ArticleJournal of physics D: Applied physics2015
Singular Value Decomposition of Optically-Mapped Cardiac Rotors and Fibrillatory Activity.
Article in Journal of physics D: Applied physics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Causality analysis of leading singular value decomposition modes identifies rotor as the dominant driving normal mode in fibrillation.Chaos (Woodbury, N.Y.) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Our progress of understanding how cellular and structural factors contribute to the arrhythmia is hampered in part because of controversies whether a fibrillating heart is driven by a single, several, or multiple number of sources, and whether they are focal or reentrant, and how to localize them. Here we demonstrate how a novel usage of the neutral singular value decomposition (SVD) method enables the extraction of the governing spatial and temporal modes of excitation from a rotor and fibrillatory waves. Those modes highlight patterns and regions of organization in the midst of the otherwise seemingly-randomly propagating excitation waves. We apply the method to experimental models of cardiac fibrillation in rabbit hearts. We show that the SVD analysis is able to enhance the classification of the heart electrical patterns into regions harboring drivers in the form of fast reentrant activity and other regions of by-standing activity. This enhancement is accomplished without any prior assumptions regarding the spatial, temporal or spectral properties of those drivers. The analysis corroborates that the dominant mode has the highest activation rate and further reveals a new feature: A transfer of modes from the driving to the passive regions resulting in a partial reaction of the passive region to the driving region.
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.