INTRODUCTION

 

Antiepileptic drugs (AEDs) are always the primary treatment option for epilepsy. Inspite of being effective for seizure control, AEDs can also cause neurotoxicity leading to undesirable effects on normal functions of the central nervous system (CNS)¹.

The use of electroencephalographic (EEG) measures can provide deep insight in studying the effect of pharmacological intervention on cognition^2,3 .

Since background EEG activity reflects the functional state of the brain, its analysis can be a simple and objective method of assessment of AEDs effects⁴. Although some studies have shown better diagnostic yield with quantitative EEG (QEEG) measures⁵, however, others have reported the same findings in both QEEG and routine recordings in epileptic patients⁶. Some studies carried out on background EEG activity with QEEG have been conducted in IGE and focal epileptic patients, and revealed background changes despite normal visual analysis of their  background activity^7-15.

The objective of this study is to assess the effect of AEDs on the background activity of the inter ictal EEG recordings, using quantitative measures of some epileptic patients, known to have whether partial or generalized epilepsy.

 

METHODOLOGY

 

This study is a retrospective study. It was carried out by exploring the medical records of epileptic patients attending the epilepsy outpatient clinic of Kasr Alainy hospital, during the period from 15/1/2012 and to 9/9/2012. The EEG recordings and filing were in the Clinical Neurophysiology Unit, Kasr Alainy hospital, Cairo University. The EEG records were visually assessed by only two electroencephalographers to minimize inter reader subjective variability. The patients, by clinical history, were either on AEDs or not. The AEDs included: Carbamazepine, Clonazepam, Levetiracetam, Phenytoin, Topiramate and Valproate (or Valproic acid).

Digital EEG was recorded using Schwarzer  BrainLaB 4 GmbH.   The investigation was carried out while the patient was recumbent in dorsal position in semi-luminated room. The electrodes were placed according to the international 10-20 system, with electrode impedance below 10 Kohm, and ear lobe electrodes served as reference. Recording was carried out for about 20 minutes with 3 minutes hyperventilation as well as intermittent photic stimulation.

Five artifacts’ free epochs, each of 10 seconds duration were selected for QEEG. The relative powers of 19 electrodes (Fp1, Fp2, F7, F8, F3, F4, C3,C4, T3, T4, T5, T6, P3, P4, O1, O2, Fz, Cz and Pz) were studied in the following frequency bands: delta (1-3Hz), theta (4-7 Hz), alpha (8-12 Hz), Beta 1 (12.5–16 Hz) Beta2(16.5–20 Hz) and Beta3(20.5–28 Hz). The sum of quantitative EEG readings was 114 different readings for each patient.

Relative power is represented by the percentage of the power of a given frequency band compared to the sum of the power of all frequency bands. Relative delta power, for example, is equal to (absolute delta power/absolute delta power + absolute theta power + absolute alpha power + absolute beta power) * 100.

Data were statistically described in terms of mean ± standard deviation (± SD), median and range, or frequencies (number of cases) and percentages when appropriate. Comparison of numerical variables between the study groups was done using Student t test for independent samples when the data were normally distributed and/or the groups were large enough, while Mann Whitney U test for independent samples was used when data were not normally distributed. For comparing gender, Chi square (c²) test was performed. Correlation between various variables was done using Pearson moment correlation equation for linear relation in normally distributed variables and Spearman rank correlation equation for non-normal variables/non-linear monotonic relation. p values less than 0.05 was considered statistically significant. All statistical calculations were done using computer program SPSS (Statistical Package for the Social Science; SPSS Inc., Chicago, IL, USA) release 15 for Microsoft Windows (2006).

 

RESULTS

 

A)           Descriptive Data:

The study included 61 patients, 24 of them were females. Their age ranged from 11 to 57 years with a mean of 25.4 (SD=11.52). The duration of the illness ranged from “just diagnosed disease” and reached 30 years of epileptic history, with mean illness duration of 8.383 years (SD=7.986). The frequency of ictal events ranged from 1-7 fits per month, with a mean frequency of 3.262 fits/month (SD=1.569). The visual EEG analysis showed dominant background rhythm of range 8.5-11.5 Hz and a mean of 9.491Hz (SD=0.679).

There were 20 patients diagnosed as having focal epilepsy, while 41 patients were diagnosed as having generalized epilepsy. There were 30patients on AEDs, while 31 patients were not (medicated group and non-medicated group). Patients on AEDs were prescribed 1-4medication types, with an average of 1.3 AEDs. Patients taking old generation AEDs were 30, while those on new generation AEDs were 8, and patients taking both generations were 7 patients.

 

B)           Comparative Data:

1.      Quantitative EEG of medicated versus non-medicated group:

Both medicated and non-medicated groups are age and gender matched. The medicated males: females ratio was 17:13. While the non-medicated males: females ratio was 20:11. The age in medicated group showed a mean of 26.88 years (SD=10.72), while the non-medicated group showed a mean age of 24.16 years (SD=12.19).

Out of all the QEEG readings (114 Q-EEG readings), there was significant increase in powers among non-medicated, compared to the medicated group patients in 12 readings. They were slow (delta and theta) waves in the midline and bilateral parietal region (in addition to T4 and F4 theta waves). This is shown in Table (1).

2.      Quantitative EEG of medicated versus non-medicated patients with generalized epilepsy:

There were 20 medicated and 21 non-medicated patients with generalized epilepsy. Out of all the QEEG readings (114 Q-EEG readings), there was significant increased powers among non-medicated, compared to the medicated male patients in five readings They are midline and bilateral parietal slow waves (P3, P4, Fz, Cz theta and Pz delta).

3.      Quantitative EEG of medicated versus non-medicated males:

There were 17 medicated, and 20 non-medicated males. Out of all the QEEG readings (114 Q-EEG readings), there was consistently significant increased powers among non-medicated, compared to the medicated male patients in 56 readings. This is shown in Figure (1).

 

C)           Correlative Tests:

1.      Quantitative EEG readings correlation to disease duration:

Out of all the QEEG readings (114 Q-EEG readings), there were three positive correlations (two of them are non-parametric) to the disease duration (F4, O1 and Fz delta).

2.      Quantitative EEG readings correlation to epileptic fits frequency:

Out of all the QEEG readings (114 Q-EEG readings), there was a single positive correlation to the fits frequency (Cz delta).

 

 

Table 1. Significantly different QEEG readings in medicated, versus non-medicated group.

 

 

              

 

 

Figure 1. The widespread increased power of slow waves in non-medicated versus medicated males****= significant.

 

 

DISCUSSION

 

In the present study we investigated the effect of antiepileptic medications on the background EEG power spectra, using the relative power calculation. We conducted a comparison between a group of medicated and non-medicated epileptic patients, with focal and generalized seizures. The patients were age and gender matched. For all the patients, the visual background activity was normal.

The study showed a statistically significant increase in the power of slow activities of midline and parasagittal regions in the non-medicated compared to the medicated epileptic patients. This was more also noted between the medicated and non-medicated patients with generalized seizures. These findings are similar to previous works of Clemens and coworkers^14,15 who found a reduced absolute power in low-frequency bands (1.5–12.5 Hz) in epileptic patients after treatment with valproate and lamotrigine. As regards our patients, 48% of the medicated group were on valproate, and in patients with generalized seizures, they were 50%.

The absolute power reflects the degree of synchronization of the cortical EEG sources at a given frequency (or in a frequency band), and is proportional to the number of the synchronously activated generators that contribute to the signal¹⁶.

According to findings of Clemens, the valproate-related decrease of synchronization was significantly greater in the medial (midline + parasagittal) leads than in the lateral derivations¹⁴, which was also seen in the present study. The medial electrodes mainly explore the frontal and parietal cortex where the majority of the so-called non-specific thalamo-cortical fibers terminate, mediating the synchronized recruiting cortical response and the spike-wave paroxysms.^{14, 17}.

These findings are in contrast to other studies who found an increase in the absolute delta and a decrease in mean frequency of delta, which were detected in fronto-temporal and occipital leads in both medicated and non-medicated groups in patients with juvenile myoclonic epilepsy¹². Another study showed a general tendency for diffuse (absolute and relative) delta, theta and alpha power excess and relative beta power deficit in patients with idiopathic generalized epilepsy to controls⁷.

Another study showed Carbamazepine and lamotrigine, both sodium-channel modulators, altered brain topography in the gamma range in the same frequency bands (50–60 Hz). Valproate, which has multiple actions on sodium and calcium channels as well as GABA turnover, modified brain topography in the low gamma range (30–40 Hz). They did not report any change in the other frequency bands¹³. Our study did not test the gamma band. Modification of gamma-power reflects changes within local cortical regions^18,19 and may relate to seizure initiation^20,21 unlike changes in lower frequency bands, which reflect interregional communication and might relate to seizure propagation²².

We found a decreasing power of the slow activities that was significant and widespread between medicated compared to non-medicated males, whereas similar results were not seen in females. This may be explained by the changing of the blood levels of antiepileptic drugs, as many of them are broken down by the same enzymes that metabolize estrogen and progesterone^23,24.

Some studies confirmed a decrease in blood levels of antiepileptic drugs around the time of menstruation, whereas other studies were not conclusive²⁵.

The present study showed also a significant correlation, however not widespread in locations, between the power of slow wave and duration of illness as well as with frequency of seizures in all patients. This may be related to the relationship between cognitive decline and the frequency of seizures²⁶and the increased power of slow waves are associated with cognitive decline²⁷.

We conclude that, inspite of normal visual analysis of background EEG in epileptic patients, there was an increase in the relative power of slow frequency bands in non-medicated compared to medicated groups, especially in the central and parasagittal regions, evident in patients with generalized seizures and in males. In order to confirm these results, future studies with larger samples of patients are recommended.

 

[Disclosure: Authors report no conflict of interest]

 

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