Variability in interpretation of the electrocardiogram in athletes: Another limitation in pre-competitive screening

Big Data and Artificial Intelligence: Opportunities and Threats in Electrophysiology

The combination of big data and artificial intelligence (AI) is having an increasing impact on the field of electrophysiology. Algorithms are created to improve the automated diagnosis of clinical ECGs or ambulatory rhythm devices. Furthermore, the use of AI during invasive electrophysiological studies or combining several diagnostic modalities into AI algorithms to aid diagnostics are being investigated. However, the clinical performance and applicability of created algorithms are yet unknown. In this narrative review, opportunities and threats of AI in the field of electrophysiology are described, mainly focusing on ECGs. Current opportunities are discussed with their potential clinical benefits as well as the challenges. Challenges in data acquisition, model performance, (external) validity, clinical implementation, algorithm interpretation as well as the ethical aspects of AI research are discussed. This article aims to guide clinicians in the evaluation of new AI applications for electrophysiology before their clinical implementation.

Athlete's Heart and Left Heart Disease

Physical activity comprises all muscular activities that require energy expenditure. Regular sequence of structured and organized exercise with the specific purpose of improving wellness and athletic performance is defined as a sports activity.Exercise can be performed at various levels of intensity and duration. According to the social context and pathways, it can be recreational, occupational, and competitive. Therefore, the training burden varies inherently and the heart adaptation is challenging.Although a general agreement on the fact that sports practice leads to metabolic, functional and physical benefits, there is evidence that some athletes may be subjected to adverse outcomes. Sudden cardiac death can occur in apparently healthy individuals with unrecognized cardiovascular disease.Thus, panels of experts in sports medicine have promoted important pre-participation screening programmes aimed at determining sports eligibility and differentiating between physiological remodeling and cardiac disease.In this review, the most important pathophysiological and diagnostic issues are discussed.

Performance of the BMJ learning training modules for ECG interpretation in athletes

To assess the accuracy of interpreting the athlete’s ECG both pre and post a series of online training modules among a range of healthcare professionals. 10 512 healthcare professionals from 138 different nations commenced the online course. These were primarily doctors (43%), nurses (18.4%) and other healthcare professionals (3.9%). The users came from 102 different specialities, with General Practice/Family Medicine (24.5%), Cardiology (10.6%), Emergency Medicine (8.7%) and Sports Medicine (6.6%) predominating. Among the 2023 users who completed both the pre-course and post-course test, there was an overall improvement of 15.3% (95% CI 13.9% to 16.6%; p<0.001). 930 completed all four other modules, and these users fared significantly better (18.7% increase; 95% CI 17.3 to 20.0) than those completing no additional modules (11.7% increase; 95% CI 3.3 to 17.7, p=0.036). Demographic analysis showed that while the starting pre-test scores varied significantly between profession/specialty groups (57.8%–82.6%), post-test scores were largely consistent (80.8%–84.6%). Although users showed the most improvement when interpreting primary electrical diseases (12.4% increase), it was also an area of notable weakness compared with the modules of normal training-related findings and cardiomyopathies. With the evolving criteria for ECG interpretation eliciting ever improving levels of specificity and sensitivity in the detection of conditions associated with sudden cardiac death among athletes, training is required to ensure the infrastructure and personnel is in place to uphold these standards. The BMJ Learning course presented is a valuable first step and demonstrates that such an online tool can be effective in aiding ECG interpretation among healthcare professionals globally.