Evidence map›Paper›PMID 30195579›Full record

ArticleComputers in biology and medicine2018

Measuring defibrillator surface potentials: The validation of a predictive defibrillation computer model.

Jess Tate, Jeroen Stinstra, Thomas Pilcher, Ahrash Poursaid, Matthew A Jolley, Elizabeth Saarel, John Triedman, Rob S MacLeod

Abstract read
In one paragraph

Article in Computers in biology and medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Additional coils mitigate elevated defibrillation threshold in right-sided implantable cardioverter defibrillator generator placement: a simulation 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 · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jess TateDepartment of Bioengineering, University of Utah, Salt Lake City, USA; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, USA. Electronic address: jess@sci.utah.edu.
Jeroen StinstraDepartment of Bioengineering, University of Utah, Salt Lake City, USA; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, USA.
Thomas PilcherDivision of Pediatric Cardiology, University of Utah, Salt Lake City, USA.
Ahrash PoursaidDepartment of Bioengineering, University of Utah, Salt Lake City, USA; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, USA.
Matthew A JolleyDepartment of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, USA.
Elizabeth SaarelDivision of Pediatric Cardiology, University of Utah, Salt Lake City, USA.
John TriedmanDepartment of Cardiology, Children's Hospital Boston, Boston, Massachusetts, USA.
Rob S MacLeodDepartment of Bioengineering, University of Utah, Salt Lake City, USA; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, USA.

Funding

TRD - VisualizationP41GM103545 · NIGMS · UNIVERSITY OF UTAH · PI JOHNSON, CHRISTOPHER R., MACLEOD, ROB S. · 2012 to 2019
$9.7M
NIGMS NIH HHS P41 GM103545
6 · The paper itself

Abstract

Implantable cardioverter defibrillators (ICDs) are commonly used to reduce the risk in patients with life-threatening arrhythmias, however, clinicians have little systematic guidance to place the device, especially in cases of unusual anatomy. We have previously developed a computational model that evaluates the efficacy of a delivered shock as a clinical and research aid to guide ICD placement on a patient specific basis. We report here on progress to validate this model with measured ICD surface potential maps from patients undergoing ICD implantation and testing for defibrillation threshold (DFT). We obtained body surface potential maps of the defibrillation pulses by adapting a limited lead selection and potential estimation algorithm to deal with the limited space for recording electrodes. Comparison of the simulated and measured potential maps of the defibrillation shock yielded similar patterns, a typical correlation greater than 0.9, and a relative error less than 15%. Comparison of defibrillation thresholds also showed accurate prediction of the simulations. The high agreement of the potential maps and DFTs suggests that the predictive simulation generates realistic potential values and can accurately predict DFTs in patients. These validation results pave the way for use of this model in optimization studies prior to device implantation.

Indexed as

Computer SimulationDefibrillators, ImplantableAdolescentAdultAlgorithmsArrhythmias, CardiacBody Surface Potential MappingChildElectrodesEquipment DesignHeart RateHumansLinear ModelsReproducibility of ResultsVentricular FibrillationBody surface mappingDefibrillationDefibrillation modelingDefibrillation thresholdLimited lead selectionPatient-specific modeling

Identifiers

PMID30195579
PMCPMC6221557

What OpenQuestion holds

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Registered trials

None linked

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.