ReviewTrends in cardiovascular medicine2011
Human atrial fibrillation: insights from computational electrophysiological models.
Review in Trends in cardiovascular medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
15 citing papers in PubMed.
- Populations of in silico myocytes and tissues reveal synergy of multiatrial-predominant KBritish journal of pharmacology · 2020Article
- Computational modeling: What does it tell us about atrial fibrillation therapy?International journal of cardiology · 2019Review
- Article
- Understanding the Beat-to-Beat Variations of P-Waves Morphologies in AF Patients During Sinus Rhythm: A Scoping Review of the Atrial Simulation Studies.Frontiers in physiology · 2019Article
- Distinct Occurrence of Proarrhythmic Afterdepolarizations in Atrial Versus Ventricular Cardiomyocytes: Implications for Translational Research on Atrial Arrhythmia.Frontiers in pharmacology · 2018Article
- Revealing kinetics and state-dependent binding properties of IChaos (Woodbury, N.Y.) · 2017Article
- Potassium currents in the heart: functional roles in repolarization, arrhythmia and therapeutics.The Journal of physiology · 2017Review
- Article
- Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention.Annals of biomedical engineering · 2016Article
- Rabbit-specific computational modelling of ventricular cell electrophysiology: Using populations of models to explore variability in the response to ischemia.Progress in biophysics and molecular biology · 2016Article
- Computational models of atrial cellular electrophysiology and calcium handling, and their role in atrial fibrillation.The Journal of physiology · 2016Review
- Fibroblast-myocyte electrotonic coupling: does it occur in native cardiac tissue?Journal of molecular and cellular cardiology · 2014Review
- Mathematical approaches to understanding and imaging atrial fibrillation: significance for mechanisms and management.Circulation research · 2014Review
- Human atrial cell models to analyse haemodialysis-related effects on cardiac electrophysiology: work in progress.Computational and mathematical methods in medicine · 2014Review
- Sodium-calcium exchangers (NCX): molecular hallmarks underlying the tissue-specific and systemic functions.Pflugers Archiv : European journal of physiology · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Computational electrophysiology has proven useful to investigate the mechanisms of cardiac arrhythmias at various spatial scales, from isolated myocytes to the whole heart. This article reviews how mathematical modeling has aided our understanding of human atrial myocyte electrophysiology to study the contribution of structural and electrical remodeling to human atrial fibrillation. Potential new avenues of investigation and model development are suggested.
Indexed as
Identifiers
What 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.