The Application of Computer Techniques to ECG Interpretation

It is over 120 years since Einthoven introduced the electrocardiogram [...]

Bundle Branch Re-Entrant Ventricular Tachycardia after Minimal Invasive Cardiac Surgery

Background: Bundle branch re-entrant ventricular tachycardia (BBRVT) is a monomorphic ventricular arrhythmia with wide QRS complexes caused by re-entrant tachycardia between both bundle branches. BBRVT can occur in a variety of cardiac pathologies with His–Purkinje system (HPS) conduction abnormalities such as dilated cardiomyopathy, coronary artery disease, hypertrophic cardiomyopathy, valvular heart disease and even after aortic valve surgery. Case report: A 62-year-old male patient with an ischemic cardiomyopathy and implantable cardioverter defibrillator (ICD) underwent minimal invasive aortic valve replacement (Yil-AVR) and coronary artery bypass graft (CABG). He was remitted a week later because of relapsing sustained ventricular tachycardia (VT). Electrocardiogram showed a wide QRS tachycardia, which was remarkably similar to the patient’s sinus rhythm. Analysis of ICD revealed the presence of BBRVT. Catheter ablation of the right bundle branch (RBB) was performed. He is currently in clinical follow-up and no reoccurrence of VT has been recorded so far. Conclusion: Patients with known cardiomyopathy can develop BBRVT early after cardiac surgery. To our knowledge, this is the first time that BBRVT occurred after Yil-AVR.

Cost-Effectiveness and Safety of Same-Day Discharge after Elective Percutaneous Coronary Intervention

Objectives: We sought to investigate the rates of same-day discharge (SDD) post elective percutaneous coronary intervention (PCI) at our institution and review its safety by examining clinical outcomes. We also performed an economic analysis evaluating our hospital’s cost data for SDD following PCI. Methods: Patients undergoing elective PCI at St George Hospital, Australia, from January 2017 to December 2019 were evaluated. Primary outcomes included 7-day major adverse cardiovascular endpoints (MACEs) and readmission to hospital within 30 days. Results: Among 502 patients who underwent elective PCI, 421 patients (83.8%) were managed with SDD. There was one case of acute stent thrombosis and one case of coronary wire-induced perforation requiring a pericardial drain that occurred following elective PCI with SDD (0.54%). Unplanned cardiac re-hospitalisation at 30 days following elective PCI was 5.2%. SDD after elective PCI was associated with a healthcare cost saving of AUD 4817 per case. Conclusion: SDD following elective PCI was demonstrated to be a safe and effective strategy that was also associated with significant cost savings. SDD following elective PCI warrants more widespread use as it lowers healthcare costs, has equivalent patient outcomes and improves patient satisfaction.

PAF Physiology in Target Organ Systems—A Deep Dive to Understand the PAF Mystery in Pathogenesis of Disease

The purpose of this literature review is to gain an overview of the role of platelet-activating factor (PAF) within each of the body systems and how it contributes to normal and pathophysiological states. The review showed that there are multiple functions of PAF that are common to several body systems; however, there is little evidence to explain why PAF has this affect across multiple systems. Interestingly, there seems to be conflicting research as to whether PAF is an overall protective or pathogenic pathway. Within this research, it was found that there are different pathways depending on the specific body system, as well as between body systems. However, one universal function reported in the literature is of PAF as a pro-inflammatory molecule. Overall, this review identified five major functions of PAF: vasoconstriction, increased inflammation, vascular remodeling, increased edema, and endothelial permeability.

Safety and Cost Implications of Same-Day Discharge Following Elective Percutaneous Closure of Patent Foramen Ovale and Atrial Septal Defects in Australia

Background: Percutaneous closure of patent foramen ovale (PFO) and atrial septal defects (ASD) is being more commonly performed due to changes in international guidelines supporting its use. This study was performed to determine the clinical outcomes, safety and cost implications of same-day discharge (SDD) following such procedures and place this in an Australian context. Methods: This was a retrospective, observational study of patients undergoing elective percutaneous PFO or ASD closure at St. George Hospital, Australia between January 2011 and January 2020. Primary outcomes included 30-day major adverse cardiovascular endpoints (MACE) and readmission to hospital within 30 days. Results: Twenty-four patients were included in the primary analysis. Ten (41.7%) patients underwent elective ASD closure while 14 (58.3%) underwent PFO closure. Among the 24 patients who underwent elective percutaneous closure of structural heart disease, 23 patients (95.8%) were managed with SDD. There were no MACE outcomes at 30 days. No patients were re-admitted to hospital at 30 days following these procedures. When compared to overnight admission to hospital post-elective percutaneous structural heart condition closure, SDD yielded a cost saving of AUD 5999 per case. Conclusion: SDD following elective percutaneous closure of ASD and PFO was demonstrated to be a safe and effective strategy for managing patients. With more widespread use, it can lead to significant cost savings for hospitals without compromising patient care.

Body Surface Potential Mapping: Contemporary Applications and Future Perspectives

Body surface potential mapping (BSPM) is a noninvasive modality to assess cardiac bioelectric activity with a rich history of practical applications for both research and clinical investigation. BSPM provides comprehensive acquisition of bioelectric signals across the entire thorax, allowing for more complex and extensive analysis than the standard electrocardiogram (ECG). Despite its advantages, BSPM is not a common clinical tool. BSPM does, however, serve as a valuable research tool and as an input for other modes of analysis such as electrocardiographic imaging and, more recently, machine learning and artificial intelligence. In this report, we examine contemporary uses of BSPM, and provide an assessment of its future prospects in both clinical and research environments. We assess the state of the art of BSPM implementations and explore modern applications of advanced modeling and statistical analysis of BSPM data. We predict that BSPM will continue to be a valuable research tool, and will find clinical utility at the intersection of computational modeling approaches and artificial intelligence.

ECG Interpretation: Clinical Relevance, Challenges, and Advances

Since its inception, the electrocardiogram (ECG) has been an essential tool in medicine. The ECG is more than a mere tracing of cardiac electrical activity; it can detect and diagnose various pathologies including arrhythmias, pericardial and myocardial disease, electrolyte disturbances, and pulmonary disease. The ECG is a simple, non-invasive, rapid, and cost-effective diagnostic tool in medicine; however, its clinical utility relies on the accuracy of its interpretation. Computer ECG analysis has become so widespread and relied upon that ECG literacy among clinicians is waning. With recent technological advances, the application of artificial intelligence-augmented ECG (AI-ECG) algorithms has demonstrated the potential to risk stratify, diagnose, and even interpret ECGs—all of which can have a tremendous impact on patient care and clinical workflow. In this review, we examine (i) the utility and importance of the ECG in clinical practice, (ii) the accuracy and limitations of current ECG interpretation methods, (iii) existing challenges in ECG education, and (iv) the potential use of AI-ECG algorithms for comprehensive ECG interpretation.

Unexplained Syncope: The Importance of the Electrophysiology Study

Syncope of cardiac origin may be associated with an increased risk of sudden cardiac death if not treated in a timely and appropriate manner. The diagnostic approach of syncope imposes a significant economic burden on society. The investigation and elucidation of the pathogenetic mechanism of syncope are of great clinical importance, as both prognosis and appropriate therapeutic approaches depend on these factors. The responsible mechanism of presyncope or syncope can only be revealed through the patient history, baseline clinical examination and electrocardiogram. The percentage of patients who are diagnosed with these tests alone exceeds 50%. In patients with a history of organic or acquired heart disease or/and the presence of abnormal findings on the electrocardiogram, a further diagnostic electrophysiology inclusive approach should be followed to exclude life threatening arrhythmiological mechanism. However, if the patient does not suffer from underlying heart disease and does not show abnormal electrocardiographic findings in the electrocardiogram, then the probability in the electrophysiology study to find a responsible cause is small but not absent. The role of a two-step electrophysiology study inclusive risk stratification approach for the effective management of the former is thoroughly discussed in this review.

Applications of Machine Learning in Ambulatory ECG

The ambulatory ECG (AECG) is an important diagnostic tool for many heart electrophysiology-related cases. AECG covers a wide spectrum of devices and applications. At the core of these devices and applications are the algorithms responsible for signal conditioning, ECG beat detection and classification, and event detections. Over the years, there has been huge progress for algorithm development and implementation thanks to great efforts by researchers, engineers, and physicians, alongside the rapid development of electronics and signal processing, especially machine learning (ML). The current efforts and progress in machine learning fields are unprecedented, and many of these ML algorithms have also been successfully applied to AECG applications. This review covers some key AECG applications of ML algorithms. However, instead of doing a general review of ML algorithms, we are focusing on the central tasks of AECG and discussing what ML can bring to solve the key challenges AECG is facing. The center tasks of AECG signal processing listed in the review include signal preprocessing, beat detection and classification, event detection, and event prediction. Each AECG device/system might have different portions and forms of those signal components depending on its application and the target, but these are the topics most relevant and of greatest concern to the people working in this area.

Computer Assisted Patient Monitoring: Associated Patient, Clinical and ECG Characteristics and Strategy to Minimize False Alarms

This chapter is a review of studies that have examined false arrhythmia alarms during in-hospital electrocardiographic (ECG) monitoring in the intensive care unit. In addition, we describe an annotation effort being conducted at the UCSF School of Nursing, Center for Physiologic Research designed to improve algorithms for lethal arrhythmias (i.e., asystole, ventricular fibrillation, and ventricular tachycardia). Background: Alarm fatigue is a serious patient safety hazard among hospitalized patients. Data from the past five years, showed that alarm fatigue was responsible for over 650 deaths, which is likely lower than the actual number due to under-reporting. Arrhythmia alarms are a common source of false alarms and 90% are false. While clinical scientists have implemented a number of interventions to reduce these types of alarms (e.g., customized alarm settings; daily skin electrode changes; disposable vs. non-disposable lead wires; and education), only minor improvements have been made. This is likely as these interventions do not address the primary problem of false arrhythmia alarms, namely deficient and outdated arrhythmia algorithms. In this chapter we will describe a number of ECG features associated with false arrhythmia alarms. In addition, we briefly discuss an annotation effort our group has undertaken to improve lethal arrhythmia algorithms.