Abnormalities of SAECG were also mentioned in patients with chronic renal failure and in patients undergoing hemodialysis and peritoneal dialysis [4]. Roithinger et al. did not find a significant association between mortality and LVPs or structural myocardial changes in hemodialysis patients [19]. Girgis et al. concluded that SAECG s improve with hemodialysis, and, decreased left ventricular dimensions, because of fluid removal [20]. The present study is the first attempt, as far as we know, to correlate SAECG s and renal function in hypertensive patients. Despite the high prevalence of SAECG abnormalities in patients with LVH, the later was not a sensitive or specific predictor for LVPs or abnormal SAECGs in the present study. The explanation could be renal failure, and, GFR was significantly higher in patients without LVH compared to those with LVH (table 10). Table 10. Estimated glomerular filtration rate using (GFRMD), glomerular filtration rate calculated using the Salazar-Corcoran equation (GFRSC) and GFR calculated using the Cockroft Gault equation (GFRCG) are significantly higher in patients without left ventricular hypertrophy (LVH) compared to those with LVH. overcome some of the limitations of creatinine measurements [22]. The prevalence of late ventricular potentials was higher in the present study (43%) compared to previous results: 24.5% [23], 25% [24] and 21.6% [25] in the studies of Vardas, Palatini and Galinier et al, respectively. The differences may be related to the characteristics of the study population. Associated pathology could have influenced SAECGs. Coronary heart disease was present only in 8 patients in the current study, and the prevalence of LVPs is low (7-10%) in patients with coronary heart disease without myocardial infarction [4]. Congestive heart failure was the associated pathology in 4 patients, and the results regarding the predictive value of late ventricular potentials for ventricular arrhythmias in heart failure patients are conflicting [4]. Therapy may have influenced LVPs, especially beta blockers [23] and angiotensin converting enzyme inhibitors [24]. The role of SAECG as a screening test is limited due to the low positive predictive accuracy. But, due to its high negative predictive value, LVPs can play an important role in selecting patients for interventional studies [4]. 4. Conclusion An impaired renal function is significantly associated and predicts abnormal signal averaged electrocardiograms and late ventricular potentials in hypertensive patients. LVH No LVH p GFRMD 52±23 68± GFRCG 65±31 76± GFRSC 72±36 80± No connection between LVPs and LVH in renal failure was previously mentioned [21] Study limitations An important limitation of the present study is the sample size. The results should be confirmed in larger groups and follow-up studies. Serum creatinine was considered an unreliable marker of GRF because it is affected by tubular secretion, age, gender, muscle mass, physical activity, and diet [22]. The Cockcroft-Gault, the Modification of Diet in Renal Disease (MDRD) and Salazar-Corcoran equations were used, because they Figure 1. Late ventricular potentials in a hypertensive patient. References: [1] X1. Polak-Jonkisz D, Laszki-Szczachor K, Purzyc L et al. Usefulness of body surface potential ISBN:

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