Generalized tonic-clonic seizures with post-ictal atrial fibrillation

The brain-heart connection: Value of concurrent ECG and EEG recordings in epilepsy management

Concurrent electrocardiogram (ECG) and electroencephalogram (EEG) recording both ictally and interictally has significant value in the comprehensive management of epilepsy. This review highlights the diagnostic utility of simultaneous ECG and EEG monitoring in differentiating between epileptic and cardiac events, detecting cardiac abnormalities, and identifying autonomic dysfunction. The critical role of this combined approach to defining the mechanisms underlying cardiac morbidity and sudden cardiac death in patients with epilepsy and in guiding therapeutic interventions is underscored. The "Epileptic Heart Syndrome" is examined, illustrating how chronic epilepsy can adversely affect cardiac structure and function, leading to increased risk for interictal cardiac arrhythmias, morbidities, and mortality. The findings emphasize the need for standardized protocols for routine concurrent ECG and EEG recording in epilepsy monitoring units both ictally and interictally to ensure comprehensive patient care, improve diagnostic accuracy, and potentially reduce epilepsy-related morbidity and mortality. Future research directions are proposed to address existing gaps and to advance the technology and methodology for concurrent monitoring including wearable and computer-based monitoring systems.

Mapping of Neuro-Cardiac Electrophysiology: Interlinking Epilepsy and Arrhythmia

The interplay between neurology and cardiology has gained significant attention in recent years, particularly regarding the shared pathophysiological mechanisms and clinical comorbidities observed in epilepsy and arrhythmias. Neuro-cardiac electrophysiology mapping involves the comprehensive assessment of both neural and cardiac electrical activity, aiming to unravel the intricate connections and potential cross-talk between the brain and the heart. The emergence of artificial intelligence (AI) has revolutionized the field by enabling the analysis of large-scale data sets, complex signal processing, and predictive modeling. AI algorithms have been applied to neuroimaging, electroencephalography (EEG), electrocardiography (ECG), and other diagnostic modalities to identify subtle patterns, classify disease subtypes, predict outcomes, and guide personalized treatment strategies. In this review, we highlight the potential clinical implications of neuro-cardiac mapping and AI in the management of epilepsy and arrhythmias. We address the challenges and limitations associated with these approaches, including data quality, interpretability, and ethical considerations. Further research and collaboration between neurologists, cardiologists, and AI experts are needed to fully unlock the potential of this interdisciplinary field.

Epilepsy and long-term risk of arrhythmias

BACKGROUND AND AIMS

Previous evidence has mainly supported transient changes in cardiac function during interictal or peri-ictal phases in people with epilepsy, but the long-term risk of cardiac arrhythmias is poorly described. This study aimed to assess the long-term association of epilepsy with cardiac arrhythmias, considering the potential role of genetic predisposition and antiseizure medications (ASMs) in any associations observed.

METHODS

This population-based study evaluated UK Biobank data for individuals recruited between 2006 and 2010. Cox proportional hazards models and competing risk models were used to examine the association of epilepsy history with the long-term incidence risk of cardiac arrhythmias and arrhythmias subtypes. Polygenic risk scores (PRS) were calculated to investigate the effect of genetic susceptibility. The role of ASMs was also evaluated by integrating observational and drug target Mendelian randomization (MR) evidence.

RESULTS

The study included 329 432 individuals, including 2699 people with epilepsy. Compared with those without epilepsy, people with epilepsy experienced an increased risk of all cardiac arrhythmias [hazard ratio (HR) 1.36, 95% confidence interval (CI) 1.21-1.53], atrial fibrillation (HR 1.26, 95% CI 1.08-1.46), and other cardiac arrhythmias (HR 1.56, 95% CI 1.34-1.81). The associations were not modified by genetic predisposition as indicated by PRS. Competing and sensitivity analyses corroborated these results. Individuals with epilepsy using ASMs, especially carbamazepine and valproic acid, were at a higher risk for cardiac arrhythmias. This observation was further supported by drug target MR results (PSMR < .05 and PHEIDI > .05).

CONCLUSION

This study revealed the higher risk of cardiac arrhythmias persists long term in people with epilepsy, especially among those using carbamazepine and valproic acid. These findings highlight the need for regular heart rhythm monitoring and management in people with epilepsy in order to reduce the risk of further cardiovascular complications.

Left Ventricular Noncompaction Cardiomyopathy as a Potential Cause of Bilateral Posterior Cerebral Artery Stroke - a Rare and Unique Clinical Occurrence

Patient: Male, 63-year-old

Final Diagnosis: Occurrence of bilateral PCA infarcts with LVNC cardiomyopathy

Symptoms: Acute vision loss in both eyes • dysarthria

Medication: —

Clinical Procedure: Emergency endovascular thrombectomy

Specialty: Neurology