T-wave heterogeneity crescendo in the surface EKG is superior to heart rate acceleration for seizure prediction

AI in ECG: Validating an ambulatory semiology labeller and predictor

OBJECTIVES

Early prediction of epileptic seizures can help reduce morbidity and mortality. In this work, we explore using electrocardiographic (ECG) signal as input to a seizure prediction system and note that the performance can be improved by using selected signal processing techniques.

METHODS

We used frequency domain analysis with a deep neural network backend for all our experiments in this work. We further analysed the effect of the proposed system for different seizure semiologies and prediction horizons. We explored refining the signal using signal processing to enhance the system's performance.

RESULTS

Our final system using the Temple University Hospital's Seizure (TUHSZ) corpus gave an overall prediction accuracy of 84.02 %, sensitivity of 87.59 %, specificity of 81.9 %, and an area under the receiver operating characteristic curve (AUROC) of 0.9112. Notably, these results surpassed the state-of-the-art outcomes reported using the TUHSZ database; all findings are statistically significant. We also validated our study using the Siena scalp EEG database. Using the frequency domain data, our baseline system gave a performance of 75.17 %, 79.17 %, 70.04 % and 0.82 for prediction accuracy, sensitivity, specificity and AUROC, respectively. After selecting the optimal frequency band of 0.8-15 Hz, we obtained a performance of 80.49 %, 89.51 %, 75.23 % and 0.89 for prediction accuracy, sensitivity, specificity and AUROC, respectively which is an improvement of 5.32 %, 10.34 %, 5.19 % and 0.08 for prediction accuracy, sensitivity, specificity and AUROC, respectively.

CONCLUSIONS

The seizure information in ECG is concentrated in a narrow frequency band. Identifying and selecting that band can help improve the performance of seizure detection and prediction.

SIGNIFICANCE

EEG is susceptible to artefacts and is not preferred in a low-cost ambulatory device. ECG can be used in wearable devices (like chest bands) and is feasible for developing a low-cost ambulatory device for seizure prediction. Early seizure prediction can provide patients and clinicians with the required alert to take necessary precautions and prevent a fatality, significantly improving the patient's quality of life.

The epileptic heart: Cardiac comorbidities and complications of epilepsy. Atrial and ventricular structure and function by echocardiography in individuals with epilepsy - From clinical implications to individualized assessment

Epilepsy is an increasing global neurological health issue. Recently, epidemiological and mechanistic studies have raised concern about cardiac involvement in individuals with epilepsy. This has resulted in the "epileptic heart" concept. Epidemiological data linking epilepsy to cardiovascular disease indicate an increased risk for ventricular and atrial arrhythmias, myocardial infarction, heart failure, and sudden death among individuals with epilepsy. Pathways of this interaction comprise increased prevalence of traditional cardiac risk factors, genetic abnormalities, altered brain circuitry with autonomic imbalance, and antiseizure medications with enzyme-inducing and ionic channel-blocking proprieties. Pathophysiological findings in the atria and ventricles of patients with epilepsy are discussed. Echocardiographic findings and future applications of this tool are reviewed. A risk stratification model and future studies on cardiac risk assessment in individuals with epilepsy are proposed.

Individuals with chronic epilepsy have elevated P-wave heterogeneity comparable to patients with atrial fibrillation

OBJECTIVE

Identification of epilepsy patients with elevated risk for atrial fibrillation (AF) is critical given the heightened morbidity and premature mortality associated with this arrhythmia. Epilepsy is a worldwide health problem affecting nearly 3.4 million people in the United States alone. The potential for increased risk for AF in patients with epilepsy is not well appreciated, despite recent evidence from a national survey of 1.4 million hospitalizations indicating that AF is the most common arrhythmia in people with epilepsy.

METHODS

We analyzed inter-lead heterogeneity of P-wave morphology, a marker reflecting arrhythmogenic nonuniformities of activation/conduction in atrial tissue. The study groups consisted of 96 patients with epilepsy and 44 consecutive patients with AF in sinus rhythm before clinically indicated ablation. Individuals without cardiovascular or neurological conditions (n = 77) were also assessed. We calculated P-wave heterogeneity (PWH) by second central moment analysis of simultaneous beats from leads II, III, and aVR ("atrial dedicated leads") from standard 12-lead electrocardiography (ECG) recordings from admission day to the epilepsy monitoring unit (EMU).

RESULTS

Female patients composed 62.5%, 59.6%, and 57.1% of the epilepsy, AF, and control subjects, respectively. The AF cohort was older (66 ± 1.1 years) than the epilepsy group (44 ± 1.8 years, p < .001). The level of PWH was greater in the epilepsy group than in the control group (67 ± 2.6 vs. 57 ± 2.5 μV, p = .046) and reached levels observed in AF patients (67 ± 2.6 vs. 68 ± 4.9 μV, p = .99). In multiple linear regression analysis, PWH levels in individuals with epilepsy were mainly correlated with the PR interval and could be related to sympathetic tone. Epilepsy remained associated with PWH after adjustments for cardiac risk factors, age, and sex.

SIGNIFICANCE

Patients with chronic epilepsy have increased PWH comparable to levels observed in patients with AF, while being ~20 years younger, suggesting an acceleration in structural change and/or cardiac electrical instability. These observations are consistent with emerging evidence of an "epileptic heart" condition.

Epileptic seizures and Epilepsy Monitoring Unit admission disclose latent cardiac electrical instability

BACKGROUND

Sudden cardiac arrest results from cardiac electrical instability and is 3-fold more frequent in patients with chronic epilepsy than in the general population. We hypothesized that focal to bilateral tonic-clonic seizures (FTBTCS) would acutely impact T-wave alternans (TWA), a marker of cardiac electrical instability linked to an elevated risk for sudden cardiac death, more than focal seizures (FS) [focal aware seizures (FAS) and focal with impaired awareness seizures (FIAS)], due to their greater sympathetic stimulation of the heart. Since stress has been shown to cause significant TWA elevations in patients with heart disease, we also hypothesized that the early days of an inpatient admission to an epilepsy monitoring unit (EMU) would be associated with higher TWA levels compared to later hospital days in patients with chronic epilepsy, presumably due to stress.

DESIGN/METHODS

We analyzed the acute effects of seizures [FAS, FIAS, FTBTCS, and nonepileptic seizures (NES)] and day of hospital stay on TWA in 18 patients admitted to the EMU using high-resolution wireless electrocardiographic (ECG) patch monitors.

RESULTS

A total of 5 patients had FTBTCS, 7 patients had FS (2 FAS, 5 FIAS), and 3 patients had NES only during the index hospital stay. Four patients did not have any electroclinical seizures or NES. FTBTCS resulted in marked acute increases in ictal TWA from baseline (2 ± 0.3 µV) to ictal maximum (70 ± 6.1 µV, p < 0.0001), the latter exceeding the 60 µV cut point defined as severely abnormal. By comparison, while FAS and FIAS also provoked significant increases in TWA (from 2 ± 0.5 µV to 30 ± 3.3 µV, p < 0.0001), maximum ictal TWA levels did not reach the 47 µV cut point defined as abnormal. Heart rate increases during FTBTCS from baseline (62 ± 5.8 beats/min) to ictal maximum (134 ± 8.6 beats/min, an increase of 72 ± 7.2 beats/min, p < 0.02) were also greater (p = 0.014) than heart rate increases during FS (from 70 ± 5.2 beats/min to 118 ± 6.2 beats/min, an increase of 48 ± 2.6 beats/min, p < 0.03). In 3 patients with NES, TWA rose mildly during the patients' typical episodes (from 2 ± 0.6 µV to 14 ± 2.6 µV, p < 0.0004), well below the cut point of abnormality, while heart rate increases were observed (from 75 ± 1.3 to 112 ± 8.7 beats/min, an increase of 37 ± 8.9 beats/min, p = 0.03). Patients with EEG-confirmed electroclinical seizures recorded while in the EMU exhibited significantly elevated interictal TWA maxima (61 ± 3.4 µV) on EMU admission day which were similar in magnitude to ictal maxima seen during FTBTCS (70 ± 6.1 µV, p = 0.21). During subsequent days of hospitalization, daily interictal TWA maxima showed gradual habituation in patients with both FS and FTBTCS but not in patients with NES only.

CONCLUSIONS

This is the first study to our knowledge demonstrating that FTBTCS acutely provoke highly significant increases in TWA to levels that have been associated with heightened risk for sudden cardiac death in other patient populations. We speculate that mortality temporally associated with FTBTCS may, in some cases, be due to sudden cardiac death rather than respiratory failure. In patients with EEG-confirmed epilepsy, hospital admission is associated with interictal TWA maxima that approach those seen during FTBTCS, presumably related to stress during the early phase of hospitalization compared to later in the hospitalization, indicating cardiac electrical instability and potential vulnerability to sudden cardiac death related to stress independent of temporal relationships to seizures. The elevated heart rates observed acutely with seizures and on hospital Day 1 are consistent with a hyperadrenergic state and the effect of elevated sympathetic output on a vulnerable cardiac substrate, a phenomenon termed "the Epileptic Heart."