Search Results (3)

Depolarization-blocking drugs (DB drugs) used for cardiac disease increase the risk of cardiac arrhythmia (ventricular tachycardia/ventricular fibrillation [VT/VF]) and out-of-hospital cardiac arrest (OHCA) in specific patient groups. However, it is unknown whether drugs for non-cardiac disease that block cardiac depolarization as the off-target effect increase the risk of OHCA on a population level. Therefore, we aimed to investigate OHCA risk of non-cardiac, DB drugs in the community. We conducted a population-based case-control study. We included OHCA cases from an emergency-medical-services-attended OHCA registry in the Netherlands (ARREST:2009–2018), and age/sex/OHCA-date matched non-OHCA controls. We calculated adjusted odds ratios (OR_adj) of use of non-cardiac DB drugs for OHCA using conditional logistic regression. Stratified analyses were performed according to first-registered rhythm (VT/VF or non-VT/VF), sex, and age (≤50, 50–70, or ≥70 years). We included 5473 OHCA cases of whom 427 (7.8%) used non-cardiac, DB drugs and 21,866 non-OHCA controls of whom 835 (3.8%) used non-cardiac, DB drugs and found that non-cardiac, DB-drug use was associated with increased OHCA-risk when compared to no use (OR_adj1.6[95%-CI:1.4–1.9]). Stratification by first-recorded rhythm revealed that this applied to OHCA with non-VT/VF (asystole) (OR_adj2.5[95%-CI:2.1–3.0]) but not with VT/VF (OR_adj1.0[95%-CI:0.8–1.2]; p-value interaction < 0.001). The risk was higher in women (OR_adj1.8[95%-CI:1.5–2.2] than in men (OR_adj1.5[95%-CI:1.2–1.8]; p-value interaction = 0.030) and at younger ages (OR_adj≥70yrs1.4[95%-CI:1.2–1.7]; OR_{adj50–70yrs}1.7[95%-CI:1.4–2.1]; OR_adj≤50yrs3.2[95%-CI:2.1–5.0]; p-value interaction < 0.001). Use of non-cardiac, DB drugs is associated with increased OHCA risk. This increased risk occurred in patients in whom non-VT/VF was the first-registered rhythm, and it occurred in both sexes but more prominently among women and more strongly in younger patients (≤50 years). Full article

Computer modeling of the electrophysiology of the heart has undergone significant progress. A healthy heart can be modeled starting from the ion channels via the spread of a depolarization wave on a realistic geometry of the human heart up to the potentials on the body surface and the ECG. Research is advancing regarding modeling diseases of the heart. This article reviews progress in calculating and analyzing the corresponding electrocardiogram (ECG) from simulated depolarization and repolarization waves. First, we describe modeling of the P-wave, the QRS complex and the T-wave of a healthy heart. Then, both the modeling and the corresponding ECGs of several important diseases and arrhythmias are delineated: ischemia and infarction, ectopic beats and extrasystoles, ventricular tachycardia, bundle branch blocks, atrial tachycardia, flutter and fibrillation, genetic diseases and channelopathies, imbalance of electrolytes and drug-induced changes. Finally, we outline the potential impact of computer modeling on ECG interpretation. Computer modeling can contribute to a better comprehension of the relation between features in the ECG and the underlying cardiac condition and disease. It can pave the way for a quantitative analysis of the ECG and can support the cardiologist in identifying events or non-invasively localizing diseased areas. Finally, it can deliver very large databases of reliably labeled ECGs as training data for machine learning. Full article

Tiagabine is an antiepileptic drug used for the treatment of partial seizures in humans. Recently, this drug has been found useful in several non-epileptic conditions, including anxiety, chronic pain and sleep disorders. Since tachycardia—an impairment of cardiac rhythm due to cardiac ion channel dysfunction—is one of the most commonly reported non-neurological adverse effects of this drug, in the present paper we have undertaken pharmacological and numerical studies to assess a potential cardiovascular risk associated with the use of tiagabine. A chemical interaction of tiagabine with a model of human voltage-gated ion channels (VGICs) is described using the molecular docking method. The obtained in silico results imply that the adverse effects reported so far in the clinical cardiological of tiagabine could not be directly attributed to its interactions with VGICs. This is also confirmed by the results from the isolated organ studies (i.e., calcium entry blocking properties test) and in vivo (electrocardiogram study) assays of the present research. It was found that tachycardia and other tiagabine-induced cardiac complications are not due to a direct effect of this drug on ventricular depolarization and repolarization. Full article