Heart rate changes during partial seizures: a study amongst Singaporean patients

Corrected QT interval and QT dispersion in temporal lobe epilepsy

Background

Cardiac arrhythmias are expected among patients with epilepsy due to the effect of anti-epileptic drugs. Temporal lobe epilepsy also causes autonomic seizures that may affect heart rhythm. Prolongation of the corrected QT interval and QT dispersion is a risk factor for cardiac arrhythmia.

Objectives

We aimed to assess corrected QT interval and QT dispersion in patients with epilepsy and if there is a difference between patients with temporal epilepsy versus non-temporal epilepsy.

Methods

This study was conducted on 100 patients (50 patients with temporal epilepsy and 50 patients with non-temporal epilepsy) and 50 age- and sex-matched healthy controls. They underwent a prolonged (6 to 24 h) 22 channel computerized electroencephalogram monitor with a 10–20 system. QT dispersion, QT interval, and corrected QT interval (using Bazett’s formula) were calculated.

Results

This study showed significantly higher QT dispersion and corrected QT interval in patients with epilepsy when compared to the age- and sex-matched control group (P < 0.001, P < 0.001). Also, the corrected QT interval and QT dispersion were significantly higher in temporal epilepsy patients when compared to the non-temporal group (P < 0.001, P < 0.001).

Conclusion

Corrected QT interval and QT dispersion are higher in epileptic patients and more among temporal epilepsy patients in comparison to non-temporal epilepsy patients.

Pre-ictal heart rate changes: A systematic review and meta-analysis

PURPOSE

To estimate the incidence of pre-ictal heart rate (HR) manifestations and to identify clinical and study-related factors modulating the estimate.

METHODS

We searched articles recording concurrent pre-ictal EEG and HR in adults and children with epilepsy. Pre-ictal HR changes were classified as HR reduction (HRR) or increase (HRI). Studies reporting the total number of seizures and the number of seizures with pre-ictal HR changes were included in a random-effects meta-analysis. A random-effects meta-regression was used to identify variables affecting study heterogeneity.

RESULTS

Thirty studies, including 1110 participants and 2957 seizures, were included. The meta-analysis showed a pooled incidence of pre-ictal HRI of 36/100 seizures (95% CI 22-50). The pre-ictal HRI incidence was 44/100 seizures (95% CI 33-55) in studies including temporal lobe epilepsy, 55/100 seizures (95% CI 41-68) in studies enrolling adults and 35/100 seizures (95% CI 16-58) when patients on antiepileptic drugs were included. The meta-regression showed that the age group, the length of the pre-ictal period, the incidence of ictal tachycardia and the time of onset of the pre-ictal HRI had a significant impact on estimates variability. The pooled incidence of pre-ictal HRR was 0/100 seizures (95% CI 0-1).

CONCLUSION

Review of bias evaluation and methods assessment disclosed several major limitations in the evidence-base. HR monitoring could be valuable to identify seizures prior to their apparent onset, opening the possibility to early interventions. Additional effort is necessary to delineate the target population who might benefit from its use and the mechanisms sustaining the pre-ictal cardiac changes.

Comparison of heart rate changes with ictal tachycardia seizures in adults and children

PURPOSE

Lower heart rate variability (HRV) is known to make patients more susceptible to tachycardia and possibly sudden unexpected death in epilepsy (SUDEP). The heart rate (HR) at which tachycardia is present may vary by age. To date, no study has been done comparing adult and child seizures at different time points. The purpose of this study was to compare the frequency of HR changes with ictal tachycardia (IT) seizures at different time points in adults versus children.

METHODS

We retrospectively assessed the changes in the HR of 99 IT seizures in children and 96 IT seizures in adults. The difference between adults and children in gender, hemispheric lateralization or sleep/wakefulness, or seizure type on the HR changes and the difference between children and adults during 10 s preictal, ictal onset, and ictal and 60 s postictal were separately assessed.

RESULTS

The HR difference and maximum HR increase with aging in children. The seizure duration in adults lasted longer as compared with that in children. There are higher HR at different points and HR difference at 10 s preictal as compared to baseline in children.

CONCLUSIONS

The study illustrates that age and duration were respectively related to HR differences distinguishing children from adults. There may be an age-related effect of HR changes associated with seizures, with higher HR at different times and HR difference at 10 s before seizure onset as compared to baseline in children, which might explain that children are more likely to predict epileptic seizures than adults, contributing to subclinical seizures and treatment efficiency in refractory patients.

Heart rate changes in partial seizures: analysis of influencing factors among refractory patients

Background

We analyzed the frequency of heart rate (HR) changes related to seizures, and we sought to identify the influencing factors of these changes during partial seizures, to summarize the regularity of the HR changes and gain some insight into the mechanisms involved in the neuronal regulation of cardiovascular function. To date, detailed information on influencing factors of HR changes related to seizures by multiple linear regression analysis remains scarce.

Methods

Using video-electroencephalograph (EEG)-electrocardiograph (ECG) recordings, we retrospectively assessed the changes in the HR of 81 patients during a total of 181 seizures, including 27 simple partial seizures (SPS), 110 complex partial seizures (CPS) and 44 complex partial seizures secondarily generalized (CPS-G). The epileptogenic focus and the seizure type, age, gender, and sleep/wakefulness state of each patient were evaluated during and after the seizure onset. The HR changes were evaluated in the stage of epilepsy as time varies.

Results

Of the 181 seizures from 81 patients with ictal ECGs, 152 seizures (83.98%) from 74 patients were accompanied by ictal tachycardia (IT). And only 1 patient was accompanied by ictal bradycardia (IB). A patient has both IT and IB. We observed that HR difference was independently correlated with side, type and sleep/wakefulness state. In this analysis, the HR changes were related to the side, gender, seizure type, and sleep/wakefulness state. Right focus, male, sleep, and CPS-G showed more significant increases than that were observed in left, female, wakefulness, SPS and CPS. HR increases rapidly within 10 seconds before seizure onset and ictus, and typically slows to normal with seizure offset.

Conclusion

CPS-G, sleep and right focus led to higher ictal HR. The HR in the stage of epilepsy has regularly been observed to change to become time-varying. The risk factors of ictal HR need to be controlled along with sleep, CPS-G and right focus. Our study first explains that the HR in seizures has a regular evolution varying with time. Our study might help to further clarify the basic mechanisms of interactions between heart and brain, making seizure detection and closed-loop systems a possible therapeutic alternative in refractory patients.

Ictal tachycardia: the head-heart connection

Epileptic seizures can lead to changes in autonomic function affecting the sympathetic, parasympathetic, and enteric nervous systems. Changes in cardiac signals are potential biomarkers that may provide an extra-cerebral indicator of ictal onset in some patients. Heart rate can be measured easily when compared to other biomarkers that are commonly associated with seizures (e.g., long-term EEG), and therefore it has become an interesting parameter to explore for detecting seizures. Understanding the prevalence and magnitude of heart rate changes associated with seizures, as well as the timing of such changes relative to seizure onset, is fundamental to the development and use of cardiac based algorithms for seizure detection. We reviewed 34 articles that reported the prevalence of ictal tachycardia in patients with epilepsy. Scientific literature supports the occurrence of significant increases in heart rate associated with ictal events in a large proportion of patients with epilepsy (82%) using concurrent electroencephalogram (EEG) and electrocardiogram (ECG). The average percentage of seizures associated with significant heart rate changes was similar for generalized (64%) and partial onset seizures (71%). Intra-individual variability was noted in several articles, with the majority of studies reporting significant increase in heart rate during seizures originating from the temporal lobe. Accurate detection of seizures is likely to require an adjustable threshold given the variability in the magnitude of heart rate changes associated with seizures within and across patients.