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Interictal autonomic abnormalities in idiopathic Rolandic Epilepsy
Epilepsy & Behavior 24 (2012) 241–245
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Interictal autonomic abnormalities in idiopathic Rolandic Epilepsy Stefano Seri a, e,⁎, Giorgio Di Lorenzo b, Tiziana Pisano a, c, Mariangela Pinci d, Daniela Brazzo a, Heather Betteridge e, Antonella Cerquiglini f a
Aston Brain Centre, School of Life and Health Sciences, Aston University, Birmingham, UK Psychophysiology Laboratory, Psychiatry Unit, Department of Neuroscience, University “Tor Vergata”, Rome, Italy Child Neurology Unit, Pediatric Hospital “A. Meyer”, Florence, Italy d Developmental Neuropsychiatry Unit, Department of Neuroscience, University “Tor Vergata”, Rome, Italy e Department of Clinical Neurophysiology, The Birmingham Children's Hospital NHS Foundation Trust, Birmingham, UK f Dipartimento di Scienze e Biotecnologie Medico-Chirurgiche, “Sapienza” Universita' di Roma, Polo Pontino, Italy b c
a r t i c l e
i n f o
Article history: Received 21 February 2012 Revised 12 March 2012 Accepted 13 March 2012 Available online 3 May 2012 Keywords: Heart rate variability Childhood Rolandic Epilepsy Autonomic nervous system Sympathovagal balance
a b s t r a c t We investigated 50 young patients with a diagnosis of Rolandic Epilepsy (RE) for the presence of abnormalities in autonomic tone compared with 50 young patients with idiopathic generalized epilepsy with absences and 50 typically developing children of comparable age. We analyzed time domain (N–N interval, pNN50) and frequency domain (High Frequency (HF), Low Frequency (LF) and LF/HF ratio) indices from tenminute resting EKG activity. Patients with RE showed significantly higher HF and lower LF power and lower LF/HF ratio than controls, independent of the epilepsy group, and did not show significant differences in any other autonomic index with respect to the two control groups. In RE, we found a negative relationship between both seizure load and frequency of sleep interictal EEG abnormalities with parasympathetic drive levels. These changes might be the expression of adaptive mechanisms to prevent the excessive sympathetic drive seen in patients with refractory epilepsies. © 2012 Elsevier Inc. All rights reserved.
1. Introduction Ictal and interictal abnormalities in autonomic control of cardiac frequency have been reported in patients with focal and generalized epilepsies [1–3]; cardiac arrhythmias, as well as changes in blood pressure and cardiac frequency, are observed in temporal relationship with most complex partial and generalized tonic-clonic seizures, independently of other clinical signs. These changes have been considered the expression of an imbalance between vagal and sympathetic activity [4]. Ictal autonomic changes have been implicated in the pathogenesis of sudden unexplained death in young persons with epilepsy [5]. Patients with temporal lobe epilepsy have a higher prevalence of cardiac arrhythmias compared to other localizations of epileptic paroxysmal activity [6,7], with tachycardia being more frequently reported than bradycardia [8,9]. Whether this is related to a specific effect of interictal and ictal discharges in this region or, rather, to a greater frequency of epileptic foci in the temporal lobe, is still unclear [10]. Bradycardia and reduced parasympathetic drive have been reported in patients with frontal lobe epilepsy [11]. Pediatric data are sparse, particularly in children with idiopathic focal epilepsies [12,13]. To further elucidate the complex relationship between seizures, interictal EEG abnormalities, and autonomic regulation in idiopathic epilepsies, we ⁎ Corresponding author at: Room SW 613, Aston University, Aston Triangle, Birmingham, B4 7ET, UK. Fax: +44 121 2044048. E-mail address: [email protected] (S. Seri). 1525-5050/$ – see front matter © 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.yebeh.2012.03.017
analyzed time and frequency domain autonomic measures in young patients with Rolandic Epilepsy (RE). To evaluate the specificity of these findings, we compared data from the RE group with data from a group of patients of comparable age with idiopathic generalized epilepsy with absences as well as from a group of typically developing children without epilepsy.
2. Methods Fifty young patients with RE were recruited from the outpatient population of the pediatric epilepsy programs of the Birmingham Children's Hospital and of the University “Tor Vergata” in Rome. As controls, we investigated a group of 50 children with childhood absence epilepsy (AE) and 50 typically developing children of comparable age and gender mix selected from a large cohort recruited from school-age children in the city of Rome as part of a separate project aimed to obtain normative electrophysiological measures across development. Exclusion criteria were the presence of sensory deficits, history of asthma and heart disease, previous treatment with carbamazepine/oxcarbazepine, lamotrigine and phenytoin, current antiepileptic treatment and/or seizures in the 6 months prior to the recording session. Children who had taken other systemic medications in the month before the recording were also excluded. All participants were instructed to avoid caffeine-based drinks for the 24 hours before the recording.
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In the epilepsy groups, seizure types and syndromic diagnoses were classified according to the International Classification of Seizures and Epilepsy Syndromes [14]. Seizure load for the RE group was ranked as ≤10 or >10 with the cut-off chosen in agreement with recent literature [15]. To investigate the role of severity of interictal EEG abnormalities in the RE group, we retrospectively analyzed data from polygraphic sleep EEG recordings for each patient and calculated the spike-wave index (SWI), defined as total minutes occupied by spike-wave discharges in NREM sleep multiplied by 100 and divided by the total minutes of NREM sleep without interictal EEG discharges, and ranked the variable as ≤50% or >50% in line with recent literature [16,17]. Patients were allocated to the latter of the two groups if at least one sleep EEG recording met the quantitative criterion. The main characteristics of the sample are summarized in Table 1. Parents and young patients consented in writing to the study before the recording. The study received approval by the Local Ethics Committee of the two institutions and was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki. 2.1. Measurement and equipment Electrocardiogram data were recorded as part of a polygraphic EEG study in which brain electrical activity was acquired from 19 electrode positions according to the international 10–20 System [18], using a digital EEG apparatus (Micromed System Plus, Treviso, Italy). One channel acquired cardiac activity from a location corresponding to the V1 EKG position. A further channel recorded chest respiratory effort. Signal was A/D converted at 512 Hz, 24-bit resolution, and stored on digital media for further analysis. Patients and controls were allowed to familiarize with the recording room and with the procedure, and were asked to remain in a supine position for 15 min before the beginning of the recording. The EEG was recorded in a sound-attenuated dimly lit room to facilitate an adequate psychophysical relaxation, using pre-wired electrode caps. Participants were instructed and if necessary, reminded to maintain a respiratory rate of 12 cycles/min. After a ten-minute period of adjustment, we acquired a ten-minute block of polygraphic signal in eyes open and closed conditions that was used for the analysis. The recording lasted approximately 60 min. 2.2. Signal processing and frequency domain analysis Signals were digitally band-pass filtered between 0.53 and 100 Hz. The EKG trace was first exported in EDF format; each QRS complex was then identified using the matching template algorithm available in the NPXLab EEG analysis and visualization software [19]. The Table 1 Main clinical characteristics.
Gender Females Males Age Mean SD Seizure load ≤10 >10 SWI ≤50% >50% AED treatment Yes No
RE
AE
CON
25 25
23 27
24 26
9.27 0.89
9.61 1.14
9.53 0.61
34 16
n.a. n.a.
n.a. n.a.
34 16
n.a. n.a.
n.a. n.a.
21 29
50 0
n.a. n.a.
SWI: spike-wave index, AED: antiepileptic drug; n.a.: not applicable.
time series of the intervals between consecutive R waves was saved in a text file and subject to time and frequency domain analyses using the Software for Advanced HRV analysis [20]. We chose a tenminute analysis time as the best compromise between reliability of the autonomic measures and the need for stationarity imposed by the specific recording setting. According to recent guidelines [21], the following autonomic indices were computed: Time domain: A) N–N (normal to normal) interval: a recommended index of cardio-vagal function; B) pNN50: the number of interval differences of successive N– N intervals greater than 50 ms divided by the total number of N–N intervals. This measure is considered to reflect parasympathetic activity [21]. Frequency domain A) High Frequency (HF): power in the frequency range between 0.15 and 0.4 Hz, considered as a marker for parasympathetic activity [22]; B) Low Frequency (LF): power in the frequency range between 0.04 and 0.15 Hz, a marker of sympathetic modulation [23]. Power spectral density (PSD) estimates where normalized by dividing the raw value by the total spectral power minus that of the specific component. The ratio between LF and HF was also computed. To reduce the effect of the variability in total power, we analyzed the LF and HF in normalized units. Given the relatively short duration of the recording, we chose not to analyze the Very Low Frequency (VLF) component between 0.003 and 0.04 Hz, as it can be of limited reliability under our experimental conditions. 2.3. Statistical method 2.3.1. Sample size calculation Since our primary endpoint was to detect differences between patients with epilepsy and controls and the LF/HF ratio was our primary outcome, we based sample size calculation on independent data obtained from a comparable cohort [24]. In this study, LF/HF values in patients with epilepsy and controls were (mean ± SD) 7.3 ± 5.4 and 4.7 ± 2.8, respectively. Assuming a normal distribution of the LF/HF ratio and a standard deviation of 4 for the total sample, the required sample size for a 90% power and a significance level of 0.05 was 100 subjects (50 for each group). 2.3.2. Statistical analysis A first level of analysis revealed that autonomic indices showed a non-normal distribution. In order to obtain the best possible approximation to a Gaussian curve, variables were square root transformed; this resulted in an appropriate equivalence to a normal distribution (Kolmogorov–Smirnov test, p > 0.2). Age was used as covariate in univariate and multivariate analysis of covariance (ANCOVA/MANCOVA) models. Multivariate analysis of covariance, followed by univariate ANCOVAs, was employed to investigate the group effect on N–N, pNN50, LF, and HF (dependent variables). Univariate results were examined only if Wilks' Lambda multivariate significance criterion was satisfied. As the presence of outliers can increase type I error rate in MANCOVAs, Mahalonobis Distance (MD) was used to identify potential multivariate outliers. Mahalonobis Distance critical value of chi-square distribution, for degrees of freedom = 2 and p b 0.001, was 13.82. Differences in LF/HF ratio among groups were assessed using a one-way ANCOVA. Statistical significance was set at p b 0.05; post hoc tests were performed to define which variables contributed to the measured effects, using Bonferroni's confidence interval adjustment for multiple comparisons. Cohen's d (CI95) was used in significant post hoc tests to measure the effect size.
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3. Results We did not find significant differences between RE, AE, and CON for gender (Pearson Chi-square: χ 2 = 0.160, df = 2, p = 0.92) and age (one-way ANOVA: F2,147 = 1.880, p = 0.16). In the RE group, the analysis of clinical variables showed a significant association between number of seizures and AEDs (Pearson Chi-square, Fischer exact test: χ 2 = 6.912, df = 1, ptwo-tailed = 0.01), between number of seizures and SWI (χ 2 = 26.228, df = 1, ptwo-tailed b 0.0001), and AED treatment and SWI (χ 2 = 10.519, df = 1, ptwo-tailed b 0.002). The RE subgroup with b10 seizures (n = 34) had a higher number of subjects who had not received AED treatment than those who had (24 vs. 10, 71% vs. 29%) whereas the converse was found for the subgroup with >10 seizures (n = 16: 11 vs. 5, 69% vs. 31%). The subgroup with b10 seizures (n = 34) had a lower number of subjects with SWI > 50% than with SWI ≤ 50% (3 vs. 31, 9% vs. 91%) whereas the converse was found for the subgroup with >10 seizures (n = 16: 13 vs. 3, 81% vs. 19%). The subgroup who did not receive AEDs (n = 29) had a lower number of subjects with SWI > 50% than those with SWI ≤ 50% (4 vs. 25, 14% vs. 86%) whereas the converse was found for the subgroup who received AE treatment (n = 21: 12 vs. 9, 57% vs. 43%). Pearson product moment correlation analysis performed on the whole sample with Bonferroni-corrected p-value (0.05/5 = 0.01) showed a significant relationship between age and frequency domain indices (LF: r = 0.26, p = 0.002; HF: r = −0.21, p = 0.009; LF/HF ratio: r = 0.24, p = 0.003) and not for time domain indices (N–N: r = 0.02, p = 0.82; pNN50: r = −0.12, p = 0.15). A multivariate MANCOVA model, using N–N, pNN50, LF, and HF as dependent variables, revealed significant group (between-subject factor: RE vs. AE vs. CON; Wilks' Lambda = 0.891, F8,286 = 2.134, p = 0.03) and age effects (Wilks' Lambda = 0.922, F4,143 = 3.032, p = 0.02). No multivariate outliers were detected in the model (highest MD value: 11.57). Univariate analyses did not show significant differences in time domain indices (N–N: F2,146 = 0.191, p = 0.83; pNN50: F2,146 = 0.616, p = 0.54), whereas significant differences were observed in frequency domain estimates (LF: F2,146 = 5.290, p = 0.006; HF: F2,146 = 4.003; p = 0.02). Rolandic Epilepsy showed lower LF power [post hoc tests: RE vs. CON, p b 0.002; Cohen's d (CI95) = −0.75 (−0.78 to −0.72)] and greater HF power [RE vs. CON, p = 0.007; Cohen's d (CI95) = 0.61 (0.57–0.63)] than controls. No significant difference was found for frequency domain indices both between AE and controls (LF: AE vs. CON, p = 0.10; HF: AE vs. CON, p = 0.77) and between the two epilepsy groups (LF: AE vs. RE, p = 0.51; HF: AE vs. RE, p = 0.15). The LF/HF ratio differed significantly between the three groups (between-subject factor: RE vs. AE vs. CON; F2,146 = 4.126; p b 0.02; age effect: F1,146 = 7.361; p b 0.008). Pairwise comparisons showed significant lower level of the LF/HF ratio in RE with respect to controls [RE vs. CON, p b 0.006; Cohen's d (CI95) = − 0.62 (−0.70 to − 0.54)] whereas no significant difference was found between AE and controls (AE vs. CON, p = 0.27) and between the two epilepsy groups (AE vs. RE, p = 0.44) (Fig. 1). To further analyze differences related to seizure load between the two RE subgroups, we used a MANCOVA model with between-subject factor REb 10 seizures vs. RE> 10 seizures. Multivariate test revealed a statistically significant group effect (Wilks' Lambda = 0.596, F4,44 = 7.465, p = 0.0001); age effect was not significant (Wilks' Lambda= 0.878, F4,44 = 1.534, p = 0.21). No multivariate outliers were present in the model (highest MD value: 7.34). Univariate analyses showed statistical differences only in frequency domain estimates (LF: F1,47 = 21.727, p b 0.0001; HF: F1,47 = 21.634; p b 0.0001). Rolandic Epilepsy patients with b10 seizures showed lower LF power [Cohen's d (CI95) = −1.45 (−1.48 to −1.40)] and higher HF power [Cohen's d (CI95) = 1.45 (1.42–1.50)] than those with >10 seizures. The LF/HF ratio differed significantly between groups (between-subject factor: REb 10 seizures vs. RE>10 seizures; F1,47 =29.821; p b 0.0001; age effect: F1,47 =3.175; p= 0.08). Rolandic Epilepsy patients with less
Fig. 1. LF/HF ratio. Distribution of LF/HF ratio in the three groups. Sympathovagal balance in patients with RE suggests a prevalence of parasympathetic drive.
than 10 seizures had significantly lower level of the LF/HF ratio than those with more than 10 seizures [Cohen's d (CI95) =−1.68 (−1.76 to −1.55)] (Fig. 2a). To investigate differences in autonomic indices between RE with SWI ≤ 50% and SWI > 50%, we used a MANCOVA model with RE ≤50% SWI vs. RE >50 SWI as between-subject factor. Multivariate test revealed a significant group effect (Wilks' Lambda = 0.464, F4,44 = 12.710, p b 0.0001); age effect was not significant (Wilks' Lambda = 0.860, F4,44 = 1.793, p = 0.15). No multivariate outliers were present in the model (highest MD value: 6.92). Univariate
Fig. 2. Sympathovagal balance as a function of seizure frequency and EEG abnormalities. A prevalence of parasympathetic drive in patients with Rolandic Epilepsy is associated with lower lifetime seizure load and spike-wave index.
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parasympathetic activity [29]. Reduced parasympathetic tone has been reported in intractable but not in well-controlled epilepsies [30]. This has led to the hypothesis that methods that able to increase parasympathetic drive might have a role in non-pharmacological management of refractory epilepsies [31]. Evidence of adaptive changes at the cortical level and in thalamo-cortical networks, leading to increased cortical inhibition of the ictal onset and surrounding areas, has been available for some time [32,33]. One speculative explanation of our finding might be that increased bottom-up cortical drive caused by ictal and interictal abnormalities could produce an increase in vagal tone mediated by activation of the hypothalamus–thalamus–vagus networks [34]. This hypothesis is supported by experimental evidence in an animal model of strict correlation between thalamus-induced hypothalamic epileptic bursts and the synchronous phasic activation of the vagal multiunit activity [35]. Increased vagal tone could therefore be an intrinsically protective mechanism to prevent the excessive sympathetic drive seen in uncontrolled epilepsies [30,36] and to limit reoccurring seizures. One of the possible neurochemical substrates could be the increase in GABA-ergic transmission [37], a mechanism invoked to explain the effect of direct vagal nerve stimulation [38]. Further corroborating evidence comes from a recent report of reduced cyclic alternating pattern (CAP) rate in patients with RE [39]. Cyclic alternating pattern rate is an index of sleep instability and is positively correlated with predominance of sympathetic drive [40]. Reduced CAP would suggest increased parasympathetic drive in RE, in agreement with our findings. The analysis of autonomic data in patients of the RE group provided some further insight on the effect of idiopathic focal epileptogenesis in the developing brain. Patients with lower seizure load had lower LF/HF ratio than those with a lifetime seizure count greater than ten. This latter group shows higher sympathetic drive than our non-epileptic controls (Table 2). This finding could be interpreted by suggesting that higher parasympathetic activation is associated with more effective seizure control and that failure of these adaptive processes might result in more difficulty to control seizures. When we look at the effect of interictal epileptiform abnormalities during NREM sleep in the RE group, sympathovagal balance in children with lower SWI suggested a prevalence of parasympathetic drive, which could be read as an indicator of efficacy of protective mechanisms against ictal epileptogenesis. This study has some limitations. Firstly, the study reflects a sample of patients seen in a tertiary specialist center and some caution is necessary in generalizing its findings. Furthermore, the SWI is necessarily a measurement taken at a clinically relevant time-point in the natural history of the condition; a one-off measurement cannot exclude that the patients with lower SWI might have had at some point more
analyses showed significant differences on N–N (F1,47 = 8.296; p b 0.006), LF (F1,47 = 22.099, p b 0.0001), and HF (F1,47 = 41.741; p b 0.0001). Rolandic Epilepsy with SWI ≤ 50% showed higher N–N values [Cohen's d (CI95) = 0.89 (0.87–0.92)], lower LF [Cohen's d (CI95) = − 1.41 (− 1.44 to −1.37)] and higher HF power [Cohen's d (CI95) = 1.95 (1.92–1.99)]. The LF/HF ratio differed significantly between groups (between-subject factor: RE ≤50% SWI vs. RE >50 SWI; F1,47 = 46.453; p b 0.0001; age effect: F1,47 = 5.481; p = 0.02). Rolandic Epilepsy patients with SWI ≤ 50% had significantly lower LF/HF ratio than those with SWI > 50 [Cohen's d (CI95) = −2.01 (−2.08 to −1.88)] (Fig. 2b). To explore differences between the RE with and without AED treatment and RE with AEDs treatment, we create a MANCOVA model with between-subject factors RE no AEDs vs. RE AEDs. Multivariate test revealed a non significant group effect (Wilks' Lambda = 0.859, F4,44 = 1.808, p = 0.14) and age effect (Wilks' Lambda= 0.861, F4,44 = 1.782, p = 0.15). No multivariate outlier was present in the model (highest MD value: 5.90). The LF/HF ratio did not differ between groups (between-subject factor: RE no AEDs vs. RE AEDs; F1,47 = 3.842; p = 0.06; age effect: F1,47 = 3.347; p = 0.07). 4. Discussion Despite the evidence suggesting a high prevalence of interictal autonomic changes in patients with epilepsy, the direction and quality of these abnormalities are still controversial, partly due to variability in age, etiology, syndromic diagnosis, degree of seizure control, time from onset, and AED treatment in the published data [25]. In this study, we focused our analysis on Rolandic Epilepsy to investigate whether autonomic adaptive mechanisms described in symptomatic focal epilepsy were confirmed in idiopathic epileptogenesis. Our findings have shown that time domain measures do not differ significantly between patients and controls. Conversely, patients with epilepsy, irrespective of the focal or generalized classification of their syndrome, present frequency domain changes characterized by increased vagal and reduced sympathetic tone, expressed by a lower LF/HF index than typically developing controls. Our data are in line with findings in patients with temporal lobe epilepsy [26,27], with the caution that in these studies some of the patients were treated with carbamazepine, which is known to induce heart rate variability changes. Autonomic changes of similar direction were reported in a recent study in newly diagnosed untreated adults with epilepsy [28], which did not reach significance threshold possibly due to a relatively small sample size. On the contrary, studies in patients with generalized tonic-clonic seizures on antiepileptic medications have described increased sympathetic drive [24] or suppressed sympathetic and
Table 2 Autonomic indices. RE (n = 50)
N–N Mean (SD) CI95 pNN50 Mean (SD) CI95 LF Mean (SD) CI95 HF Mean (SD) CI95 LF/HF Mean (SD) CI95
AE (n = 50)
CON (n = 50)
RE — Seizure load
RE — SWI
b10 (n = 34)
>10 (n = 16)
≤50% (n = 34)
>50% (n = 16)
No (n = 29)
RE — AED treatment Yes (n = 21)
0.70 (0.10) 0.67–0.72
0.70 (0.09) 0.68–0.73
0.71 (0.12) 0.68–0.74
0.72 (0.10) 0.68–0.75
0.65 (0.08) 0.61–0.69
0.72 (0.10) 0.69–0.76
0.64 (0.08) 0.60–0.68
0.69 (0.10) 0.65–0.73
0.70 (0.11) 0.65–0.75
23.26 (18.29) 18.06–28.46
25.85 (17.81) 20.79–30.91
27.06 (20.28) 21.30–32.82
26.70 (20.20) 19.65–33.74
15.95 (10.54) 10.34–21.57
26.19 (19.86) 19.26–33.12
17.02 (12.80) 10.20–23.85
22.94 (18.08) 16.06–29.82
23.70 (19.00) 15.05–32.35
0.42 (0.15) 0.37–0.46
0.46 (0.16) 0.41–0.50
0.51 (0.11) 0.48–0.54
0.36 (0.12) 0.32–0.40
0.54 (0.12) 0.47–0.61
0.36 (0.12) 0.32–0.40
0.54 (0.12) 0.47–0.60
0.40 (0.13) 0.35–0.44
0.45 (0.17) 0.37–0.52
0.59 (0.19) 0.54–0.65
0.53 (0.15) 0.48–0.57
0.49 (0.12) 0.46–0.52
0.67 (0.18) 0.60–0.73
0.44 (0.12) 0.38–0.50
0.68 (0.17) 0.62–0.74
0.41 (0.09) 0.36–0.46
0.64 (0.19) 0.57–0.72
0.52 (0.17) 0.45–0.60
0.85 (0.62) 0.68–1.03
1.00 (0.57) 0.83–1.16
1.19 (0.68) 0.99–1.38
0.61 (0.35) 0.48–0.73
1.38 (0.74) 0.98–1.77
0.58 (0.29) 0.48–0.68
1.44 (0.73) 1.05–1.83
0.73 (0.55) 0.52–0.94
1.03 (0.68) 0.72–1.34
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frequent abnormalities in sleep. Finally, focal epileptogenesis is a process that evolves over a long period of time. While indirect evidence of minimal autonomic imbalance in newly diagnosed epilepsies [28] suggests that autonomic changes might have a progressive course and develop over the natural history of the disorder as a result of repeated ictal episodes and interictal discharges [41], our study cannot provide direct evidence of the causal relationship between the degree of seizure control and severity of EEG abnormalities and autonomic changes. Mechanisms underlying autonomic changes in epilepsy are complex and difficult to read in a single conceptual framework, particularly if models derived from symptomatic focal epilepsies are tout court applied to idiopathic focal epileptogenesis [42]. Our study draws attention to the need for more systematic investigation of autonomic disturbances which appear particularly prominent in other agerelated focal epilepsies such as Panayiotopoulos syndrome, using a wider range of measures of sympathovagal activity.
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Epilepsy & Behavior journal homepage: www.elsevier.com/locate/yebeh
Interictal autonomic abnormalities in idiopathic Rolandic Epilepsy Stefano Seri a, e,⁎, Giorgio Di Lorenzo b, Tiziana Pisano a, c, Mariangela Pinci d, Daniela Brazzo a, Heather Betteridge e, Antonella Cerquiglini f a
Aston Brain Centre, School of Life and Health Sciences, Aston University, Birmingham, UK Psychophysiology Laboratory, Psychiatry Unit, Department of Neuroscience, University “Tor Vergata”, Rome, Italy Child Neurology Unit, Pediatric Hospital “A. Meyer”, Florence, Italy d Developmental Neuropsychiatry Unit, Department of Neuroscience, University “Tor Vergata”, Rome, Italy e Department of Clinical Neurophysiology, The Birmingham Children's Hospital NHS Foundation Trust, Birmingham, UK f Dipartimento di Scienze e Biotecnologie Medico-Chirurgiche, “Sapienza” Universita' di Roma, Polo Pontino, Italy b c
a r t i c l e
i n f o
Article history: Received 21 February 2012 Revised 12 March 2012 Accepted 13 March 2012 Available online 3 May 2012 Keywords: Heart rate variability Childhood Rolandic Epilepsy Autonomic nervous system Sympathovagal balance
a b s t r a c t We investigated 50 young patients with a diagnosis of Rolandic Epilepsy (RE) for the presence of abnormalities in autonomic tone compared with 50 young patients with idiopathic generalized epilepsy with absences and 50 typically developing children of comparable age. We analyzed time domain (N–N interval, pNN50) and frequency domain (High Frequency (HF), Low Frequency (LF) and LF/HF ratio) indices from tenminute resting EKG activity. Patients with RE showed significantly higher HF and lower LF power and lower LF/HF ratio than controls, independent of the epilepsy group, and did not show significant differences in any other autonomic index with respect to the two control groups. In RE, we found a negative relationship between both seizure load and frequency of sleep interictal EEG abnormalities with parasympathetic drive levels. These changes might be the expression of adaptive mechanisms to prevent the excessive sympathetic drive seen in patients with refractory epilepsies. © 2012 Elsevier Inc. All rights reserved.
1. Introduction Ictal and interictal abnormalities in autonomic control of cardiac frequency have been reported in patients with focal and generalized epilepsies [1–3]; cardiac arrhythmias, as well as changes in blood pressure and cardiac frequency, are observed in temporal relationship with most complex partial and generalized tonic-clonic seizures, independently of other clinical signs. These changes have been considered the expression of an imbalance between vagal and sympathetic activity [4]. Ictal autonomic changes have been implicated in the pathogenesis of sudden unexplained death in young persons with epilepsy [5]. Patients with temporal lobe epilepsy have a higher prevalence of cardiac arrhythmias compared to other localizations of epileptic paroxysmal activity [6,7], with tachycardia being more frequently reported than bradycardia [8,9]. Whether this is related to a specific effect of interictal and ictal discharges in this region or, rather, to a greater frequency of epileptic foci in the temporal lobe, is still unclear [10]. Bradycardia and reduced parasympathetic drive have been reported in patients with frontal lobe epilepsy [11]. Pediatric data are sparse, particularly in children with idiopathic focal epilepsies [12,13]. To further elucidate the complex relationship between seizures, interictal EEG abnormalities, and autonomic regulation in idiopathic epilepsies, we ⁎ Corresponding author at: Room SW 613, Aston University, Aston Triangle, Birmingham, B4 7ET, UK. Fax: +44 121 2044048. E-mail address: [email protected] (S. Seri). 1525-5050/$ – see front matter © 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.yebeh.2012.03.017
analyzed time and frequency domain autonomic measures in young patients with Rolandic Epilepsy (RE). To evaluate the specificity of these findings, we compared data from the RE group with data from a group of patients of comparable age with idiopathic generalized epilepsy with absences as well as from a group of typically developing children without epilepsy.
2. Methods Fifty young patients with RE were recruited from the outpatient population of the pediatric epilepsy programs of the Birmingham Children's Hospital and of the University “Tor Vergata” in Rome. As controls, we investigated a group of 50 children with childhood absence epilepsy (AE) and 50 typically developing children of comparable age and gender mix selected from a large cohort recruited from school-age children in the city of Rome as part of a separate project aimed to obtain normative electrophysiological measures across development. Exclusion criteria were the presence of sensory deficits, history of asthma and heart disease, previous treatment with carbamazepine/oxcarbazepine, lamotrigine and phenytoin, current antiepileptic treatment and/or seizures in the 6 months prior to the recording session. Children who had taken other systemic medications in the month before the recording were also excluded. All participants were instructed to avoid caffeine-based drinks for the 24 hours before the recording.
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In the epilepsy groups, seizure types and syndromic diagnoses were classified according to the International Classification of Seizures and Epilepsy Syndromes [14]. Seizure load for the RE group was ranked as ≤10 or >10 with the cut-off chosen in agreement with recent literature [15]. To investigate the role of severity of interictal EEG abnormalities in the RE group, we retrospectively analyzed data from polygraphic sleep EEG recordings for each patient and calculated the spike-wave index (SWI), defined as total minutes occupied by spike-wave discharges in NREM sleep multiplied by 100 and divided by the total minutes of NREM sleep without interictal EEG discharges, and ranked the variable as ≤50% or >50% in line with recent literature [16,17]. Patients were allocated to the latter of the two groups if at least one sleep EEG recording met the quantitative criterion. The main characteristics of the sample are summarized in Table 1. Parents and young patients consented in writing to the study before the recording. The study received approval by the Local Ethics Committee of the two institutions and was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki. 2.1. Measurement and equipment Electrocardiogram data were recorded as part of a polygraphic EEG study in which brain electrical activity was acquired from 19 electrode positions according to the international 10–20 System [18], using a digital EEG apparatus (Micromed System Plus, Treviso, Italy). One channel acquired cardiac activity from a location corresponding to the V1 EKG position. A further channel recorded chest respiratory effort. Signal was A/D converted at 512 Hz, 24-bit resolution, and stored on digital media for further analysis. Patients and controls were allowed to familiarize with the recording room and with the procedure, and were asked to remain in a supine position for 15 min before the beginning of the recording. The EEG was recorded in a sound-attenuated dimly lit room to facilitate an adequate psychophysical relaxation, using pre-wired electrode caps. Participants were instructed and if necessary, reminded to maintain a respiratory rate of 12 cycles/min. After a ten-minute period of adjustment, we acquired a ten-minute block of polygraphic signal in eyes open and closed conditions that was used for the analysis. The recording lasted approximately 60 min. 2.2. Signal processing and frequency domain analysis Signals were digitally band-pass filtered between 0.53 and 100 Hz. The EKG trace was first exported in EDF format; each QRS complex was then identified using the matching template algorithm available in the NPXLab EEG analysis and visualization software [19]. The Table 1 Main clinical characteristics.
Gender Females Males Age Mean SD Seizure load ≤10 >10 SWI ≤50% >50% AED treatment Yes No
RE
AE
CON
25 25
23 27
24 26
9.27 0.89
9.61 1.14
9.53 0.61
34 16
n.a. n.a.
n.a. n.a.
34 16
n.a. n.a.
n.a. n.a.
21 29
50 0
n.a. n.a.
SWI: spike-wave index, AED: antiepileptic drug; n.a.: not applicable.
time series of the intervals between consecutive R waves was saved in a text file and subject to time and frequency domain analyses using the Software for Advanced HRV analysis [20]. We chose a tenminute analysis time as the best compromise between reliability of the autonomic measures and the need for stationarity imposed by the specific recording setting. According to recent guidelines [21], the following autonomic indices were computed: Time domain: A) N–N (normal to normal) interval: a recommended index of cardio-vagal function; B) pNN50: the number of interval differences of successive N– N intervals greater than 50 ms divided by the total number of N–N intervals. This measure is considered to reflect parasympathetic activity [21]. Frequency domain A) High Frequency (HF): power in the frequency range between 0.15 and 0.4 Hz, considered as a marker for parasympathetic activity [22]; B) Low Frequency (LF): power in the frequency range between 0.04 and 0.15 Hz, a marker of sympathetic modulation [23]. Power spectral density (PSD) estimates where normalized by dividing the raw value by the total spectral power minus that of the specific component. The ratio between LF and HF was also computed. To reduce the effect of the variability in total power, we analyzed the LF and HF in normalized units. Given the relatively short duration of the recording, we chose not to analyze the Very Low Frequency (VLF) component between 0.003 and 0.04 Hz, as it can be of limited reliability under our experimental conditions. 2.3. Statistical method 2.3.1. Sample size calculation Since our primary endpoint was to detect differences between patients with epilepsy and controls and the LF/HF ratio was our primary outcome, we based sample size calculation on independent data obtained from a comparable cohort [24]. In this study, LF/HF values in patients with epilepsy and controls were (mean ± SD) 7.3 ± 5.4 and 4.7 ± 2.8, respectively. Assuming a normal distribution of the LF/HF ratio and a standard deviation of 4 for the total sample, the required sample size for a 90% power and a significance level of 0.05 was 100 subjects (50 for each group). 2.3.2. Statistical analysis A first level of analysis revealed that autonomic indices showed a non-normal distribution. In order to obtain the best possible approximation to a Gaussian curve, variables were square root transformed; this resulted in an appropriate equivalence to a normal distribution (Kolmogorov–Smirnov test, p > 0.2). Age was used as covariate in univariate and multivariate analysis of covariance (ANCOVA/MANCOVA) models. Multivariate analysis of covariance, followed by univariate ANCOVAs, was employed to investigate the group effect on N–N, pNN50, LF, and HF (dependent variables). Univariate results were examined only if Wilks' Lambda multivariate significance criterion was satisfied. As the presence of outliers can increase type I error rate in MANCOVAs, Mahalonobis Distance (MD) was used to identify potential multivariate outliers. Mahalonobis Distance critical value of chi-square distribution, for degrees of freedom = 2 and p b 0.001, was 13.82. Differences in LF/HF ratio among groups were assessed using a one-way ANCOVA. Statistical significance was set at p b 0.05; post hoc tests were performed to define which variables contributed to the measured effects, using Bonferroni's confidence interval adjustment for multiple comparisons. Cohen's d (CI95) was used in significant post hoc tests to measure the effect size.
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3. Results We did not find significant differences between RE, AE, and CON for gender (Pearson Chi-square: χ 2 = 0.160, df = 2, p = 0.92) and age (one-way ANOVA: F2,147 = 1.880, p = 0.16). In the RE group, the analysis of clinical variables showed a significant association between number of seizures and AEDs (Pearson Chi-square, Fischer exact test: χ 2 = 6.912, df = 1, ptwo-tailed = 0.01), between number of seizures and SWI (χ 2 = 26.228, df = 1, ptwo-tailed b 0.0001), and AED treatment and SWI (χ 2 = 10.519, df = 1, ptwo-tailed b 0.002). The RE subgroup with b10 seizures (n = 34) had a higher number of subjects who had not received AED treatment than those who had (24 vs. 10, 71% vs. 29%) whereas the converse was found for the subgroup with >10 seizures (n = 16: 11 vs. 5, 69% vs. 31%). The subgroup with b10 seizures (n = 34) had a lower number of subjects with SWI > 50% than with SWI ≤ 50% (3 vs. 31, 9% vs. 91%) whereas the converse was found for the subgroup with >10 seizures (n = 16: 13 vs. 3, 81% vs. 19%). The subgroup who did not receive AEDs (n = 29) had a lower number of subjects with SWI > 50% than those with SWI ≤ 50% (4 vs. 25, 14% vs. 86%) whereas the converse was found for the subgroup who received AE treatment (n = 21: 12 vs. 9, 57% vs. 43%). Pearson product moment correlation analysis performed on the whole sample with Bonferroni-corrected p-value (0.05/5 = 0.01) showed a significant relationship between age and frequency domain indices (LF: r = 0.26, p = 0.002; HF: r = −0.21, p = 0.009; LF/HF ratio: r = 0.24, p = 0.003) and not for time domain indices (N–N: r = 0.02, p = 0.82; pNN50: r = −0.12, p = 0.15). A multivariate MANCOVA model, using N–N, pNN50, LF, and HF as dependent variables, revealed significant group (between-subject factor: RE vs. AE vs. CON; Wilks' Lambda = 0.891, F8,286 = 2.134, p = 0.03) and age effects (Wilks' Lambda = 0.922, F4,143 = 3.032, p = 0.02). No multivariate outliers were detected in the model (highest MD value: 11.57). Univariate analyses did not show significant differences in time domain indices (N–N: F2,146 = 0.191, p = 0.83; pNN50: F2,146 = 0.616, p = 0.54), whereas significant differences were observed in frequency domain estimates (LF: F2,146 = 5.290, p = 0.006; HF: F2,146 = 4.003; p = 0.02). Rolandic Epilepsy showed lower LF power [post hoc tests: RE vs. CON, p b 0.002; Cohen's d (CI95) = −0.75 (−0.78 to −0.72)] and greater HF power [RE vs. CON, p = 0.007; Cohen's d (CI95) = 0.61 (0.57–0.63)] than controls. No significant difference was found for frequency domain indices both between AE and controls (LF: AE vs. CON, p = 0.10; HF: AE vs. CON, p = 0.77) and between the two epilepsy groups (LF: AE vs. RE, p = 0.51; HF: AE vs. RE, p = 0.15). The LF/HF ratio differed significantly between the three groups (between-subject factor: RE vs. AE vs. CON; F2,146 = 4.126; p b 0.02; age effect: F1,146 = 7.361; p b 0.008). Pairwise comparisons showed significant lower level of the LF/HF ratio in RE with respect to controls [RE vs. CON, p b 0.006; Cohen's d (CI95) = − 0.62 (−0.70 to − 0.54)] whereas no significant difference was found between AE and controls (AE vs. CON, p = 0.27) and between the two epilepsy groups (AE vs. RE, p = 0.44) (Fig. 1). To further analyze differences related to seizure load between the two RE subgroups, we used a MANCOVA model with between-subject factor REb 10 seizures vs. RE> 10 seizures. Multivariate test revealed a statistically significant group effect (Wilks' Lambda = 0.596, F4,44 = 7.465, p = 0.0001); age effect was not significant (Wilks' Lambda= 0.878, F4,44 = 1.534, p = 0.21). No multivariate outliers were present in the model (highest MD value: 7.34). Univariate analyses showed statistical differences only in frequency domain estimates (LF: F1,47 = 21.727, p b 0.0001; HF: F1,47 = 21.634; p b 0.0001). Rolandic Epilepsy patients with b10 seizures showed lower LF power [Cohen's d (CI95) = −1.45 (−1.48 to −1.40)] and higher HF power [Cohen's d (CI95) = 1.45 (1.42–1.50)] than those with >10 seizures. The LF/HF ratio differed significantly between groups (between-subject factor: REb 10 seizures vs. RE>10 seizures; F1,47 =29.821; p b 0.0001; age effect: F1,47 =3.175; p= 0.08). Rolandic Epilepsy patients with less
Fig. 1. LF/HF ratio. Distribution of LF/HF ratio in the three groups. Sympathovagal balance in patients with RE suggests a prevalence of parasympathetic drive.
than 10 seizures had significantly lower level of the LF/HF ratio than those with more than 10 seizures [Cohen's d (CI95) =−1.68 (−1.76 to −1.55)] (Fig. 2a). To investigate differences in autonomic indices between RE with SWI ≤ 50% and SWI > 50%, we used a MANCOVA model with RE ≤50% SWI vs. RE >50 SWI as between-subject factor. Multivariate test revealed a significant group effect (Wilks' Lambda = 0.464, F4,44 = 12.710, p b 0.0001); age effect was not significant (Wilks' Lambda = 0.860, F4,44 = 1.793, p = 0.15). No multivariate outliers were present in the model (highest MD value: 6.92). Univariate
Fig. 2. Sympathovagal balance as a function of seizure frequency and EEG abnormalities. A prevalence of parasympathetic drive in patients with Rolandic Epilepsy is associated with lower lifetime seizure load and spike-wave index.
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parasympathetic activity [29]. Reduced parasympathetic tone has been reported in intractable but not in well-controlled epilepsies [30]. This has led to the hypothesis that methods that able to increase parasympathetic drive might have a role in non-pharmacological management of refractory epilepsies [31]. Evidence of adaptive changes at the cortical level and in thalamo-cortical networks, leading to increased cortical inhibition of the ictal onset and surrounding areas, has been available for some time [32,33]. One speculative explanation of our finding might be that increased bottom-up cortical drive caused by ictal and interictal abnormalities could produce an increase in vagal tone mediated by activation of the hypothalamus–thalamus–vagus networks [34]. This hypothesis is supported by experimental evidence in an animal model of strict correlation between thalamus-induced hypothalamic epileptic bursts and the synchronous phasic activation of the vagal multiunit activity [35]. Increased vagal tone could therefore be an intrinsically protective mechanism to prevent the excessive sympathetic drive seen in uncontrolled epilepsies [30,36] and to limit reoccurring seizures. One of the possible neurochemical substrates could be the increase in GABA-ergic transmission [37], a mechanism invoked to explain the effect of direct vagal nerve stimulation [38]. Further corroborating evidence comes from a recent report of reduced cyclic alternating pattern (CAP) rate in patients with RE [39]. Cyclic alternating pattern rate is an index of sleep instability and is positively correlated with predominance of sympathetic drive [40]. Reduced CAP would suggest increased parasympathetic drive in RE, in agreement with our findings. The analysis of autonomic data in patients of the RE group provided some further insight on the effect of idiopathic focal epileptogenesis in the developing brain. Patients with lower seizure load had lower LF/HF ratio than those with a lifetime seizure count greater than ten. This latter group shows higher sympathetic drive than our non-epileptic controls (Table 2). This finding could be interpreted by suggesting that higher parasympathetic activation is associated with more effective seizure control and that failure of these adaptive processes might result in more difficulty to control seizures. When we look at the effect of interictal epileptiform abnormalities during NREM sleep in the RE group, sympathovagal balance in children with lower SWI suggested a prevalence of parasympathetic drive, which could be read as an indicator of efficacy of protective mechanisms against ictal epileptogenesis. This study has some limitations. Firstly, the study reflects a sample of patients seen in a tertiary specialist center and some caution is necessary in generalizing its findings. Furthermore, the SWI is necessarily a measurement taken at a clinically relevant time-point in the natural history of the condition; a one-off measurement cannot exclude that the patients with lower SWI might have had at some point more
analyses showed significant differences on N–N (F1,47 = 8.296; p b 0.006), LF (F1,47 = 22.099, p b 0.0001), and HF (F1,47 = 41.741; p b 0.0001). Rolandic Epilepsy with SWI ≤ 50% showed higher N–N values [Cohen's d (CI95) = 0.89 (0.87–0.92)], lower LF [Cohen's d (CI95) = − 1.41 (− 1.44 to −1.37)] and higher HF power [Cohen's d (CI95) = 1.95 (1.92–1.99)]. The LF/HF ratio differed significantly between groups (between-subject factor: RE ≤50% SWI vs. RE >50 SWI; F1,47 = 46.453; p b 0.0001; age effect: F1,47 = 5.481; p = 0.02). Rolandic Epilepsy patients with SWI ≤ 50% had significantly lower LF/HF ratio than those with SWI > 50 [Cohen's d (CI95) = −2.01 (−2.08 to −1.88)] (Fig. 2b). To explore differences between the RE with and without AED treatment and RE with AEDs treatment, we create a MANCOVA model with between-subject factors RE no AEDs vs. RE AEDs. Multivariate test revealed a non significant group effect (Wilks' Lambda = 0.859, F4,44 = 1.808, p = 0.14) and age effect (Wilks' Lambda= 0.861, F4,44 = 1.782, p = 0.15). No multivariate outlier was present in the model (highest MD value: 5.90). The LF/HF ratio did not differ between groups (between-subject factor: RE no AEDs vs. RE AEDs; F1,47 = 3.842; p = 0.06; age effect: F1,47 = 3.347; p = 0.07). 4. Discussion Despite the evidence suggesting a high prevalence of interictal autonomic changes in patients with epilepsy, the direction and quality of these abnormalities are still controversial, partly due to variability in age, etiology, syndromic diagnosis, degree of seizure control, time from onset, and AED treatment in the published data [25]. In this study, we focused our analysis on Rolandic Epilepsy to investigate whether autonomic adaptive mechanisms described in symptomatic focal epilepsy were confirmed in idiopathic epileptogenesis. Our findings have shown that time domain measures do not differ significantly between patients and controls. Conversely, patients with epilepsy, irrespective of the focal or generalized classification of their syndrome, present frequency domain changes characterized by increased vagal and reduced sympathetic tone, expressed by a lower LF/HF index than typically developing controls. Our data are in line with findings in patients with temporal lobe epilepsy [26,27], with the caution that in these studies some of the patients were treated with carbamazepine, which is known to induce heart rate variability changes. Autonomic changes of similar direction were reported in a recent study in newly diagnosed untreated adults with epilepsy [28], which did not reach significance threshold possibly due to a relatively small sample size. On the contrary, studies in patients with generalized tonic-clonic seizures on antiepileptic medications have described increased sympathetic drive [24] or suppressed sympathetic and
Table 2 Autonomic indices. RE (n = 50)
N–N Mean (SD) CI95 pNN50 Mean (SD) CI95 LF Mean (SD) CI95 HF Mean (SD) CI95 LF/HF Mean (SD) CI95
AE (n = 50)
CON (n = 50)
RE — Seizure load
RE — SWI
b10 (n = 34)
>10 (n = 16)
≤50% (n = 34)
>50% (n = 16)
No (n = 29)
RE — AED treatment Yes (n = 21)
0.70 (0.10) 0.67–0.72
0.70 (0.09) 0.68–0.73
0.71 (0.12) 0.68–0.74
0.72 (0.10) 0.68–0.75
0.65 (0.08) 0.61–0.69
0.72 (0.10) 0.69–0.76
0.64 (0.08) 0.60–0.68
0.69 (0.10) 0.65–0.73
0.70 (0.11) 0.65–0.75
23.26 (18.29) 18.06–28.46
25.85 (17.81) 20.79–30.91
27.06 (20.28) 21.30–32.82
26.70 (20.20) 19.65–33.74
15.95 (10.54) 10.34–21.57
26.19 (19.86) 19.26–33.12
17.02 (12.80) 10.20–23.85
22.94 (18.08) 16.06–29.82
23.70 (19.00) 15.05–32.35
0.42 (0.15) 0.37–0.46
0.46 (0.16) 0.41–0.50
0.51 (0.11) 0.48–0.54
0.36 (0.12) 0.32–0.40
0.54 (0.12) 0.47–0.61
0.36 (0.12) 0.32–0.40
0.54 (0.12) 0.47–0.60
0.40 (0.13) 0.35–0.44
0.45 (0.17) 0.37–0.52
0.59 (0.19) 0.54–0.65
0.53 (0.15) 0.48–0.57
0.49 (0.12) 0.46–0.52
0.67 (0.18) 0.60–0.73
0.44 (0.12) 0.38–0.50
0.68 (0.17) 0.62–0.74
0.41 (0.09) 0.36–0.46
0.64 (0.19) 0.57–0.72
0.52 (0.17) 0.45–0.60
0.85 (0.62) 0.68–1.03
1.00 (0.57) 0.83–1.16
1.19 (0.68) 0.99–1.38
0.61 (0.35) 0.48–0.73
1.38 (0.74) 0.98–1.77
0.58 (0.29) 0.48–0.68
1.44 (0.73) 1.05–1.83
0.73 (0.55) 0.52–0.94
1.03 (0.68) 0.72–1.34
S. Seri et al. / Epilepsy & Behavior 24 (2012) 241–245
frequent abnormalities in sleep. Finally, focal epileptogenesis is a process that evolves over a long period of time. While indirect evidence of minimal autonomic imbalance in newly diagnosed epilepsies [28] suggests that autonomic changes might have a progressive course and develop over the natural history of the disorder as a result of repeated ictal episodes and interictal discharges [41], our study cannot provide direct evidence of the causal relationship between the degree of seizure control and severity of EEG abnormalities and autonomic changes. Mechanisms underlying autonomic changes in epilepsy are complex and difficult to read in a single conceptual framework, particularly if models derived from symptomatic focal epilepsies are tout court applied to idiopathic focal epileptogenesis [42]. Our study draws attention to the need for more systematic investigation of autonomic disturbances which appear particularly prominent in other agerelated focal epilepsies such as Panayiotopoulos syndrome, using a wider range of measures of sympathovagal activity.
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