Aim: We examined the diagnostic accuracy of single-lead ECG as assessed by radiographers and 12-lead ECG as assessed by cardiac nurses for the diagnosis of atrial fibrillation (AF).
Methods: Based on the Danish Cardiovascular Screening Trial, we conducted a population-based, cross-sectional study of 1338 randomly selected Danish men aged 65-74 years with no exclusion criteria. The participants were screened with single-lead ECG during a CT scan assessed by radiographers and 12-lead ECG assessed by cardiac nurses. The diagnostic accuracy was evaluated compared with that produced by a 12-lead ECG assessed by two consenting cardiologists.
Results: The study identified 68 participants with ongoing AF, of whom 60 had self-reported AF and 8 had AF detected in the screening. Single-lead ECG assessed for AF by radiographers had a sensitivity of 60.3% (95% CI 47.7 to 72.0), specificity of 97.2% (95% CI 96.2 to 98.1), positive predictive value (PPV) of 53.9% (95% CI 42.1 to 65.5) and negative predictive value (NPV) of 97.9% (95% CI 96.9 to 98.6). 12-lead ECG assessed by cardiac nurses had a sensitivity of 97.1% (95% CI 89.8 to 99.6), specificity of 100% (95% CI 99.7 to 100), PPV of 100% (95% CI 94.6 to 100) and NPV of 99.8% (95% CI 99.4 to 100).
Conclusions: Single-lead ECG assessed by radiographers had a moderate sensitivity and PPV but a very high specificity and NPV. Using radiographers may be acceptable for opportunistic screening, in particular if radiographers are thoroughly trained. Thus, 12-lead ECG assessed by cardiac nurses is a potential diagnostic method for the detection of AF.
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http://dx.doi.org/10.1136/openhrt-2018-000942 | DOI Listing |
Eur Heart J Digit Health
January 2025
Cardiovascular Center, Tufts Medical Center, 800 Washington Street, Boston, MA 02111, USA.
Aims: This study evaluates the performance of OpenAI's latest large language model (LLM), Chat Generative Pre-trained Transformer-4o, on the Adult Clinical Cardiology Self-Assessment Program (ACCSAP).
Methods And Results: Chat Generative Pre-trained Transformer-4o was tested on 639 ACCSAP questions, excluding 45 questions containing video clips, resulting in 594 questions for analysis. The questions included a mix of text-based and static image-based [electrocardiogram (ECG), angiogram, computed tomography (CT) scan, and echocardiogram] formats.
Eur Heart J Digit Health
January 2025
Department of Cardiovascular Medicine, Mayo Clinic, 200 1st St SW, Rochester, MN 55905, USA.
Aims: Gender-affirming hormone therapy (GAHT) is used by some transgender individuals (TG), who comprise 1.4% of US population. However, the effects of GAHT on electrocardiogram (ECG) remain unknown.
View Article and Find Full Text PDFEur Heart J Digit Health
January 2025
Cardiovascular Division, Department of Medicine, University of Minnesota Medical School, 401 East River Parkway, Minneapolis, MN, USA.
Aims: Many studies have utilized data sources such as clinical variables, polygenic risk scores, electrocardiogram (ECG), and plasma proteins to predict the risk of atrial fibrillation (AF). However, few studies have integrated all four sources from a single study to comprehensively assess AF prediction.
Methods And Results: We included 8374 (Visit 3, 1993-95) and 3730 (Visit 5, 2011-13) participants from the Atherosclerosis Risk in Communities Study to predict incident AF and prevalent (but covert) AF.
Cureus
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 PDFBMC Pregnancy Childbirth
January 2025
Department of Anesthesiology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Background: Lack of motivation and behavioral abnormalities are the hallmarks of postpartum depression (PPD). Severe uterine contractions during labor are pain triggers for psychiatric disorders, including PPD in women during the puerperium. Creating biomarkers to monitor PPD may help in its early detection and treatment.
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