ArticleBMC cardiovascular disorders2019
Dynamic predictive accuracy of electrocardiographic biomarkers of sudden cardiac death within a survival framework: the Atherosclerosis Risk in Communities (ARIC) study.
Article in BMC cardiovascular disorders, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- Machine learning of electrophysiological signals for the prediction of ventricular arrhythmias: systematic review and examination of heterogeneity between studies.EBioMedicine · 2023Pooled it
- Changes of the QRS-T angle in Patients Undergoing Transcatheter Aortic Valve Implantation.International journal of medical sciences · 2026Article
- Time-Dependent ECG-AI Prediction of Fatal Coronary Heart Disease: A Retrospective Study.Journal of cardiovascular development and disease · 2024Article
- Electrical Heterogeneity in Hispanic Background Subpopulations: The HCHS/SOL.JACC. Advances · 2024Article
- Latent profiles of global electrical heterogeneity: the Hispanic Community Health Study/Study of Latinos.European heart journal. Digital health · 2024Article
- Competing risks of monomorphic vs. non-monomorphic ventricular arrhythmias in primary prevention implantable cardioverter-defibrillator recipients: Global Electrical Heterogeneity and Clinical Outcomes (GEHCO) study.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2024Article
- Feasibility of remote monitoring for fatal coronary heart disease using Apple Watch ECGs.Cardiovascular digital health journal · 2024Article
- Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease.Nature communications · 2023Article
- Digitizing ECG image: A new method and open-source software code.Computer methods and programs in biomedicine · 2022Article
- Article
- Adaptive Cardiac Resynchronization Therapy Effect on Electrical Dyssynchrony (aCRT-ELSYNC): A randomized controlled trial.Heart rhythm O2 · 2021Article
- Competing risks in patients with primary prevention implantable cardioverter-defibrillators: Global Electrical Heterogeneity and Clinical Outcomes study.Heart rhythm · 2021Article
- Electrocardiogram machine learning for detection of cardiovascular disease in African Americans: the Jackson Heart Study.European heart journal. Digital health · 2021Article
- Article
- Bringing Critical Race Praxis Into the Study of Electrophysiological Substrate of Sudden Cardiac Death: The ARIC Study.Journal of the American Heart Association · 2020Article
- Importance of the heart vector origin point definition for an ECG analysis: The Atherosclerosis Risk in Communities (ARIC) study.Computers in biology and medicine · 2019Article
- Reproducibility of global electrical heterogeneity measurements on 12-lead ECG: The Multi-Ethnic Study of Atherosclerosis.Journal of electrocardiologyArticle
- Does Sex Modify an Association of Electrophysiological Substrate with Sudden Cardiac Death? The Atherosclerosis Risk in Communities (ARIC) Study.Cardiovascular digital health journalArticle
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundThe risk of sudden cardiac death (SCD) is known to be dynamic. However, the accuracy of a dynamic SCD prediction is unknown. We aimed to measure the dynamic predictive accuracy of ECG biomarkers of SCD and competing non-sudden cardiac death (non-SCD).
methodsAtherosclerosis Risk In Community study participants with analyzable ECGs in sinus rhythm were included (n = 15,716; 55% female, 73% white, age 54.2 ± 5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity and traditional ECG metrics (heart rate, QRS, QTc) were measured. Adjudicated SCD was the primary outcome; non-SCD was the competing outcome. Time-dependent area under the receiver operating characteristic curve (ROC(t) AUC) analysis was performed to assess the prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years using a survival analysis framework. Reclassification improvement as compared to clinical risk factors (age, sex, race, diabetes, hypertension, coronary heart disease, stroke) was measured.
resultsOver a median 24.4 y follow-up, there were 577 SCDs (incidence 1.76 (95%CI 1.63-1.91)/1000 person-years), and 829 non-SCDs [2.55 (95%CI 2.37-2.71)]. No ECG biomarkers predicted SCD within 3 months after ECG recording. Within 6 months, spatial ventricular gradient (SVG) elevation predicted SCD (AUC 0.706; 95%CI 0.526-0.886), but not a non-SCD (AUC 0.527; 95%CI 0.303-0.75). SVG elevation more accurately predicted SCD if the ECG was recorded 6 months before SCD (AUC 0.706; 95%CI 0.526-0.886) than 2 years before SCD (AUC 0.608; 95%CI 0.515-0.701). Within the first 3 months after ECG recording, only SVG azimuth improved reclassification of the risk beyond clinical risk factors: 18% of SCD events were reclassified from low or intermediate risk to a high-risk category. QRS-T angle was the strongest long-term predictor of SCD (AUC 0.710; 95%CI 0.668-0.753 for ECG recorded within 10 years before SCD).
conclusionShort-term and long-term predictive accuracy of ECG biomarkers of SCD differed, reflecting differences in transient vs. persistent SCD substrates. The dynamic predictive accuracy of ECG biomarkers should be considered for competing SCD risk scores. The distinction between markers predicting short-term and long-term events may represent the difference between markers heralding SCD (triggers or transient substrates) versus markers identifying persistent substrate.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.