Advertisement

Exploring factors associated with interictal heart rate variability in patients with medically controlled focal epilepsy

  • Author Footnotes
    # contributed as first author
    Wei-Chih Yeh
    Footnotes
    # contributed as first author
    Affiliations
    Department of Neurology, Kaohsiung Medical University Hospital, No. 100, Tzyou 1st. Road, Kaohsiung City 80754, Taiwan

    Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, No. 100, Shih-Chuan 1st Road, Kaohsiung City 80708, Taiwan
    Search for articles by this author
  • Hsun-Chang Lin
    Affiliations
    Department of Neurology, Health and Welfare Ministry Pingtung Hospital, No.270, Ziyou Rd., Pingtung City, Pingtung County 900, Taiwan
    Search for articles by this author
  • Yao-Chung Chuang
    Affiliations
    Department of Neurology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung, University College of Medicine, Kaohsiung, Taiwan.
    Search for articles by this author
  • Chung-Yao Hsu
    Correspondence
    Corresponding author at: Department of Neurology, Division of Epilepsy and Sleep Disorders, Kaohsiung Medical University Hospital, No.100, Tzyou 1st Rd., Kaohsiung City 80754, Taiwan
    Affiliations
    Department of Neurology, Kaohsiung Medical University Hospital, No.100, Tzyou 1st Rd., Kaohsiung City 80754, Taiwan

    Department of Neurology, Faculty of Medicine, College of Medicine, Kaohsiung Medical, University, Kaohsiung City 80708, Taiwan.
    Search for articles by this author
  • Author Footnotes
    # contributed as first author
Open ArchivePublished:August 07, 2021DOI:https://doi.org/10.1016/j.seizure.2021.08.003

      Highlights

      • People with epilepsy has lower heart rate variability.
      • Patients with refractory epilepsy may have more severe autonomic dysregulation.
      • We investigated factors associated with interictal HRV in patients with medically controlled focal epilepsy.
      • Low heart rate variability was seen for focal to bilateral tonic–clonic seizures.
      • Thus, even for medically controlled epilepsies, such cases require careful consideration.

      Abstract

      Purpose

      Heart rate variability (HRV) reflects the balance between the functional outputs of the sympathetic and parasympathetic nervous systems. It is lower in patients with epilepsy than in the healthy controls. However, HRV has been inadequately studied in different patient subgroups with medically controlled epilepsy. Hence, this study aimed to investigate factors associated with interictal HRV in patients with medically controlled epilepsy.

      Methods

      This retrospective cohort study included 54 patients (24 males and 30 females) with medically controlled focal epilepsy who only received monotherapy to eliminate the confounding effect of different antiseizure medications (ASMs). Patients with major systemic or psychiatric disorder comorbidities were excluded. For HRV analysis, electroencephalography and 5-minute well-qualified electrocardiogram segment recording were conducted during stage N1 or N2 sleep. In addition, the association between age, gender, seizure onset type, ASMs, and the time domain and frequency-domain HRV measures was analyzed.

      Results

      HRV negatively correlated with advanced age. Patients with focal to bilateral tonic-clonic seizure (FBTCS) had a significantly lower HRV than focal impaired awareness seizures (FIAS). HRV was not associated with any gender and ASMs.

      Conclusions

      HRV negatively correlated with age, and patients with FBTCS had a decreased HRV. Thus, these patients may have a declining autonomic function. Therefore, different seizure types may carry different risks of autonomic dysfunction in patients with medically controlled focal epilepsy.

      Key words

      Abbreviations:

      ASMs (antiseizure medications), DCT (discrete cosine transform), EEG (electroencephalography), EKG (electrocardiogram), FBTCS (focal to bilateral tonic–clonic seizure), FFT (fast Fourier transform), FIAS (focal impaired awareness seizure), GTCS (generalized tonic–clonic seizure), HF (high frequency), HRV (heart rate variability), LF (low frequency), n-HF (normalized high frequency), n-LF (normalized low frequency), NN interval (normal-to-normal interval), RMSSD (root mean square of the successive differences), SD1 (standard deviation of the short axis of Poincaré plot), SD2 (standard deviation of the long axis of Poincaré plot), SDNN (standard deviation of normal-to-normal intervals), SUDEP (sudden unexpected death of epilepsy), TP (total power), VLF (very low frequency)

      Introduction

      People with epilepsy have autonomic dysfunction and a significantly higher premature mortality rate than the healthy controls. [
      • Devinsky O.
      • Spruill T.
      • Thurman D.
      • et al.
      Recognizing and preventing epilepsy-related mortality: A call for action.
      ,
      • Fazel S.
      • Wolf A.
      • Langstrom N.
      • et al.
      Premature mortality in epilepsy and the role of psychiatric comorbidity: a total population study.
      ] Heart rate variability (HRV), a marker of autonomic function, reflects the balance between sympathetic and parasympathetic activities. [
      • Cygankiewicz I.
      • Zareba W.
      Heart rate variability.
      ] HRV parameters are a useful objective marker of physiological stress. It measures the changes in time intervals between consecutive heartbeats. [
      • Shaffer F.
      • Ginsberg J.P.
      ] Increased HRV indicates an increased parasympathetic activity, whereas decreased HRV indicates increased sympathetic activity. [
      • Ernst G.
      ]
      Elevated levels of chronic stress (increased sympathetic activity) are associated with a range of physiological changes (cardiovascular, endocrinological and, immunological changes) which have negative impacts on people's physical and mental health. [
      • Kim H.G.
      • Cheon E.J.
      • Bai D.S.
      • et al.
      Stress and Heart Rate Variability: A Meta-Analysis and Review of the Literature.
      ] Decreased HRV is an independent predicting factor of sudden death in people with chronic heart failure. [
      • La Rovere M.T.
      • Pinna G.D.
      • Maestri R.
      • et al.
      Short-term heart rate variability strongly predicts sudden cardiac death in chronic heart failure patients.
      ] Maintaining the balance between the parasympathetic and sympathetic nervous systems is important, particularly in patients with epilepsy because they are susceptible to medical or psychiatric comorbidities. [
      • Keezer M.R.
      • Sisodiya S.M.
      • Sander J.W.
      Comorbidities of epilepsy: current concepts and future perspectives.
      ]
      Different subgroup of patients with epilepsy have lower interictal HRV than the healthy controls. [
      • Myers K.A.
      • Sivathamboo S.
      • Perucca P.
      Heart rate variability measurement in epilepsy: How can we move from research to clinical practice?.
      ,
      • do Nascimento Vinholes L.
      • Sousa da Silva A.
      • Tassi E.Marinho
      • et al.
      Heart rate variability in frontal lobe epilepsy: Association with SUDEP risk.
      ,
      • Sivathamboo S.
      • Perucca P.
      Interictal autonomic dysfunction.
      ] Patients with frontal lobe epilepsy have decreased standard deviation of normal-to-normal intervals (SDNN), SDNN-index (SDNN-index), and root mean square of the successive differences (RMSSD). [
      • do Nascimento Vinholes L.
      • Sousa da Silva A.
      • Tassi E.Marinho
      • et al.
      Heart rate variability in frontal lobe epilepsy: Association with SUDEP risk.
      ] All time domain and frequency-domain HRV measures are lower in patients with generalized epilepsy than in the healthy control. [
      • Sivakumar S.S.
      • Namath A.G.
      • Tuxhorn I.E.
      • et al.
      Decreased heart rate and enhanced sinus arrhythmia during interictal sleep demonstrate autonomic imbalance in generalized epilepsy.
      ] In addition, a meta-analysis of 39 studies found that patients with epilepsy had lower values of high frequency (HF), SDNN, and RMSSD than the healthy controls. [
      • Lotufo P.A.
      • Valiengo L.
      • Bensenor I.M.
      • et al.
      A systematic review and meta-analysis of heart rate variability in epilepsy and antiepileptic drugs.
      ]
      One-third of patients with epilepsy are refractory to currently available ASMs. [
      • Tang F.
      • Hartz A.M.S.
      • Bauer B.
      Drug-Resistant Epilepsy: Multiple Hypotheses, Few Answers.
      ] Patients with refractory epilepsy may have more severe autonomic dysregulation. [
      • Kananen J.
      • Tuovinen T.
      • Ansakorpi H.
      • et al.
      Altered physiological brain variation in drug-resistant epilepsy.
      ] Compared with patients with medically controlled temporal lobe epilepsy (TLE), patients with refractory TLE had overall reduction of HRV. [
      • Ansakorpi H.
      • Korpelainen J.T.
      • Huikuri H.V.
      • et al.
      Heart rate dynamics in refractory and well controlled temporal lobe epilepsy.
      ]
      ASMs may also influence the HRV of people with epilepsy. Carbamazepine, a sodium channel blocker, suppresses both sympathetic and parasympathetic functions. [
      • Persson H.
      • Ericson M.
      • Tomson T.
      Carbamazepine affects autonomic cardiac control in patients with newly diagnosed epilepsy.
      ] On the other hand, study from Litovchenko et al. indicated that levetiracetam and lamotrigine have more neutral effects on the autonomic balance of the HRV than carbamazepine and valproic acid. [
      • Litovchenko T.
      • Grymailo V.
      • Tondiy O.
      • et al.
      The peculiarities of the heart rate variability and electroencephalogram changes in patients with epilepsy and cardiovascular pathology.
      ]
      Factors associated with HRV in patients with refractory epilepsy have been investigated thoroughly, but studies focusing on interictal HRV between subgroups of patients with medically controlled epilepsy remain limited. Therefore, the present study aimed to evaluate HRV-related factors in patients with medically controlled focal epilepsy.

      Materials and methods

      Participants

      This retrospective cohort study enrolled patients diagnosed with epilepsy who were followed up at the Neurology Department of Kaohsiung Medical University Hospital between January 2010 and July 2014. All the patients who were followed up at our department underwent routine video EEG.
      The present study aimed to focus on patients with seizure freedom after ASMs (medically controlled epilepsy) based on the criterion defined by the International League Against Epilepsy (ILAE). [
      • Kwan P.
      • Arzimanoglou A.
      • Berg A.T.
      • et al.
      Definition of drug resistant epilepsy: consensus proposal by the ad hoc Task Force of the ILAE Commission on Therapeutic Strategies.
      ] We included patients who were diagnosed with focal epilepsy, already underwent electroencephalography (EEG) with a recorded electrocardiogram (EKG), prescribed with ASM monotherapy, and regularly used ASM for at least 4 weeks. Conversely, we excluded patients with generalized seizure onset and unknown seizure onset. Patients with chronic heart failure, chronic kidney disease, hyperthyroidism and hypothyroidism, Parkinson's diseases, or beta-blocker or calcium channel blocker therapy, as shown on the electronic medical record.
      Epilepsy was classified according to both, seizure semiology and interictal EEG findings. Most of the “EEG focus” in this study indicated interictal epileptiform discharges that were recorded during EEG monitoring. They included sharp, spike, spike-and-wave, and poly-spike waves. Only a few patients had ictal discharge during the monitoring. These ictal EEG foci can further support the semiology. Moreover, sleep deprivation or medication was not used to facilitate sleep; all the recordings were acquired under natural sleep conditions. The institutional review board of our hospital approved our study (IRB number: KMUH-IRB-20130231).
      Considering the retrospective study design and the anonymized data format, informed consent was not required. All study-related procedures were carried out in accordance with the principles of the Declaration of Helsinki. This article does not disclose any personal identifiable information of any participant in any form. Therefore, consent for publication is not required for our study.

      Antiseizure medications

      According to their main pharmacological mechanisms, carbamazepine, lamotrigine, oxcarbazepine, and phenytoin were classified as sodium channel blockers, while levetiracetam and valproate were classified as broad-spectrum ASMs. [
      • Sills G.J.
      • Rogawski M.A.
      Mechanisms of action of currently used antiseizure drugs.
      ]

      EEG sample

      All patients underwent EEG study (Nicolet Ultra-Som). Results from the international 10–20 system of EEG with 19 electrodes (Fp1, Fp2, F3, F4, F7, F8, T3, T4, C3, C4, T5, T6, P3, P4, O1, O2, Fz, Cz, and Pz) and lead II EKG electrode were recorded simultaneously. HRV was analyzed using the 5-minute EKG segment during stage N1 or N2 sleep with regular sinus rhythm.

      HRV analysis

      HRV measures included time domain and frequency-domain indices. HRV analysis was computed by Matrix Laboratory (version 9.1), the time-frequency transformation was conducted using the discrete cosine transform technique. The time-domain measures of HRV included the RMSSD and SDNN-index. Meanwhile, the frequency-domain measures included the total power (TP), HF, low frequency (LF), very low frequency (VLF), LF-to-HF (LF/HF) ratio, normalized LF (n-LF), normalized HF (n-HF), and standard deviation of the short axis of Poincaré plot (SD1), standard deviation of the long axis of Poincaré plot (SD2), and SD2-to-SD1 (SD2/SD1) ratio of HRV nonlinear measures. [
      • Shaffer F.
      • Ginsberg J.P.
      ] The TP is the sum of variance of all normal-to-normal (NN) intervals < 0.4 Hz. HF corresponds to a fluctuation of 0.15–0.4 Hz, whereas LF corresponds to a fluctuation of 0.04–0.15 Hz. VLF reflects the frequency of 0.003–0.04 Hz. The present study evaluated the differences in HRV measures between gender, different seizure onset types, and various ASMs. The correlation between HRV and age was also analyzed.

      Statistical analysis

      All statistical data were analyzed using JMP (version 12). Continuous variables such as age and HRV measures are expressed as mean ± standard deviation. Binary variables including gender, epilepsy type, and ASMs are expressed as number and percentage of patients. The continuous variables between different subgroups were compared using independent t test. The correlation between HRV measure and age was analyzed by simple linear regression. Further, p < 0.05 indicated statistical significance.

      Results

      Background information

      We screened 310 patients diagnosed with epilepsy. However, 256 patients were excluded because of the diagnosis, ASM polytherapy, and seizure episode 1 year prior. Ultimately, 54 patients were included for the analysis (Figure 1).
      Fig. 1.
      Fig. 1.Of the 310 screened patients diagnosed with epilepsy, 82, 117, and 57 were excluded because of the diagnosis, seizure episode 1 year prior to EEG, and ASM polytherapy. Hence, 54 patients were finally analyzed.
      The study population was composed of 30 females and 24 male patients. The mean age was 35.9 ± 14.8 years (18–76 years). Sodium channel blockers (phenytoin, 15 [27.8%]; lamotrigine, 10 [18.5%]; carbamazepine, 6 [11.1%]; and oxcarbazepine, 5 [9.3%]) were used by 36 (66.7%) patients. Meanwhile, broad-spectrum ASMs (valproate, 15 [27.8%]; levetiracetam, 3 [5.6%]) were used by 18 (33.3%) patients (Table 1).
      Table 1Background information.
      Characteristicsn%
      Female percentage3055.6%
      ASMs
      Sodium channel blockers
      Phenytoin1527.8%
      Lamotrigine1018.5%
      Carbamazepine611.1%
      Oxcarbazepine59.3%
      Broad-spectrum
      Valproate1527.8%
      Levetiracetam35.6%
      Seizure type
      Focal impaired awareness2851.9%
      Focal to bilateral tonic–clonic2342.6%
      Focal aware motor35.6%
      Epilepsy type
      Temporal lobe epilepsy2953.7%
      Frontal lobe epilepsy1731.5%
      Undetermined814.8%
      ASMs, antiseizure medications.

      Types of seizure and epilepsy

      According to the International League against Epilepsy classification, if awareness is impaired at any seizure point, the seizure type is focal impaired awareness seizure (FIAS). If a seizure starts in one area of the brain, then spreads to both sides of the brain as a tonic–clonic seizure, it is considered as a focal to bilateral tonic–clonic seizure (FBTCS). [
      • Fisher R.S.
      • Cross J.H.
      • D'Souza C.
      • et al.
      Instruction manual for the ILAE 2017 operational classification of seizure types.
      ] According to seizure semiology, 28 (51.9%) patients had FIAS, 23 (42.6%) had FBTCS, and 3 (5.6%) had focal awareness motor seizure. On the basis of seizure semiology and EEG focus, 29 (53.7%), 17 (31.5%), and 8 (14.8%) patients had temporal lobe epilepsy, frontal lobe epilepsy, and undetermined EEG focus, respectively (Table 1).

      HRV measures

      HRV between genders

      Females had lower HRV measures than males, but no statistically significant differences were observed in all HRV measures, including the mean age (p = 0.3220) (Table 2).
      Table 2Heart rate variability between genders.
      Male (n = 24)Female (n = 30)p value
      Age38.13 ± 14.5934.03 ± 14.960.322
      Time Domain
      RMSSD (ms)45.11 ± 33.8936.85 ± 20.420.301
      SDNN-index (ms)49.93 ± 28.0439.54 ± 18.770.133
      Frequency Domain
      LF (ms2)840.53 ± 889.16490.21 ± 578.290.104
      HF (ms2)1022.20 ± 1344.76506.24 ± 535.610.087
      LF/HF (%)1.76 ± 1.901.13 ± 0.670.136
      n-LF (ms2)0.51 ± 0.180.46 ± 0.150.283
      n-HF (ms2)0.45 ± 0.170.49 ± 0.140.385
      VLF (ms2)1061.47 ± 1056.31709.85 ± 903.750.191
      TP (ms2)2984.60 ± 3066.661752.13 ± 1756.380.097
      Poincaré Plot
      SD1 (ms)31.90 ± 23.9726.06 ± 14.440.305
      SD2 (ms)61.92 ± 33.4448.89 ± 23.240.116
      SD2/SD1 (%)2.47 ± 1.172.03 ± 0.580.119
      Data are expressed as mean ± standard deviation for continuous variables; Independent t test for continuous variables; *p < 0.05. RMSSD, square root of the mean of the sum of the squares of differences between adjacent normal-to-normal (NN) intervals; SDNN-index, standard deviation of all NN intervals index; n-LF, normalized low frequency; n-HF, normalized high frequency; LF/HF ratio, low frequency-to-high frequency ratio; LF, low frequency; HF, high frequency; VLF, very low frequency; TP, total power; SD1, standard deviation of the short axis of Poincaré plot; SD2, standard deviation of the long axis of Poincaré plot; SD1/SD2 ratio, SD1-to-SD2 ratio.

      HRV between ASMs

      All HRV measures were not significantly different between the sodium channel blockers group and the broad-spectrum ASMs group. Likewise, the mean age was not significantly different between the two groups (p = 0.907) (Table 3).
      Table 3Heart rate variability between different antiseizure medications.
      Sodium channel blockers (n = 36)Broad-spectrum ASMs (n = 18)p value
      Age35.67 ± 14.0536.22 ± 16.630.907
      Time Domain
      RMSSD (ms)37.82 ± 24.3745.92 ± 32.410.315
      SDNN-index (ms)43.44 ± 22.0845.60 ± 27.250.766
      Frequency Domain
      LF (ms2)634.43 ± 705.00668.87 ± 843.940.877
      HF (ms2)676.55 ± 916.52853.55 ± 1180.370.554
      LF/HF (%)1.60 ± 1.601.03 ± 0.660.166
      n-LF (ms2)0.51 ± 0.170.44 ± 0.140.192
      n-HF (ms2)0.45 ± 0.160.51 ± 0.130.237
      VLF (ms2)859.00 ± 996.81880.38 ± 976.650.946
      TP (ms2)2215.12 ± 2212.602469.45 ± 3008.750.738
      Poincaré Plot
      SD1 (ms)26.75 ± 17.2332.47 ± 22.920.314
      SD2 (ms)54.48 ± 27.4155.07 ± 31.940.947
      SD2/SD1 (%)2.37 ± 1.001.94 ± 0.640.102
      Data are expressed as mean ± standard deviation for continuous variables; Independent t test for continuous variables; *p < 0.05. RMSSD, square root of the mean of the sum of the squares of differences between adjacent normal-to-normal (NN) intervals; SDNN-index, standard deviation of all NN intervals index; n-LF, normalized low frequency; n-HF, normalized high frequency; LF/HF ratio, low frequency-to-high frequency ratio; LF, low frequency; HF, high frequency; VLF, very low frequency; TP, total power; SD1, standard deviation of the short axis of Poincaré plot; SD2, standard deviation of the long axis of Poincaré plot; SD2/SD1 ratio, SD2-to-SD1 ratio.

      HRV between FBTCS and FIAS

      Clinically, FBTCS and FIAS both exhibit consciousness disturbance. Therefore, to compare the HRV measures between these seizure types, we conducted a subgroup analysis. The mean age was not significantly different between these two groups (p = 0.388). Patients with FBTCS had a significantly lower HRV in RMSSD (p = 0.02), SDNN-index (p = 0.04), LF (p = 0.017), HF (p = 0.049), TP (p = 0.03), and SD1 (p = 0.024) than those with FIAS. Conversely, VLF was lower in patients with FBTCS, but the differences were not statistically significant (Table 4).
      Table 4Heart rate variability of different types of seizure.
      FIAS (n = 28)FBTCS (n = 23)p value
      Age35.88 ± 14.6539.71 ± 15.050.388
      Time Domain
      RMSSD (ms)44.70 ± 31.7628.48 ± 13.510.023*
      SDNN-index (ms)47.53 ± 26.8634.42 ± 14.660.046*
      Frequency Domain
      LF (ms2)778.73 ± 867.65320.71 ± 303.990.017*
      HF (ms2)1036.09 ± 1317.50293.32 ± 247.850.049*
      LF/HF (%)1.12 ± 0.751.76 ± 1.980.183
      n-LF (ms2)0.47 ± 0.130.49 ± 0.200.635
      n-HF (ms2)0.49 ± 0.120.45 ± 0.190.397
      VLF (ms2)833.04 ± 798.35659.42 ± 831.490.473
      TP (ms2)2709.03 ± 2927.041304.30 ± 1196.860.036*
      Poincaré Plot
      SD1 (ms)31.61 ± 22.4620.14 ± 9.560.024*
      SD2 (ms)58.59 ± 31.6943.71 ± 19.640.055
      SD2/SD1 (%)2.16 ± 0.872.42 ± 1.000.342
      Data are expressed as mean ± standard deviation for continuous variables; Independent t test for continuous variables; *p < 0.05. FBTCS, focal to bilateral tonic–clonic seizure; FIAS, focal impaired awareness seizure; RMSSD, square root of the mean of the sum of the squares of differences between adjacent normal-to-normal (NN) intervals; SDNN-index, standard deviation of all NN intervals index; n-LF, normalized low frequency; n-HF, normalized high frequency; LF/HF ratio, low frequency-to-high frequency ratio; LF, low frequency; HF, high frequency; VLF, very low frequency; TP, total power; SD1, standard deviation of the short axis of Poincaré plot; SD2, standard deviation of the long axis of Poincaré plot; SD1/SD2 ratio, SD1-to-SD2 ratio.

      Correlation between age and HRV by linear regression

      Age negatively correlated with HRV but significantly correlated with the RMSSD (r = −0.4463, p = 0.0007) and SDNN-index (r = −0.4919, p = 0.0002). Likewise, age significantly correlated with the LF, HF, VLF, and TP (r = −0.4499, p = 0.0006; r = −0.3952, p = 0.0031; r = −0.3799, p = 0.0046; and r = −0.4554, p = 0.0005, respectively) as well as with the SD1 (r = −0.4463, p = 0.0007) and SD2 (r = −0.4865, p = 0.0002) (Table 5).
      Table 5Correlation between age and HRV parameters.
      Index (unit)CorrelationLower 95%Upper 95%p value
      Time Domain
      RMSSD (ms)−0.4463−0.6378−0.20270.0007*
      SDNN-index (ms)−0.4919−0.6712−0.25810.0002*
      Frequency Domain
      LF (ms2)−0.4499−0.6405−0.20710.0006*
      HF (ms2)−0.3952−0.5995−0.14250.0031*
      LF/HF (%)0.0433−0.22710.30750.7558
      n-LF (ms2)0.1168−0.15580.37290.4003
      n-HF (ms2)−0.1339−0.38780.13880.3342
      VLF (ms2)−0.3799−0.5879−0.12480.0046*
      TP (ms2)−0.4554−0.6445−0.21360.0005*
      Poincaré Plot
      SD1 (ms)−0.4463−0.6378−0.20270.0007*
      SD2 (ms)−0.4865−0.6673−0.25150.0002*
      SD2/SD1 (%)0.1326−0.14020.38660.3393
      Data are expressed as correlation coefficients; *p < 0.05, considered statistically significant. RMSSD, square root of the mean of the sum of the squares of differences between adjacent normal-to-normal (NN) intervals; SDNN-index, standard deviation of all NN intervals index; n-LF, normalized low frequency; n-HF, normalized high frequency; LF/HF ratio, low frequency-to-high frequency ratio; LF, low frequency; HF, high frequency; VLF, very low frequency; TP, total power; SD1, standard deviation of the short axis of Poincaré plot; SD2, standard deviation of the long axis of Poincaré plot; SD1/SD2 ratio, SD1-to-SD2 ratio.

      Discussion

      The present study revealed that patients with FBTCS had a significantly lower HRV than those with FIAS. Patients with FBTCS had a lower HRV in terms of RMSSD, SDNN-index, LF, HF, TP, and SD1. Furthermore, HRV is negatively correlated with age. All HRV measures were also not significantly different between gender and ASMs. In addition, there was no significant difference in the mean age of patients with FIAS and FBTCS; therefore, changes in HRV attributed to age did not affect the present study results. In the general population, advanced age was associated with a decreased HRV. [
      • Zhang J.
      Effect of Age and Sex on Heart Rate Variability in Healthy Subjects.
      ]
      Almeida-Santos et al. found that SDNN and SDNN-index decreased linearly with age in 1743 people aged 40–100 years. [
      • Almeida-Santos M.A.
      • Barreto-Filho J.A.
      • Oliveira J.L.
      • et al.
      Aging, heart rate variability and patterns of autonomic regulation of the heart.
      ] HRV decrease may be a physiological change induced by normal aging; a longitudinal population‐based study concluded that HRV decreases with aging independent of comorbid diseases or medication use. [
      • Jandackova V.K.
      • Scholes S.
      • Britton A.
      • et al.
      Are Changes in Heart Rate Variability in Middle-Aged and Older People Normative or Caused by Pathological Conditions? Findings From a Large Population-Based Longitudinal Cohort Study.
      ]
      In the present study, females had lower values in most of the HRV measures than male patients, but the differences were not statistically significant. In the general population, advanced age may have a greater impact on HRV than gender. [
      • Zhang J.
      Effect of Age and Sex on Heart Rate Variability in Healthy Subjects.
      ] Although no interictal differences on HRV were found between genders in the present study, Behbahani et al. found that middle-age male patients had a significantly greater increase in pre-ictal HRV than middle-aged female patients, suggesting a higher sympathetic tone in male patients. [
      • Behbahani S.
      • Jafarnia Dabanloo N.
      • Motie Nasrabadi A.
      • et al.
      Gender-Related Differences in Heart Rate Variability of Epileptic Patients.
      ]
      In the present study, patients with FBTCS had a significantly lower HRV than those with FIAS. In the literature, there was hemisphere lateralization of the autonomic nervous system. Patients with left temporal lobe epilepsy have a lower HRV than those with right temporal lobe epilepsy. [
      • Dono F.
      • Evangelista G.
      • Frazzini V.
      • et al.
      Interictal Heart Rate Variability Analysis Reveals Lateralization of Cardiac Autonomic Control in Temporal Lobe Epilepsy.
      ] Ictal hypoxemia is more severe in seizures spreading to the contralateral hemisphere. [
      • Bateman L.M.
      • Li C.S.
      • Seyal M.
      Ictal hypoxemia in localization-related epilepsy: analysis of incidence, severity and risk factors.
      ] Ictal bradycardia is more often observed in seizures with bilateral hemisphere involvement than in seizures with focal involvement. [
      • Britton J.W.
      • Ghearing G.R.
      • Benarroch E.E.
      • et al.
      The ictal bradycardia syndrome: localization and lateralization.
      ] A recent study using arterial spin labeling magnetic resonance perfusion imaging found that FBTCS was associated with more frequent postictal hypoperfusion at the brainstem respiratory centers than FIAS. [
      • Liu J.
      • Peedicail J.S.
      • Gaxiola-Valdez I.
      • et al.
      Postictal brainstem hypoperfusion and risk factors for sudden unexpected death in epilepsy.
      ] FBTCS, which involves the hemisphere bilaterally, may cause more disturbed autonomic dysfunction than FIAS, which mainly involves the focal area or unilateral hemisphere of the brain. However, TLE patients with bitemporal seizure spreading could also present with FIAS. TLE can be a progressive disorder, [
      • Coan A.C.
      • Cendes F.
      Epilepsy as progressive disorders: what is the evidence that can guide our clinical decisions and how can neuroimaging help?.
      ] and the alternation of networks was correlated to the disease duration [
      • Morgan V.L.
      • Abou-Khalil B.
      • Rogers B.P.
      Evolution of functional connectivity of brain networks and their dynamic interaction in temporal lobe epilepsy.
      ]. A recent clinical study by Sinha et al. showed that TLE patients with FBTCS had significantly more widespread alternations in the brain network structure than patients without FBTCS [
      • Sinha N.
      • Peternell N.
      • Schroeder G.M.
      • et al.
      Focal to bilateral tonic-clonic seizures are associated with widespread network abnormality in temporal lobe epilepsy.
      ]. The authors concluded that the alternation of the brain networks in patients with FBTCS may result in a more rapid seizure spread.
      All HRV measures were not significantly different in the present study between patients receiving sodium channel blockers and those receiving broad-spectrum ASMs. Although carbamazepine reportedly increases the risk for autonomic dysfunctions. [
      • Persson H.
      • Ericson M.
      • Tomson T.
      Carbamazepine affects autonomic cardiac control in patients with newly diagnosed epilepsy.
      ] A meta-analysis revealed that HF and LF showed no significant difference between patients with and without ASMs. [
      • Lotufo P.A.
      • Valiengo L.
      • Bensenor I.M.
      • et al.
      A systematic review and meta-analysis of heart rate variability in epilepsy and antiepileptic drugs.
      ]
      This study revealed significant differences in HRV between patients with FIAS and FBTCS. Lower HRV in terms of RMSSD, SDNN-index, LF, HF, TP, and SD1 was found in patients with FBTCS than patients with FIAS. A recent study indicated that autonomic dysfunction in patients with epilepsy might cause impaired cerebral autoregulation. [
      • Chen S.F.
      • Pan H.Y.
      • Huang C.R.
      • et al.
      Autonomic Dysfunction Contributes to Impairment of Cerebral Autoregulation in Patients with Epilepsy.
      ] In addition, autonomic dysfunction in epilepsy may affect cardiorespiratory functions and lead to fatal impairments. [
      • Akyuz E.
      • Uner A.K.
      • Koklu B.
      • et al.
      Cardiorespiratory findings in epilepsy: A recent review on outcomes and pathophysiology.
      ,
      • Fialho G.L.
      • Wolf P.
      • Walz R.
      • et al.
      Increased cardiac stiffness is associated with autonomic dysfunction in patients with temporal lobe epilepsy.
      ] The causes of mortality in the epilepsy population may be multifactorial, and the link between HRV and sudden death in patients with epilepsy is still unclear. However, Suzuki et al. surveyed 855 patients with epilepsy and found that poor adherence to ASMs is associated with increased frequency of FBTCS and that patients aged 20–39 years were significantly more likely to be nonadherent to ASMs than the younger and older groups. [
      • Suzuki H.
      • Mikuni N.
      • Ohnishi H.
      • et al.
      Forgetting to take antiseizure medications is associated with focal to bilateral tonic-clonic seizures, as revealed by a cross-sectional study.
      ] According to the study of Cutillo et al., minimizing the frequency of FBTCS with appropriate ASM therapy may decrease the risk for sudden death in patients with epilepsy. [
      • Cutillo G.
      • Tolba H.
      • Hirsch L.J.
      Anti-seizure medications and efficacy against focal to bilateral tonic-clonic seizures: A systematic review with relevance for SUDEP prevention.
      ]

      Strength and limitations

      Regarding the strength of our study, we only included patients with focal seizures who were prescribed ASM monotherapy. Thus, our inclusion criteria controlled the influence of ASM drug-drug interactions. In addition, the study only analyzed the EKG segment during stage N1 or N2 sleep to avoid the EKG difference between sleep and awake.
      However, our study has some limitations. First, the sample size was small because we only included medically controlled patients receiving ASM monotherapy. Second, this study has a single-center design, thereby limiting the generalization of the results. Third, we did not differentiate primary from secondary epilepsy; various etiologies may influence HRV differently. Finally, we did not compare the HRV differences based on the location of epilepsy (i.e., temporal lobe epilepsy vs. frontal lobe epilepsy; right temporal vs. left temporal) because the main purpose of the study was to compare the HRV differences in subgroups according to semiology (FIAS vs. FBTC). Temporal lobe and frontal lobe epilepsies may include a range of seizure semiology. Additionally, we would like to emphasize that even in medically controlled focal seizures, different seizure semiology may carry varied autonomic dysfunctions.

      Conclusion

      Age was the predominant factor affecting the HRV of patients with epilepsy. FBTCS showed a significantly lower HRV than FIAS. Thus, patients with FBTCS may exhibit more disturbed autonomic regulation despite having medically controlled seizures than those with FIAS. However, more study is needed to elucidate the underlying mechanisms of interictal HRV between different subgroups of epilepsy.

      Declaration of Competing Interest

      The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

      References

        • Devinsky O.
        • Spruill T.
        • Thurman D.
        • et al.
        Recognizing and preventing epilepsy-related mortality: A call for action.
        Neurology. 2016; 86: 779-786
        • Fazel S.
        • Wolf A.
        • Langstrom N.
        • et al.
        Premature mortality in epilepsy and the role of psychiatric comorbidity: a total population study.
        Lancet. 2013; 382: 1646-1654
        • Cygankiewicz I.
        • Zareba W.
        Heart rate variability.
        Handb Clin Neurol. 2013; 117: 379-393
        • Shaffer F.
        • Ginsberg J.P.
        An Overview of Heart Rate Variability Metrics and Norms. 5. Front Public Health, 2017: 258
        • Ernst G.
        Heart-Rate Variability-More than Heart Beats?5. Front Public Health, 2017: 240
        • Kim H.G.
        • Cheon E.J.
        • Bai D.S.
        • et al.
        Stress and Heart Rate Variability: A Meta-Analysis and Review of the Literature.
        Psychiatry Investig. 2018; 15: 235-245
        • La Rovere M.T.
        • Pinna G.D.
        • Maestri R.
        • et al.
        Short-term heart rate variability strongly predicts sudden cardiac death in chronic heart failure patients.
        Circulation. 2003; 107: 565-570
        • Keezer M.R.
        • Sisodiya S.M.
        • Sander J.W.
        Comorbidities of epilepsy: current concepts and future perspectives.
        Lancet Neurol. 2016; 15: 106-115
        • Myers K.A.
        • Sivathamboo S.
        • Perucca P.
        Heart rate variability measurement in epilepsy: How can we move from research to clinical practice?.
        Epilepsia. 2018; 59: 2169-2178
        • do Nascimento Vinholes L.
        • Sousa da Silva A.
        • Tassi E.Marinho
        • et al.
        Heart rate variability in frontal lobe epilepsy: Association with SUDEP risk.
        Acta Neurol Scand. 2021; 143: 62-70
        • Sivathamboo S.
        • Perucca P.
        Interictal autonomic dysfunction.
        Curr Opin Neurol. 2021; 34: 197-205
        • Sivakumar S.S.
        • Namath A.G.
        • Tuxhorn I.E.
        • et al.
        Decreased heart rate and enhanced sinus arrhythmia during interictal sleep demonstrate autonomic imbalance in generalized epilepsy.
        J Neurophysiol. 2016; 115: 1988-1999
        • Lotufo P.A.
        • Valiengo L.
        • Bensenor I.M.
        • et al.
        A systematic review and meta-analysis of heart rate variability in epilepsy and antiepileptic drugs.
        Epilepsia. 2012; 53: 272-282
        • Tang F.
        • Hartz A.M.S.
        • Bauer B.
        Drug-Resistant Epilepsy: Multiple Hypotheses, Few Answers.
        Front Neurol. 2017; 8: 301
        • Kananen J.
        • Tuovinen T.
        • Ansakorpi H.
        • et al.
        Altered physiological brain variation in drug-resistant epilepsy.
        Brain Behav. 2018; 8: e01090
        • Ansakorpi H.
        • Korpelainen J.T.
        • Huikuri H.V.
        • et al.
        Heart rate dynamics in refractory and well controlled temporal lobe epilepsy.
        J Neurol Neurosurg Psychiatry. 2002; 72: 26-30
        • Persson H.
        • Ericson M.
        • Tomson T.
        Carbamazepine affects autonomic cardiac control in patients with newly diagnosed epilepsy.
        Epilepsy Res. 2003; 57: 69-75
        • Litovchenko T.
        • Grymailo V.
        • Tondiy O.
        • et al.
        The peculiarities of the heart rate variability and electroencephalogram changes in patients with epilepsy and cardiovascular pathology.
        Wiad Lek. 2019; 72: 165-168
        • Kwan P.
        • Arzimanoglou A.
        • Berg A.T.
        • et al.
        Definition of drug resistant epilepsy: consensus proposal by the ad hoc Task Force of the ILAE Commission on Therapeutic Strategies.
        Epilepsia. 2010; 51: 1069-1077
        • Sills G.J.
        • Rogawski M.A.
        Mechanisms of action of currently used antiseizure drugs.
        Neuropharmacology. 2020; 168107966
        • Fisher R.S.
        • Cross J.H.
        • D'Souza C.
        • et al.
        Instruction manual for the ILAE 2017 operational classification of seizure types.
        Epilepsia. 2017; 58: 531-542
        • Zhang J.
        Effect of Age and Sex on Heart Rate Variability in Healthy Subjects.
        Journal of Manipulative & Physiological Therapeutics. 2007; 30: 374-379
        • Almeida-Santos M.A.
        • Barreto-Filho J.A.
        • Oliveira J.L.
        • et al.
        Aging, heart rate variability and patterns of autonomic regulation of the heart.
        Arch Gerontol Geriatr. 2016; 63: 1-8
        • Jandackova V.K.
        • Scholes S.
        • Britton A.
        • et al.
        Are Changes in Heart Rate Variability in Middle-Aged and Older People Normative or Caused by Pathological Conditions? Findings From a Large Population-Based Longitudinal Cohort Study.
        J Am Heart Assoc. 2016; 5
        • Behbahani S.
        • Jafarnia Dabanloo N.
        • Motie Nasrabadi A.
        • et al.
        Gender-Related Differences in Heart Rate Variability of Epileptic Patients.
        Am J Mens Health. 2018; 12: 117-125
        • Dono F.
        • Evangelista G.
        • Frazzini V.
        • et al.
        Interictal Heart Rate Variability Analysis Reveals Lateralization of Cardiac Autonomic Control in Temporal Lobe Epilepsy.
        Front Neurol. 2020; 11: 842
        • Bateman L.M.
        • Li C.S.
        • Seyal M.
        Ictal hypoxemia in localization-related epilepsy: analysis of incidence, severity and risk factors.
        Brain. 2008; 131: 3239-3245
        • Britton J.W.
        • Ghearing G.R.
        • Benarroch E.E.
        • et al.
        The ictal bradycardia syndrome: localization and lateralization.
        Epilepsia. 2006; 47: 737-744
        • Liu J.
        • Peedicail J.S.
        • Gaxiola-Valdez I.
        • et al.
        Postictal brainstem hypoperfusion and risk factors for sudden unexpected death in epilepsy.
        Neurology. 2020; 95: e1694-e1705
        • Coan A.C.
        • Cendes F.
        Epilepsy as progressive disorders: what is the evidence that can guide our clinical decisions and how can neuroimaging help?.
        Epilepsy & Behavior. 2013; 26: 313-321
        • Morgan V.L.
        • Abou-Khalil B.
        • Rogers B.P.
        Evolution of functional connectivity of brain networks and their dynamic interaction in temporal lobe epilepsy.
        Brain connectivity. 2015; 5: 35-44
        • Sinha N.
        • Peternell N.
        • Schroeder G.M.
        • et al.
        Focal to bilateral tonic-clonic seizures are associated with widespread network abnormality in temporal lobe epilepsy.
        Epilepsia. 2021; 62: 729-741
        • Chen S.F.
        • Pan H.Y.
        • Huang C.R.
        • et al.
        Autonomic Dysfunction Contributes to Impairment of Cerebral Autoregulation in Patients with Epilepsy.
        J Pers Med. 2021; 11
        • Akyuz E.
        • Uner A.K.
        • Koklu B.
        • et al.
        Cardiorespiratory findings in epilepsy: A recent review on outcomes and pathophysiology.
        J Neurosci Res. 2021;
        • Fialho G.L.
        • Wolf P.
        • Walz R.
        • et al.
        Increased cardiac stiffness is associated with autonomic dysfunction in patients with temporal lobe epilepsy.
        Epilepsia. 2018; 59: e85-e90
        • Suzuki H.
        • Mikuni N.
        • Ohnishi H.
        • et al.
        Forgetting to take antiseizure medications is associated with focal to bilateral tonic-clonic seizures, as revealed by a cross-sectional study.
        PLoS One. 2020; 15e0240082
        • Cutillo G.
        • Tolba H.
        • Hirsch L.J.
        Anti-seizure medications and efficacy against focal to bilateral tonic-clonic seizures: A systematic review with relevance for SUDEP prevention.
        Epilepsy Behav. 2021; 117107815