Fabio M. Leonelli

Melphalan-Induced Supraventricular Tachycardia: Incidence and Risk Factors

Cardiotoxicity of aggressive chemotherapeutic regimens includes cardiomyopathy and arrhythmias. Although cardiomyopathy is a well‐recognized entity, arrhythmias are poorly studied.

Hyperkalemia During Cardiac Pacing

In this issue of the Journal, McVenes et al.1 report the effect of hyperkalemia and hypernatremia in dogs with transvenous dual chamber pacemakers. On one hand, during NaCl infusion (Na+ increased 10% from 143 ± 3 to 158 ± 5 mEq/L), they found no changes in atrial or ventricular pacing thresholds, associated with a 20% decrease in pacing impedance. The amplitude of the atrial electrogram decreased 32–36% while that of the ventricular electrogram decreased 25% and its slew rate decreased by about the same amount. These changes are interesting but of little clinical significance because the degree of hypernatremia attained in the study is rare in clinical practice. On the other hand, the experimental observations of McVenes et al.1 on the effect of potassium infusions are important because hyperkalemia is a common clinical problem in pacemaker patients especially in the setting of heart failure.2,3

Mobile sensing and network analytics for realizing smart automated systems towards health Internet of Things

Internet of Things (IoT) provides an unprecedented opportunity to realize smart automated systems such as smart manufacturing, smart city and smart home in the past few years. Pervasive sensing and mobile technology deployed in large-scale IoT systems lead to the accumulation of big data. In particular, wearable biosensing accelerates human-centered computing for smart health management. However, limited work has been done to develop advanced IoT technologies for smart monitoring and control of heart health. There is an urgent need to develop a new IoT technology specific to the heart, namely Internet of Hearts (IOH) that will enable and assist (1) the acquisition of electrocardiogram (ECG) signals pertinent to space-time cardiac dynamics at anytime anywhere; (2) real-time management and compact representation of multi-sensor signals; (3) big data analytics in large-scale IoT contexts. This paper presents a new technology of Mobile and E-Network Smart Health (MESH), which is composed of 4 components as follows: 1) Mobile-based ECG sensing device; 2) Space-time representation of cardiac electrical activity; 3) Optimal model-based representation of ECG signals; 4) Dynamic network embedding for disease pattern recognition. Our preliminary experimental results demonstrated that network analytics is efficient and effective for smart health management in IoT contexts. The MESH technology shows strong potentials to provide an indispensable and enabling tool for realizing smart heart health and wellbeing for the population worldwide.

P Wave and the Substrates of Arrhythmias Originating in the Atria

The sinus node is the primary cardiac pacemaker from which the wavefront of activation proceeds through bundles of atrial fibers to the atrioventricular node. Left atrial activation proceeds along the Bachmann bundle and lower right atrium, determining P-wave morphology. Electrocardiogram reveals ectopic or retrograde atrial activation, wandering pacemaker activity, or artificial pacemaker-mediated atrial depolarization. Vectorcardiography and transesophageal recording are complementary methods. Atrial anatomic structure and automatic cells outside the sinus node constitute the mechanisms of focal and reentrant atrial arrhythmias. Arrhythmias with specific arrhythmogenic mechanisms correspond to precise electrocardiographic morphology for accurate diagnosis.

Arrhythmias Originating in the Atria

Atrial flutter, atrial tachycardias, and atrial fibrillation are the main sustained atrial tachycardias. Reentry, increased automaticity, and triggered activity are atrial arrhythmias main mechanisms. Atrial flutter is the clinical and theoretical model of reentry. Its classification is based on the atrial chamber involved and the arrhythmias anatomic path. Ablative procedures for atrial fibrillation have created several new reentrant tachycardias. Electrocardiography (ECG) identifies the site of origin of focal atrial tachycardias and the mechanism of these arrhythmias. ECG is fundamental in the diagnosis of atrial fibrillation and often allows understanding of its mechanism of origin and maintenance.

Echocardiographic Findings During Stress-Induced ST-Segment Elevation in Lead aVR in Ostial Left Main, Left Anterior Descending Stenosis

![Figure][1] [![Graphic][3] ][3][![Graphic][4] ][4] A 63-year-old man with hypertension, hyperlipidemia, and nicotine abuse underwent an echocardiogram stress test to investigate a recent history of chest pressure at rest. Baseline echocardiogram and electrocardiogram (A) were

Atrial fibrillation source identification

Atrial Fibrillation, a common arrhythmia accompanied by an increased morbidity and mortality remains difficult to treat either with medications or invasive procedures. Targeted destruction of atrial fibrillation triggers offers the best hope for permanent resolution of the arrhythmia. In this work, identification of atrial triggers is based on the analysis of complex endocardial recordings. Here, we propose a novel algorithm to detect the source of atrial fibrillation by classifying the signals originating from the four pulmonary veins in the left atrium.

Atrioventricular Nodal Conduction Disease

This article describes the different anatomic structures involved in normal atrioventricular conduction and their pathologic states. It defines their effects on the electrocardiogram, and describes how to localize the level and evaluate the severity of conduction disease by electrocardiographic analysis. It illustrates the relevance of intracavitary recordings in the diagnosis of level of block.

P Wave Analysis in the Era of Atrial Fibrillation Ablation

The common arrhythmia atrial fibrillation (AF) is incompletely understood. The mechanism of initiation and the perpetuation of AF remain speculative. This article summarizes current knowledge of the complex relationship between arrhythmias triggering AF and their long-term effects on atrial tissue, leading to perpetuation of tachycardia. It focuses on the role of the electrocardiogram (ECG) from AF diagnosis to identification of sinus P wave abnormalities predicting future occurrences. The role of ambulatory ECG recordings in managing AF and the use of frequency analysis determining degree of organization and identification of AF triggers are discussed.

Intraventricular Delay and Blocks

From the atrioventricular node, electrical activation is propagated to both ventricles by a system of specialized conducting fibers, His Purkinje System (HPS), guaranteeing a fast, synchronous depolarization of both ventricles. From the predivisional common stem, a right and left branch separate, subdividing further in a fairly predictable fashion. Synchronous ventricular activation results in a QRS with specific characteristics and duration of less than 110 milliseconds. Block or delay in any part of the HPS changes the electrocardiographic (ECG) morphology. This article discusses the use and limitations of standard ECG in detecting abnormal ventricular propagation in specific areas of the HPS.