Cardiac Arrhythmia and Geomagnetic Activity

Background: The purpose of this paper is a review of a number of studies considering links between life threatening cardiac arrhythmias, sudden cardiac death (SCD) and the level of environmental physical activity factors like geomagnetic activity (GMA) and opposite them cosmic ray and high energy proton flux. This is a part of studies in the field named Clinical Cosmobiology. Methods: Temporal distribution of cardiac arrhythmias and SCD daily and monthly were compared to the level of GMA, space proton flux, cosmic ray activity according to neutron activity (impulse/min) on the earth's surface. The cosmophysical data was obtained from the cosmic science institutions in the USA, Russia and Finland (cosmic ray data, partially). Results: As it follows from the results of the quoted studies there is an inverse relationship between the frequency of cardiac arrhythmic events and SCD and the level of daily GMA. Conclusions: Now studies are in progress considering the role of neutron (cosmic ray) activity in the natural history of the mentioned events. According to the various studies, we can presume that the GMA has some protective effect on cardiac arrhythmias and SCD

Cardiac safety of tiotropium in patients with cardiac events: a retrospective analysis of the UPLIFT® trial.

BackgroundTiotropium is an anticholinergic bronchodilator for symptom relief and reducing exacerbations with an established safety profile in patients with chronic obstructive pulmonary disease (COPD). Using data from the 4-year Understanding Potential Long-term Impacts on Function with Tiotropium (UPLIFT®) study, we re-evaluated the safety of tiotropium HandiHaler® in patients who experienced recent myocardial infarction (MI), heart failure or unstable rhythm disorder during the study.MethodsA post-hoc analysis of all-cause mortality and serious cardiac adverse events (cardiac SAEs), including cardiac deaths and death unknown, was conducted in patients who had experienced cardiac arrhythmia, MI or cardiac failure during UPLIFT® and who completed the study. Descriptive analyses were performed.ResultsMost patients experiencing cardiac events, for which they would have been excluded at baseline, remained in the trial. Kaplan-Meier analyses revealed a trend to later occurrence of cardiac SAEs with tiotropium HandiHaler® versus placebo. Patients who experienced a cardiac event and continued in UPLIFT® were not found to be at subsequently increased risk of all-cause mortality or cardiac SAEs with tiotropium treatment. Evaluation of deaths by major adverse cardiac events composite endpoints also showed that patients treated with tiotropium were not at increased risk of mortality or cardiac SAEs compared with placebo.ConclusionsRisk of cardiac events, mortality or SAEs was not increased by tiotropium in patients experiencing cardiac events for which they would have been excluded at study baseline. The findings support the cardiac safety of tiotropium HandiHaler® in patients with COPD

Profile of cardiac arrhythmia in acute stroke patients

Introduction: Cardiac arrhythmias are common and can be fatal in acute strokes, but they are often under-recognized. The presence of cardiac arrhythmia in acute stroke doubles the mortality. Objectives: This study aimed to determine the types of cardiac arrhythmia in acute stroke patients admitted in two urban hospitals in Dar es Salaam, The Aga Khan Hospital, Dar es Salaam and Muhimbili National Hospital. The secondary objectives were to determine the associations between the characteristic of stroke and cardiac arrhythmias as well as to determine the impact of cardiac arrhythmia on 30- days stroke outcomes. Methods: This was a prospective longitudinal study that recruited a total of 222 stroke patients admitted to the above-named hospitals from October 1, 2019, to March 30, 2020. The radiologically confirmed stroke patients were screened for cardiac arrhythmia using 12 lead Electrocardiograms within 72 hours post-stroke. The outcome measure was determined using the Modified Rankin Score on admission and day 30 of stroke. Results: Among 222 acute stroke patients admitted, significant cardiac arrhythmia occurred in 30 patients (13.96%) in the first 72 hours of acute stroke. Atrial fibrillation 10(5.4%), ventricular tachycardia 7(3.2%), sinus arrhythmia 7(3.2%), Sinus bradyarrhythmia 2(0.9%), Ventricular fibrillation 2(0.9%), Premature ventricular complex 2(0.9%) and Atrial flutter 1(0.5%) were the identified in acute stroke. Cardiac arrhythmias were independently associated with high stroke severity score, hemorrhagic stroke, and cerebral hemisphere stroke. Cardiac arrhythmia is an independent predictor of poor outcome in acute stroke. The study found that 62.5% of acute stroke patients with cardiac arrhythmia had 30 days of poor outcome with 27 % mortality. Conclusion: Cardiac arrhythmia is very common in acute stroke. Serious arrhythmia in acute strokes such as Ventricular fibrillation and ventricular tachycardia are also common and can lead to sudden death. Understanding of the attributable types of cardiac arrhythmias in acute stroke patients has important implications for stroke management and prevention of mortality

Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation

The electrocardiogram (ECG) is one of the most extensively employed signals used in the diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture the heart's rhythmic irregularities, commonly known as arrhythmias. A careful study of ECG signals is crucial for precise diagnoses of patients' acute and chronic heart conditions. In this study, we propose a two-dimensional (2-D) convolutional neural network (CNN) model for the classification of ECG signals into eight classes; namely, normal beat, premature ventricular contraction beat, paced beat, right bundle branch block beat, left bundle branch block beat, atrial premature contraction beat, ventricular flutter wave beat, and ventricular escape beat. The one-dimensional ECG time series signals are transformed into 2-D spectrograms through short-time Fourier transform. The 2-D CNN model consisting of four convolutional layers and four pooling layers is designed for extracting robust features from the input spectrograms. Our proposed methodology is evaluated on a publicly available MIT-BIH arrhythmia dataset. We achieved a state-of-the-art average classification accuracy of 99.11\%, which is better than those of recently reported results in classifying similar types of arrhythmias. The performance is significant in other indices as well, including sensitivity and specificity, which indicates the success of the proposed method.Comment: 14 pages, 5 figures, accepted for future publication in Remote Sensing MDPI Journa

The Garden of the Heart: HeartMath - The New Biotechnology for Treating Children with ADD/ADHD and Arrhythmia

This article gives a practitioner's account of her success using HeartMath's techniques and emWave(R) PC heart rhythm coherence feedback system in treating children with AD/HD. Dr. St. Martin's report describes how she helped nearly 400 children eliminate their need for medication using the emWave(R) PC and HeartMath tools

MultiNeuron - Neural Networks Simulator for Medical, Physiological, and Psychological Applications

This work describes neural software applied in medicine and physiology to: - investigate and diagnose immune deficiencies; diagnose and study allergic and pseudoallergic reactions; forecast emergence or aggravation of stagnant cardiac insufficiency in patients with cardiac rhythm disorders; forecast development of cardiac arrhythmia after myocardial infarction; reveal relationships between the accumulated radiation dose and a set of immunological, hormonal, and bio-chemical parameters of human blood and find a method to be able to judge by these parameters the dose value; propose a technique for early diagnosis of chor-oid melanomas; Neural networks help also to predict human relations within a group