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Cardiac Autonomic Balance in Children With Epilepsy: Value of Antiepileptic Drugs
Pediatric Neurology xxx (2015) 1e5
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Pediatric Neurology journal homepage: www.elsevier.com/locate/pnu
Original Article
Cardiac Autonomic Balance in Children With Epilepsy: Value of Antiepileptic Drugs Omnia Fathy El-Rashidy MD, Rania Hamed Shatla MD *, Omnya Ibrahim Youssef MD, Eman Samir MBBCh Department of Pediatrics, Faculty of Medicine, Ain Shams University, Cairo, Egypt
abstract BACKGROUND: Dysfunction of the autonomous nervous system causes arrhythmias and, although previous studies have investigated the effects of epilepsy on the autonomic control of the heart, there is still uncertainty about whether imbalance of sympathetic, vagal, or both systems occurs in epilepsy as well as the effect of anticonvulsants on the autonomic system. AIM: To evaluate cardiac autonomic status in children with epilepsy on antiepileptic drugs. PATIENTS AND METHODS: Sixty patients with epilepsy were recruited from the Outpatient Neurology Clinic at Ain Shams University and were divided into the following groups: group I, drug naive; and group II, patients with epilepsy on regular antiepileptic drugs. The second group was further subdivided into the following groups: group IIa, received monotherapy; and group IIb, received polytherapy. Forty age- and sex-matched healthy children served as controls. Included patients underwent videorecorded electroencephalograph, Holter electrocardiogram (EKG) for time and frequency domains of heart rate variability, and standard EKG recording for QTc, QTd. RESULTS: Mean values of all time domain, total power, and high-frequency power were significantly lower, whereas low-frequency and low-frequency/high-frequency power, QTc. and QTd were significantly higher in group I compared with group II and in patients compared with controls. No significant difference was found between patients on different antiepileptic drug regimens regarding heart rate variability values. A significant negative correlation was found between Chalfont severity score and 50% of difference between adjacent, normal RR intervals in patient groups. CONCLUSIONS: Children with epilepsy have cardiac autonomic dysfunction evident in their heart rate variability assessment. Patients on antiepileptic drugs had better autonomic balance than those not on antiepileptic drugs. Holter and EKG follow-up should be considered for early detection in those at high-risk cardiac complications. Keywords: epilepsy, heart rate variability, antiepileptic drugs, autonomic imbalance
Pediatr Neurol 2015; -: 1-5 Ó 2015 Elsevier Inc. All rights reserved.
Introduction
The electrical stimulation of various sites of the brain may cause cardiac rate and rhythm abnormalities. The most common types of cardiac autonomic dysfunction associated with seizures are tachyarrhythmia, bradyarrhythmia, and electrocardiogram (EKG) changes.1 Article History: Received October 10, 2014; Accepted in final form November 28, 2014 * Communications should be addressed to: Dr. Shatla; Associate Professor of Pediatrics; Ain Shams University; Cairo, Egypt 11566. E-mail address: [email protected] 0887-8994/$ - see front matter Ó 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.pediatrneurol.2014.11.018
Darbin et al.2 found that the severity of convulsive seizures and seizure repetition are determinants of disordered cardiac autonomic regulation and directly influence the duration of cardiac arrhythmia during the immediate postictal state. Dysfunction in systemic and cerebral circulation physiology and seizure-induced hormonal and metabolic changes might contribute to sudden unexpected death in patients with epilepsy (SUDEP).3 The effect of antiepileptic drugs (AEDs) on the heart might be unpredictable. AEDs might prevent SUDEP by improving seizure control. On the other hand, AEDs might potentially contribute to SUDEP if they are suddenly withdrawn or by exerting direct effects on cardiac control.4
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Carbamazepine and other AEDs can slow cardiac conduction.5 Lamotrigine has been shown to lengthen cardiac repolarization and the QT interval.6 Certain AEDs, such as carbamazepine, rufinamide, or primidone, may induce QT shortening.7,8 To detect the sympathetic-parasympathetic balance of the autonomic nervous system, measuring heart rate variability (HRV) is a useful noninvasive tool.9 It reflects the beat-to-beat alterations in the heart rate and is mainly modulated by parasympathetic and sympathetic activities.10 HRV is analyzed by time and or frequency domain methods; the former is derived from measuring and calculating the differences in the normal to normal RR intervals and the latter involves spectral analysis of normal to normal RR interval series.11 The aim of this study was to evaluate interictal cardiac autonomic status in children with epilepsy receiving AEDs.
marker of parasympathetic activity), low-frequency power (LF) values (ms2) (a measure of sympathetic activity), and the ratio between LF and HF (an index of the balance between sympathetic and parasympathetic influences).13 Analysis of Holter data for other variables describing cardiac changes and arrhythmias was done as premature atrial contractions and premature ventricular contractions, bigeminy, trigeminy, and any other dysrhythmias. A 12-lead EKG recording for P wave amplitude and duration, PR interval, QRS duration, QTc and QTd estimation, and QTc assessment were done according to Bazett’s formula: [QTc measured ¼ QT/squared root RR interval]. The upper limit of normal QTc was considered 0.44 seconds.14 Instructions were given to parents before recording and emphasized not missing drug doses, if received, and avoiding conditions that might induce stress and any caffeine containing beverages so as not to affect patients heart rate.
Patients and methods
Statistical analysis was carried out using SPSS, version 17.0 (SPSS Inc., Chicago, IL). The collected data were statistically managed as follows. Descriptive statistics were calculated as the mean standard deviation for quantitative variables; the number and % were used for qualitative variables. For analytic statistics, to assess the differences in frequency of qualitative variables, the chi-square test was used, whereas Fisher’s exact test was applied if any expected cell values in a two by two table was <5. To assess differences in means of quantitative variables between cases and controls, independent samples t test was applied. The relation between quantitative variables within the case group was analyzed using one-way analysis of variance test. Pearson’s correlation coefficient was used to correlate various quantitative variables within the case group. The statistical methods were verified, assuming a significance level of P < 0.05 and a highly significant level of P < 0.001.
This cross-sectional, case-controlled study was conducted in the Pediatric Neurology Clinic and Children’s Hospital, Ain Shams University, Cairo. Sixty patients with idiopathic epilepsy were enrolled in the study and were divided into two groups. Group I comprised drug-naive patients and group II comprised patients on regular AEDs; they were further subdivided into group IIa, which included patients receiving monotherapy (valproic acid or carbamazepine), and group IIb, which included patients receiving polytherapy. Studied groups were compared to 40 age- and sex-matched healthy children and adolescents as a control group. Patients with evidence of organic heart disease or other diseases or illnesses that might affect cardiovascular and autonomic nervous systems (e.g., systemic lupus erythematosus endocrine metabolic disorders) were excluded from the study. Also, any patients on any regular medication, other than AEDs, which could affect the cardiovascular and autonomic nervous systems were excluded. Consent was received from parents or caregivers after explaining the study requirements and details to them. The study was approved by the hospital’s ethical committee. The studied groups were subjected to the following. - A complete history, which placed stress on a detailed history of the patient’s epilepsy (age of onset, seizure type, type and severity of seizures rated according to the Chalfont seizure severity scale,12 details of drug therapy in terms of duration, dose, and preparations). - A thorough clinical examination with detailed neurological and cardiac examinations. - Twenty-four hour EKG (Holter) recording for time and frequency domains; HRV indices and dysrhythmia assessments were done using a Holter monitor (circadian, model number HR1 recorder) that recorded two channels of EKG into a standard 60-minute cassette tape for 24 hours. Parents of patients and controls kept notes of 24hour events. Holter tapes were analyzed using a Hyundai computer/ delux 145 with a HillMed inversion DFA 3.3). Time domain measures of HRV included the following: standard deviation of all normal RR intervals (SDNN, ms) in the entire 24-hour EKG recording; standard deviation of averaged normal sinus RR intervals for all 5-minute segments of entire recording (measured in ms); mean of standard deviations of all normal RR intervals for all 5-minute segments of the entire recording (measured in ms); root mean square of successive RR interval differences (the square root of the mean of the sum of the squares of differences between adjacent normal RR intervals over the entire recording, measured in ms), and the percentage of difference between adjacent normal RR intervals that are greater than 50 ms computed over the entire 24-hour EKG recording (pNN50, measured in percentage), according to Silvetti et al.13 Frequency domain measures of HRV included the following: Total power (TP) values (ms2); high-frequency power (HF) values (ms2) (a
Statistical analysis of data
Results
The patients included in our study (32 males and 28 females) had ages ranging from 4 to 12 years (median 8 years; mean 8.4 2.6 years). They were compared with 20 healthy controls (21 males and 19 females), with ages ranging from 4 to 13 years (median age 8.2 years; mean 8.6 2.8 years). Regarding EKG data, 22 patients (36.7 %) had premature atrial contractions, 15 (25.0%) had premature ventricular contractions, three (5.0 %) had one couplet, and one patient (1.7 %) had one triplet, six patients had prolonged QTc (more than 0.44 seconds) and five had prolonged QTd (more than TABLE 1. Distribution of Normal and Abnormal Holter Data of the Patients with Epilepsy Group
Patients (n ¼ 60)
Variables
PACs PVCs Couplets Triplets
Absent Present Absent Present Absent Present Absent Present
Abbreviations: PACs ¼ Premature atrial contractions PVCs ¼ Premature ventricular contractions
No.
%
38 22 45 15 57 3 59 1
63.3 36.7 75.0 25.0 95.0 5.0 98.3 1.7
O.F. El-Rashidy et al. / Pediatric Neurology xxx (2015) 1e5 TABLE 2. Comparison Between Patients and Controls Regarding Mean Values of QTc and QTd
Variable
Patients
Controls
t
P Value
QTc (seconds) QTd (ms)
0.43 0.02 47.4 2.5
0.40 0.02 45.4 1.7
6.5 4.5
<0.001 <0.001
50 ms) (Table 1). Also, the mean values of QTc and QTd were significantly elevated in patients compared with the control group (Table 2). The mean values of all time domain measures (SDNN, standard deviation of averaged normal sinus RR intervals for all 5-minute segments of the entire recording, mean of standard deviations of all normal RR intervals, pNN50, and root mean square of successive RR intervals difference) and frequency domain measures of HRV (TP and HF) were significantly lower, whereas the mean values of (LF and LF/ HF) were significantly higher in patients compared with the control group (Table 3). When we compared the mean values of both time and frequency domain measures of HRV among patients on different AED regimens, results showed no significant difference (Table 4). The Chalfont seizure severity score showed a significant negative correlation with pNN50. A nonsignificant correlation was observed between duration of illness and both time and frequency domain measures of HRV, with the exception of LH/HF ratio, which showed a statistically significant negative correlation with duration of illness (r ¼ 0.39, P ¼ 0.019). Discussion
Analysis of heart rate variability is prominent among modern methodological approaches for assessing the state of the cardiovascular system and the body as a whole.15 Heart rate variability reflects the complex interplay of sympathetic and parasympathetic innervations of the, and a reduced HRV has been shown to be a predictor of mortality and susceptibility to cardiac arrhythmias.16 TABLE 3. Comparison Between Patients and Controls Regarding Mean Values of Time and Frequency Domains of HRV
Patients HRV Time domain SDNN (ms) 79.5 SDANN (ms) 67.3 SDNNI (ms) 47.7 pNN50 (%) 7.5 rMSSD (ms) 11.1 HRV frequency domain TP (ms2) 2320.7 LF (ms2) 966.2 HF (ms2) 600.4 LF/HF 1.71
Controls
8.7 5.6 5.7 1.5 1.9
139.3 29.1 25.6 0.09
t
P Value
140.0 120.1 86.8 14.1 27.9
11.6 6.7 3.1 1.2 5.1
29.8 42.7 39.7 23.3 23.3
<0.001 <0.001 <0.001 <0.001 <0.001
4406.9 910.8 780.8 1.16
63.6 20.2 7.7 0.02
88.6 10.6 43.2 35.0
<0.001 <0.001 <0.001 <0.001
Abbreviations: HRV ¼ Heart rate variability SDANN ¼ Standard deviation of averaged normal sinus RR intervals SDNN ¼ Standard deviation of all normal RR intervals SDNNI ¼ Mean of standard deviations of all normal RR intervals pNN50 ¼ Percentage of difference between adjacent normal RR intervals rMSSD ¼ Root mean square of successive RR intervals TP ¼ Total power
3
TABLE 4. Comparison Between Patients on Different AED Regimens Regarding HRV Time and Frequency Domain Measures
AED Regimen HRV time domain SDNN (ms) No AEDs Monotherapy Polytherapy SDANN (ms) No AEDs Monotherapy Polytherapy SDNNI (ms) No AEDs Monotherapy Polytherapy pNN50 (%) No AEDs Monotherapy Polytherapy rMSSD (ms) No AEDs Monotherapy Polytherapy HRV frequency domain TP (ms2) No AEDs Monotherapy Polytherapy LF (ms2) No AEDs Monotherapy Polytherapy HF (ms2) No AEDs Monotherapy Polytherapy LF/HF No AEDs Monotherapy Polytherapy
Mean SD
F
P Value
79.4 8.9 77.0 10.8 82.4 3.5
1.5
0.236
66.0 5.7 67.3 5.9 70.0 4.3
2.5
0.091
46.7 6.0 47.1 4.9 50.7 5.1
2.7
0.076
7.2 1.6 7.5 1.6 7.9 1.1
0.8
0.446
11.4 2.0 10.6 1.8 10.9 1.8
0.9
0.414
2305.8 125.1 2346.1 142.4 2323.6 168.6
0.4
0.651
973.9 28.5 958.9 33.8 958.1 20.9
2.2
0.124
598.9 22.1 600.8 26.9 602.9 32.2
0.1
0.981
1.74 0.01 1.66 0.11 1.70 0.07
2.9
0.531
Abbreviations: AEDs ¼ Antiepileptic drugs HF ¼ High frequency HRV ¼ Heart rate variability LF ¼ Low frequency pNN50 ¼ Percentage of difference between adjacent normal RR intervals SD ¼ Standard deviation SDNN ¼ Standard deviation of all normal RR intervals SDNNI ¼ Mean of standard deviations of all normal RR intervals TP ¼ Total power
Our study documented a significant reduction in the mean values of time domain measures of HRV in patients compared with controls. This finding reinforced the results reported in previous studies.17-21 This reduction in heart rate variability in patients with epilepsy might reflect an imbalance between sympathetic and parasympathetic cardiac controls, with the suggestion of a decrease in parasympathetic tone and/or an increase in sympathetic tone.22 Brain control of cardiac function is well-recognized, and acute neurological events, including epileptic seizures, may disturb cardiac function even in the absence of significant cardiac structural or electrophysiological abnormalities.23 This is particularly crucial because autonomic cardiac
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arrhythmias may contribute significantly to the SUDEP phenomenon. On the other hand, Evrengul et al.24 analyzed time domain measures and reported higher SDNN and SDANN values in patients than in controls; they further suggested that an increase in the sympathetic control of the heart rate could play a key role in development of ventricular tachyarrhythmias. Regarding frequency domain measures of HRV, a significant reduction in the mean values of TP and HF and increase in the mean values of LF and LF/HF were observed in patients compared with controls. Similar results were reported by Lotufo et al.,25 Ferri et al.,26 Hallioglu et al.,19 and Evrengul et al.,24 suggesting higher sympathetic and lower parasympathetic regulation of autonomic cardiac activity among patients with chronic epilepsy. Whether autonomic dysfunction resulted from epilepsy or anticonvulsive drugs needs to be further elucidated. Most of the results from previous studies have been conflicting,27-29 and only few studies have examined the effects of epilepsy and AEDs on HRV parameters separately. Persson et al.29 reported that both sympathetic and parasympathetic activities were found to be suppressed after carbamazepine therapy. Hallioglu et al.19 and Ansakorpi et al.21 suggested that interictal autonomic dysfunction could be improved after achieving clinical improvement with the help of AEDs. Moreover, if AEDs are stopped abruptly, suppressed HRV and increased sympathetic activity will develop dramatically.4 Additionally, autonomic dysfunction was found to be more frequent in refractory epilepsy in patients.30,31 In our study, the mean values of HRV parameters in drugnaive patients were almost similar to those on mono- and polytherapy; this is in contrast to Lotufo et al.25 However, after dividing our patients into subgroups, our sample size became too small and we were unable to find any statistically significant differences among subgroups except for LF/ HF values. In patients with long-lasting epilepsy and multiple seizures, there are now convincing arguments for a chronic dysfunction of the autonomic nervous system.32,33 Our work echoes similar findings of a significant negative correlation between a Chalfont seizure severity score of pNN50 and a significant negative correlation of LH/HF with duration of illness. Several studies aimed at identifying risk stratification of SUDEP have raised the possibility of a relatively prolonged QTc.34,35 Several potential mechanisms of prolonged QTc during seizures have been discussed, including: hypercapnia,36 hypoxia,37 release of catecholamines,38 and cerebral dysregulation with involvement of the insular cortex.39 Our work showed significantly prolonged mean values of QTc and QTd in patients with epilepsy than in the control group; however, none had abnormal shortening. In agreement with Kandler et al.40 and Drake et al.,35 Tavernor et al.41 noted a statistically significant QTc lengthening in patients who later suffered from SUDEP compared with controls. Schimpf et al.42 reported significant QTc shortening among patients with epilepsy on monotherapy with rufinamide; however, the clinical importance of abnormal ictal QT shortening is currently unclear and the authors suggested a substantial disturbance of autonomic function that might be involved in the pathophysiology of SUDEP.
Surges et al.44 reported abnormal transient shortening of QTc with medically refractory epilepsy. Kwon et al.43 assessed drug-induced QT prolongation to determine if the use of AEDs contributed to SUDEP in patients with epilepsy. They found that the mean values of QTc showed no significant difference between patients and controls and that there was no significant difference between the mono- group and polytherapy group, which is in agreement with our nonsignificant results. The spectrum of EKG changes during epileptic activity is extensive. In our study, there was no consistent pattern of EKG changes in individual patients. Twenty-two patients had premature atrial contractions, 15 showed premature ventricular contractions, three showed couplets, and one showed triplets. Many other researchers reported different EKG abnormalities; O’Regan and Brown,45 Opherk et al.,46 and Tigaran et al.47 reported ST depression in children and ST elevation was noted by O’Regan and Brown45 and Nei et al.48 Another study, however, did not document interictal EKG abnormality in patients with epilepsy.49 In conclusion, our results confirm a substantial degree of autonomic dysfunction among patients with epilepsy and argue for a potential role of the epileptic disorder rather than AEDs on this autonomic imbalance. On behalf of the authors, I confirm that this article received no grants or funding.
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Contents lists available at ScienceDirect
Pediatric Neurology journal homepage: www.elsevier.com/locate/pnu
Original Article
Cardiac Autonomic Balance in Children With Epilepsy: Value of Antiepileptic Drugs Omnia Fathy El-Rashidy MD, Rania Hamed Shatla MD *, Omnya Ibrahim Youssef MD, Eman Samir MBBCh Department of Pediatrics, Faculty of Medicine, Ain Shams University, Cairo, Egypt
abstract BACKGROUND: Dysfunction of the autonomous nervous system causes arrhythmias and, although previous studies have investigated the effects of epilepsy on the autonomic control of the heart, there is still uncertainty about whether imbalance of sympathetic, vagal, or both systems occurs in epilepsy as well as the effect of anticonvulsants on the autonomic system. AIM: To evaluate cardiac autonomic status in children with epilepsy on antiepileptic drugs. PATIENTS AND METHODS: Sixty patients with epilepsy were recruited from the Outpatient Neurology Clinic at Ain Shams University and were divided into the following groups: group I, drug naive; and group II, patients with epilepsy on regular antiepileptic drugs. The second group was further subdivided into the following groups: group IIa, received monotherapy; and group IIb, received polytherapy. Forty age- and sex-matched healthy children served as controls. Included patients underwent videorecorded electroencephalograph, Holter electrocardiogram (EKG) for time and frequency domains of heart rate variability, and standard EKG recording for QTc, QTd. RESULTS: Mean values of all time domain, total power, and high-frequency power were significantly lower, whereas low-frequency and low-frequency/high-frequency power, QTc. and QTd were significantly higher in group I compared with group II and in patients compared with controls. No significant difference was found between patients on different antiepileptic drug regimens regarding heart rate variability values. A significant negative correlation was found between Chalfont severity score and 50% of difference between adjacent, normal RR intervals in patient groups. CONCLUSIONS: Children with epilepsy have cardiac autonomic dysfunction evident in their heart rate variability assessment. Patients on antiepileptic drugs had better autonomic balance than those not on antiepileptic drugs. Holter and EKG follow-up should be considered for early detection in those at high-risk cardiac complications. Keywords: epilepsy, heart rate variability, antiepileptic drugs, autonomic imbalance
Pediatr Neurol 2015; -: 1-5 Ó 2015 Elsevier Inc. All rights reserved.
Introduction
The electrical stimulation of various sites of the brain may cause cardiac rate and rhythm abnormalities. The most common types of cardiac autonomic dysfunction associated with seizures are tachyarrhythmia, bradyarrhythmia, and electrocardiogram (EKG) changes.1 Article History: Received October 10, 2014; Accepted in final form November 28, 2014 * Communications should be addressed to: Dr. Shatla; Associate Professor of Pediatrics; Ain Shams University; Cairo, Egypt 11566. E-mail address: [email protected] 0887-8994/$ - see front matter Ó 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.pediatrneurol.2014.11.018
Darbin et al.2 found that the severity of convulsive seizures and seizure repetition are determinants of disordered cardiac autonomic regulation and directly influence the duration of cardiac arrhythmia during the immediate postictal state. Dysfunction in systemic and cerebral circulation physiology and seizure-induced hormonal and metabolic changes might contribute to sudden unexpected death in patients with epilepsy (SUDEP).3 The effect of antiepileptic drugs (AEDs) on the heart might be unpredictable. AEDs might prevent SUDEP by improving seizure control. On the other hand, AEDs might potentially contribute to SUDEP if they are suddenly withdrawn or by exerting direct effects on cardiac control.4
2
O.F. El-Rashidy et al. / Pediatric Neurology xxx (2015) 1e5
Carbamazepine and other AEDs can slow cardiac conduction.5 Lamotrigine has been shown to lengthen cardiac repolarization and the QT interval.6 Certain AEDs, such as carbamazepine, rufinamide, or primidone, may induce QT shortening.7,8 To detect the sympathetic-parasympathetic balance of the autonomic nervous system, measuring heart rate variability (HRV) is a useful noninvasive tool.9 It reflects the beat-to-beat alterations in the heart rate and is mainly modulated by parasympathetic and sympathetic activities.10 HRV is analyzed by time and or frequency domain methods; the former is derived from measuring and calculating the differences in the normal to normal RR intervals and the latter involves spectral analysis of normal to normal RR interval series.11 The aim of this study was to evaluate interictal cardiac autonomic status in children with epilepsy receiving AEDs.
marker of parasympathetic activity), low-frequency power (LF) values (ms2) (a measure of sympathetic activity), and the ratio between LF and HF (an index of the balance between sympathetic and parasympathetic influences).13 Analysis of Holter data for other variables describing cardiac changes and arrhythmias was done as premature atrial contractions and premature ventricular contractions, bigeminy, trigeminy, and any other dysrhythmias. A 12-lead EKG recording for P wave amplitude and duration, PR interval, QRS duration, QTc and QTd estimation, and QTc assessment were done according to Bazett’s formula: [QTc measured ¼ QT/squared root RR interval]. The upper limit of normal QTc was considered 0.44 seconds.14 Instructions were given to parents before recording and emphasized not missing drug doses, if received, and avoiding conditions that might induce stress and any caffeine containing beverages so as not to affect patients heart rate.
Patients and methods
Statistical analysis was carried out using SPSS, version 17.0 (SPSS Inc., Chicago, IL). The collected data were statistically managed as follows. Descriptive statistics were calculated as the mean standard deviation for quantitative variables; the number and % were used for qualitative variables. For analytic statistics, to assess the differences in frequency of qualitative variables, the chi-square test was used, whereas Fisher’s exact test was applied if any expected cell values in a two by two table was <5. To assess differences in means of quantitative variables between cases and controls, independent samples t test was applied. The relation between quantitative variables within the case group was analyzed using one-way analysis of variance test. Pearson’s correlation coefficient was used to correlate various quantitative variables within the case group. The statistical methods were verified, assuming a significance level of P < 0.05 and a highly significant level of P < 0.001.
This cross-sectional, case-controlled study was conducted in the Pediatric Neurology Clinic and Children’s Hospital, Ain Shams University, Cairo. Sixty patients with idiopathic epilepsy were enrolled in the study and were divided into two groups. Group I comprised drug-naive patients and group II comprised patients on regular AEDs; they were further subdivided into group IIa, which included patients receiving monotherapy (valproic acid or carbamazepine), and group IIb, which included patients receiving polytherapy. Studied groups were compared to 40 age- and sex-matched healthy children and adolescents as a control group. Patients with evidence of organic heart disease or other diseases or illnesses that might affect cardiovascular and autonomic nervous systems (e.g., systemic lupus erythematosus endocrine metabolic disorders) were excluded from the study. Also, any patients on any regular medication, other than AEDs, which could affect the cardiovascular and autonomic nervous systems were excluded. Consent was received from parents or caregivers after explaining the study requirements and details to them. The study was approved by the hospital’s ethical committee. The studied groups were subjected to the following. - A complete history, which placed stress on a detailed history of the patient’s epilepsy (age of onset, seizure type, type and severity of seizures rated according to the Chalfont seizure severity scale,12 details of drug therapy in terms of duration, dose, and preparations). - A thorough clinical examination with detailed neurological and cardiac examinations. - Twenty-four hour EKG (Holter) recording for time and frequency domains; HRV indices and dysrhythmia assessments were done using a Holter monitor (circadian, model number HR1 recorder) that recorded two channels of EKG into a standard 60-minute cassette tape for 24 hours. Parents of patients and controls kept notes of 24hour events. Holter tapes were analyzed using a Hyundai computer/ delux 145 with a HillMed inversion DFA 3.3). Time domain measures of HRV included the following: standard deviation of all normal RR intervals (SDNN, ms) in the entire 24-hour EKG recording; standard deviation of averaged normal sinus RR intervals for all 5-minute segments of entire recording (measured in ms); mean of standard deviations of all normal RR intervals for all 5-minute segments of the entire recording (measured in ms); root mean square of successive RR interval differences (the square root of the mean of the sum of the squares of differences between adjacent normal RR intervals over the entire recording, measured in ms), and the percentage of difference between adjacent normal RR intervals that are greater than 50 ms computed over the entire 24-hour EKG recording (pNN50, measured in percentage), according to Silvetti et al.13 Frequency domain measures of HRV included the following: Total power (TP) values (ms2); high-frequency power (HF) values (ms2) (a
Statistical analysis of data
Results
The patients included in our study (32 males and 28 females) had ages ranging from 4 to 12 years (median 8 years; mean 8.4 2.6 years). They were compared with 20 healthy controls (21 males and 19 females), with ages ranging from 4 to 13 years (median age 8.2 years; mean 8.6 2.8 years). Regarding EKG data, 22 patients (36.7 %) had premature atrial contractions, 15 (25.0%) had premature ventricular contractions, three (5.0 %) had one couplet, and one patient (1.7 %) had one triplet, six patients had prolonged QTc (more than 0.44 seconds) and five had prolonged QTd (more than TABLE 1. Distribution of Normal and Abnormal Holter Data of the Patients with Epilepsy Group
Patients (n ¼ 60)
Variables
PACs PVCs Couplets Triplets
Absent Present Absent Present Absent Present Absent Present
Abbreviations: PACs ¼ Premature atrial contractions PVCs ¼ Premature ventricular contractions
No.
%
38 22 45 15 57 3 59 1
63.3 36.7 75.0 25.0 95.0 5.0 98.3 1.7
O.F. El-Rashidy et al. / Pediatric Neurology xxx (2015) 1e5 TABLE 2. Comparison Between Patients and Controls Regarding Mean Values of QTc and QTd
Variable
Patients
Controls
t
P Value
QTc (seconds) QTd (ms)
0.43 0.02 47.4 2.5
0.40 0.02 45.4 1.7
6.5 4.5
<0.001 <0.001
50 ms) (Table 1). Also, the mean values of QTc and QTd were significantly elevated in patients compared with the control group (Table 2). The mean values of all time domain measures (SDNN, standard deviation of averaged normal sinus RR intervals for all 5-minute segments of the entire recording, mean of standard deviations of all normal RR intervals, pNN50, and root mean square of successive RR intervals difference) and frequency domain measures of HRV (TP and HF) were significantly lower, whereas the mean values of (LF and LF/ HF) were significantly higher in patients compared with the control group (Table 3). When we compared the mean values of both time and frequency domain measures of HRV among patients on different AED regimens, results showed no significant difference (Table 4). The Chalfont seizure severity score showed a significant negative correlation with pNN50. A nonsignificant correlation was observed between duration of illness and both time and frequency domain measures of HRV, with the exception of LH/HF ratio, which showed a statistically significant negative correlation with duration of illness (r ¼ 0.39, P ¼ 0.019). Discussion
Analysis of heart rate variability is prominent among modern methodological approaches for assessing the state of the cardiovascular system and the body as a whole.15 Heart rate variability reflects the complex interplay of sympathetic and parasympathetic innervations of the, and a reduced HRV has been shown to be a predictor of mortality and susceptibility to cardiac arrhythmias.16 TABLE 3. Comparison Between Patients and Controls Regarding Mean Values of Time and Frequency Domains of HRV
Patients HRV Time domain SDNN (ms) 79.5 SDANN (ms) 67.3 SDNNI (ms) 47.7 pNN50 (%) 7.5 rMSSD (ms) 11.1 HRV frequency domain TP (ms2) 2320.7 LF (ms2) 966.2 HF (ms2) 600.4 LF/HF 1.71
Controls
8.7 5.6 5.7 1.5 1.9
139.3 29.1 25.6 0.09
t
P Value
140.0 120.1 86.8 14.1 27.9
11.6 6.7 3.1 1.2 5.1
29.8 42.7 39.7 23.3 23.3
<0.001 <0.001 <0.001 <0.001 <0.001
4406.9 910.8 780.8 1.16
63.6 20.2 7.7 0.02
88.6 10.6 43.2 35.0
<0.001 <0.001 <0.001 <0.001
Abbreviations: HRV ¼ Heart rate variability SDANN ¼ Standard deviation of averaged normal sinus RR intervals SDNN ¼ Standard deviation of all normal RR intervals SDNNI ¼ Mean of standard deviations of all normal RR intervals pNN50 ¼ Percentage of difference between adjacent normal RR intervals rMSSD ¼ Root mean square of successive RR intervals TP ¼ Total power
3
TABLE 4. Comparison Between Patients on Different AED Regimens Regarding HRV Time and Frequency Domain Measures
AED Regimen HRV time domain SDNN (ms) No AEDs Monotherapy Polytherapy SDANN (ms) No AEDs Monotherapy Polytherapy SDNNI (ms) No AEDs Monotherapy Polytherapy pNN50 (%) No AEDs Monotherapy Polytherapy rMSSD (ms) No AEDs Monotherapy Polytherapy HRV frequency domain TP (ms2) No AEDs Monotherapy Polytherapy LF (ms2) No AEDs Monotherapy Polytherapy HF (ms2) No AEDs Monotherapy Polytherapy LF/HF No AEDs Monotherapy Polytherapy
Mean SD
F
P Value
79.4 8.9 77.0 10.8 82.4 3.5
1.5
0.236
66.0 5.7 67.3 5.9 70.0 4.3
2.5
0.091
46.7 6.0 47.1 4.9 50.7 5.1
2.7
0.076
7.2 1.6 7.5 1.6 7.9 1.1
0.8
0.446
11.4 2.0 10.6 1.8 10.9 1.8
0.9
0.414
2305.8 125.1 2346.1 142.4 2323.6 168.6
0.4
0.651
973.9 28.5 958.9 33.8 958.1 20.9
2.2
0.124
598.9 22.1 600.8 26.9 602.9 32.2
0.1
0.981
1.74 0.01 1.66 0.11 1.70 0.07
2.9
0.531
Abbreviations: AEDs ¼ Antiepileptic drugs HF ¼ High frequency HRV ¼ Heart rate variability LF ¼ Low frequency pNN50 ¼ Percentage of difference between adjacent normal RR intervals SD ¼ Standard deviation SDNN ¼ Standard deviation of all normal RR intervals SDNNI ¼ Mean of standard deviations of all normal RR intervals TP ¼ Total power
Our study documented a significant reduction in the mean values of time domain measures of HRV in patients compared with controls. This finding reinforced the results reported in previous studies.17-21 This reduction in heart rate variability in patients with epilepsy might reflect an imbalance between sympathetic and parasympathetic cardiac controls, with the suggestion of a decrease in parasympathetic tone and/or an increase in sympathetic tone.22 Brain control of cardiac function is well-recognized, and acute neurological events, including epileptic seizures, may disturb cardiac function even in the absence of significant cardiac structural or electrophysiological abnormalities.23 This is particularly crucial because autonomic cardiac
4
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arrhythmias may contribute significantly to the SUDEP phenomenon. On the other hand, Evrengul et al.24 analyzed time domain measures and reported higher SDNN and SDANN values in patients than in controls; they further suggested that an increase in the sympathetic control of the heart rate could play a key role in development of ventricular tachyarrhythmias. Regarding frequency domain measures of HRV, a significant reduction in the mean values of TP and HF and increase in the mean values of LF and LF/HF were observed in patients compared with controls. Similar results were reported by Lotufo et al.,25 Ferri et al.,26 Hallioglu et al.,19 and Evrengul et al.,24 suggesting higher sympathetic and lower parasympathetic regulation of autonomic cardiac activity among patients with chronic epilepsy. Whether autonomic dysfunction resulted from epilepsy or anticonvulsive drugs needs to be further elucidated. Most of the results from previous studies have been conflicting,27-29 and only few studies have examined the effects of epilepsy and AEDs on HRV parameters separately. Persson et al.29 reported that both sympathetic and parasympathetic activities were found to be suppressed after carbamazepine therapy. Hallioglu et al.19 and Ansakorpi et al.21 suggested that interictal autonomic dysfunction could be improved after achieving clinical improvement with the help of AEDs. Moreover, if AEDs are stopped abruptly, suppressed HRV and increased sympathetic activity will develop dramatically.4 Additionally, autonomic dysfunction was found to be more frequent in refractory epilepsy in patients.30,31 In our study, the mean values of HRV parameters in drugnaive patients were almost similar to those on mono- and polytherapy; this is in contrast to Lotufo et al.25 However, after dividing our patients into subgroups, our sample size became too small and we were unable to find any statistically significant differences among subgroups except for LF/ HF values. In patients with long-lasting epilepsy and multiple seizures, there are now convincing arguments for a chronic dysfunction of the autonomic nervous system.32,33 Our work echoes similar findings of a significant negative correlation between a Chalfont seizure severity score of pNN50 and a significant negative correlation of LH/HF with duration of illness. Several studies aimed at identifying risk stratification of SUDEP have raised the possibility of a relatively prolonged QTc.34,35 Several potential mechanisms of prolonged QTc during seizures have been discussed, including: hypercapnia,36 hypoxia,37 release of catecholamines,38 and cerebral dysregulation with involvement of the insular cortex.39 Our work showed significantly prolonged mean values of QTc and QTd in patients with epilepsy than in the control group; however, none had abnormal shortening. In agreement with Kandler et al.40 and Drake et al.,35 Tavernor et al.41 noted a statistically significant QTc lengthening in patients who later suffered from SUDEP compared with controls. Schimpf et al.42 reported significant QTc shortening among patients with epilepsy on monotherapy with rufinamide; however, the clinical importance of abnormal ictal QT shortening is currently unclear and the authors suggested a substantial disturbance of autonomic function that might be involved in the pathophysiology of SUDEP.
Surges et al.44 reported abnormal transient shortening of QTc with medically refractory epilepsy. Kwon et al.43 assessed drug-induced QT prolongation to determine if the use of AEDs contributed to SUDEP in patients with epilepsy. They found that the mean values of QTc showed no significant difference between patients and controls and that there was no significant difference between the mono- group and polytherapy group, which is in agreement with our nonsignificant results. The spectrum of EKG changes during epileptic activity is extensive. In our study, there was no consistent pattern of EKG changes in individual patients. Twenty-two patients had premature atrial contractions, 15 showed premature ventricular contractions, three showed couplets, and one showed triplets. Many other researchers reported different EKG abnormalities; O’Regan and Brown,45 Opherk et al.,46 and Tigaran et al.47 reported ST depression in children and ST elevation was noted by O’Regan and Brown45 and Nei et al.48 Another study, however, did not document interictal EKG abnormality in patients with epilepsy.49 In conclusion, our results confirm a substantial degree of autonomic dysfunction among patients with epilepsy and argue for a potential role of the epileptic disorder rather than AEDs on this autonomic imbalance. On behalf of the authors, I confirm that this article received no grants or funding.
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