ReviewOchsner journal2016
Surface Electrocardiogram Predictors of Sudden Cardiac Arrest.
Review in Ochsner journal, 2016. 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.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in electrocardiogram signals for sudden cardiac death prediction: a systematic review and meta-analysis.Systematic reviews · 2025Pooled it
- Sudden cardiac arrest prediction via deep learning electrocardiogram analysis.European heart journal. Digital health · 2025Article
- Predicting Cardiopulmonary Arrest with Digital Biomarkers: A Systematic Review.Journal of clinical medicine · 2023Review
- The "Five Malignant Waves" of the Eletrocardiography.Arquivos brasileiros de cardiologia · 2023Article
- ECG Markers of Acute Melatonin Treatment in a Porcine Model of Acute Myocardial Ischemia.International journal of molecular sciences · 2022Article
- Recent Non-Invasive Parameters to Identify Subjects at High Risk of Sudden Cardiac Death.Journal of clinical medicine · 2022Review
- Beyond Ejection Fraction: Novel Clinical Approaches Towards Sudden Cardiac Death Risk Stratification in Patients with Dilated Cardiomyopathy.Current cardiology reviews · 2022Review
- Signal averaged ECG in patients with early repolarization.Journal of arrhythmia · 2021Article
- Thermal modulation of epicardial Ca2+ dynamics uncovers molecular mechanisms of Ca2+ alternans.The Journal of general physiology · 2021Article
- Article
- Cardiac magnetic resonance predicts ventricular arrhythmias in scleroderma: the Scleroderma Arrhythmia Clinical Utility Study (SAnCtUS).Rheumatology (Oxford, England) · 2020Article
- Single-modal and multi-modal false arrhythmia alarm reduction using attention-based convolutional and recurrent neural networks.PloS one · 2020Article
- Prospects of using cardiovascular magnetic resonance in the identification of arrhythmogenic substrate in autoimmune rheumatic diseases.Rheumatology international · 2018Review
- Article
- Detection of Acute Myocardial Infarction in a Pig Model Using the SAN-Atrial-AVN-His (SAAH) Electrocardiogram (ECG), Model PHS-A10, an Automated and Integrated Signals Recognition System.Medical science monitor : international medical journal of experimental and clinical research · 2018Article
- Meta-analysis of T-wave indices for risk stratification in myocardial infarction.Journal of geriatric cardiology : JGC · 2017Article
- Increase of Short-Term Heart Rate Variability Induced by Blood Pressure Measurements during Ambulatory Blood Pressure Monitoring.Computational and mathematical methods in medicine · 2017Article
- TpTe and TpTe/QT: novel markers to predict sudden cardiac death in ESRD?Jornal brasileiro de nefrologiaArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHeart disease is a major cause of death in industrialized nations, with approximately 50% of these deaths attributable to sudden cardiac arrest. If patients at high risk for sudden cardiac arrest can be identified, their odds of surviving fatal arrhythmias can be significantly improved through prophylactic implantable cardioverter defibrillator placement. This review summarizes the current knowledge pertaining to surface electrocardiogram (ECG) predictors of sudden cardiac arrest.
methodsWe conducted a literature review focused on methods of predicting sudden cardiac arrest through noninvasive electrocardiographic testing.
resultsSeveral electrocardiographic-based methods of risk stratification of sudden cardiac arrest have been studied, including QT prolongation, QRS duration, fragmented QRS complexes, early repolarization, Holter monitoring, heart rate variability, heart rate turbulence, signal-averaged ECG, T wave alternans, and T-peak to T-end. These ECG findings have shown variable effectiveness as screening tools.
conclusionAt this time, no individual ECG finding has been found to be able to adequately stratify patients with regard to risk for sudden cardiac arrest. However, one or more of these candidate surface ECG parameters may become useful components of future multifactorial risk stratification calculators.
Indexed as
Identifiers
27660578PMC5024811What OpenQuestion holds
Registered trials
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.