Background: Electrocardiogram (ECG) with preparticipation evaluation (PPE) for athletes remains controversial in the United States and diagnostic accuracy of clinician ECG interpretation is unclear. This study aimed to assess reliability and validity of clinician ECG interpretation using expert-validated ECGs according to the 2010 European Society of Cardiology (ESC) interpretation criteria.
Methods: This is a blinded, prospective study of diagnostic accuracy of clinician ECG interpretation. Anonymized ECGs were validated for normal and abnormal patterns by blinded expert interpreters according to the ESC interpretation criteria from October 2011 through March 2012. Six pairs of clinician interpreters were recruited from relevant clinical specialties in an academic medical center in March 2012. Each clinician interpreted 85 ECGs according to the ESC interpretation guidelines. Cohen and Fleiss' kappa, sensitivity, and specificity were calculated within specialties and across primary care and cardiology specialty groups.
Results: Experts interpreted 189 ECGs yielding a kappa of 0.63, demonstrating "substantial" inter-rater agreement. A total of 85 validated ECGs, including 26 abnormals, were selected for clinician interpretation. The kappa across cardiology specialists was "substantial" and "moderate" across primary care (0.69 vs 0.52, respectively, P < 0.001). Sensitivity and specificity to detect abnormal patterns were similar between cardiology and primary care groups (sensitivity 93.3% vs 81.3%, respectively, P = 0.31; specificity 88.8% vs 89.8%, respectively, P = 0.91).
Conclusions: Clinician ECG interpretation according to the ESC interpretation criteria appears to demonstrate limited reliability and validity. Before widespread adoption of ECG for PPE of U.S. athletes, further research of training focused on improved reliability and validity of clinician ECG interpretation is warranted.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6932271 | PMC |
http://dx.doi.org/10.1111/anec.12138 | DOI Listing |
Eur J Trauma Emerg Surg
January 2025
Emergency Department, Habib bourguiba university hospital, Faculty of Medicine, Sfax University, Majida Boulila Avenue, Sfax, Tunisia.
Introduction: Electrical injuries (EIs) represent a significant clinical challenge due to their complex pathophysiology and variable presentation, ranging from minor burns to severe internal organ damage. Despite their prevalence in both; domestic and occupational settings, there remains a rareness of systematic guidelines and comprehensive literature to aid clinicians in effectively managing these injuries. Understanding these factors is crucial for developing protocols that can mitigate the risk of delayed complications, such as cardiac arrhythmias, in patients who initially appear stable.
View Article and Find Full Text PDFCardiol Young
January 2025
Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada.
Hypertensive heart disease and hypertrophic cardiomyopathy both lead to left ventricular hypertrophy despite differing in aetiology. Elucidating the correct aetiology of the presenting hypertrophy can be a challenge for clinicians, especially in patients with overlapping risk factors. Furthermore, drugs typically used to combat hypertensive heart disease may be contraindicated for the treatment of hypertrophic cardiomyopathy, making the correct diagnosis imperative.
View Article and Find Full Text PDFCureus
December 2024
Department of Cardiology, Shariati Hospital, School of Medicine, Tehran University of Medical Sciences, Tehran, IRN.
Pulmonary thromboembolism (PTE) is the third most common cause of acute cardiovascular disease, which can lead to high morbidity and mortality if left untreated. Anatomical and electrophysiological variations and obesity may complicate timely diagnosis and delay required management. While computed tomography pulmonary angiography (CTPA) remains the most accurate diagnostic tool, initial assessments using electrocardiography (ECG) or echocardiography can be helpful in early suspicion.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Information Engineering, Università Politecnica delle Marche, via Brecce Bianche, Ancona, 60131, Italy.
Background: Deep-learning applications in cardiology typically perform trivial binary classification and are able to discriminate between subjects affected or not affected by a specific cardiac disease. However, this working scenario is very different from the real one, where clinicians are required to recognize the occurrence of one cardiac disease among the several possible ones, performing a multiclass classification. The present work aims to create a new interpretable deep-learning tool able to perform a multiclass classification and, thus, discriminate among several different cardiac diseases.
View Article and Find Full Text PDFCurr Cardiol Rep
January 2025
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
Purpose Of Review: Artificial Intelligence (AI) technology will significantly alter critical care cardiology, from our understanding of diseases to the way in which we communicate with patients and colleagues. We summarize the potential applications of AI in the cardiac intensive care unit (CICU) by reviewing current evidence, future developments and possible challenges.
Recent Findings: Machine Learning (ML) methods have been leveraged to improve interpretation and discover novel uses for diagnostic tests such as the ECG and echocardiograms.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!