Evidence map›Paper›PMID 31221358›Full record

ArticleJACC. Clinical electrophysiology2019

Quantification of Electromechanical Coupling to Prevent Inappropriate Implantable Cardioverter-Defibrillator Shocks.

Daniel Keene, Matthew J Shun-Shin, Ahran D Arnold, James P Howard, David Lefroy, D Wyn Davies, Phang Boon Lim, Fu Siong Ng, Michael Koa-Wing, Norman A Qureshi and 6 more

Abstract read
In one paragraph

Article in JACC. Clinical electrophysiology, 2019. 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. Therapeutic potential of conduction system pacing as a method for improving cardiac output during ventricular tachycardia.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2024
    Article
  2. Review
  3. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Daniel KeeneDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom. Electronic address: d.keene@imperial.ac.uk.
Matthew J Shun-ShinDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
Ahran D ArnoldDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
James P HowardDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
David LefroyDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom.
D Wyn DaviesDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom.
Phang Boon LimDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
Fu Siong NgDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
Michael Koa-WingDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
Norman A QureshiDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
Nick W F LintonDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
Jaymin S ShahDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom.
Nicholas S PetersDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
Prapa KanagaratnamDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
Darrel P FrancisDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
Zachary I WhinnettDepartment of Cardiology, Imperial College Hospitals National Health Service Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.

Funding

British Heart Foundation FS/13/44/30291British Heart Foundation FS/15/25/31423British Heart Foundation FS/15/53/31615British Heart Foundation RG/16/3/32175
6 · The paper itself

Abstract

objectivesThis study sought to test specialized processing of laser Doppler signals for discriminating ventricular fibrillation (VF) from common causes of inappropriate therapies.

backgroundInappropriate implantable cardioverter-defibrillator (ICD) therapies remain a clinically important problem associated with morbidity and mortality. Tissue perfusion biomarkers, implemented to assist automated diagnosis of VF, sometimes mistake artifacts and random noise for perfusion, which could lead to shocks being inappropriately withheld.

methodsThe study tested a novel processing algorithm that combines electrogram data and laser Doppler perfusion monitoring as a method for assessing circulatory status. Fifty patients undergoing VF induction during ICD implantation were recruited. Noninvasive laser Doppler and continuous electrograms were recorded during both sinus rhythm and VF. Two additional scenarios that might have led to inappropriate shocks were simulated for each patient: ventricular lead fracture and T-wave oversensing. The laser Doppler was analyzed using 3 methods for reducing noise: 1) running mean; 2) oscillatory height; and 3) a novel quantification of electromechanical coupling which gates laser Doppler relative to electrograms. In addition, the algorithm was tested during exercise-induced sinus tachycardia.

resultsOnly the electromechanical coupling algorithm found a clear perfusion cut off between sinus rhythm and VF (sensitivity and specificity of 100%). Sensitivity and specificity remained at 100% during simulated lead fracture and electrogram oversensing. (Area under the curve running mean: 0.91; oscillatory height: 0.86; electromechanical coupling: 1.00). Sinus tachycardia did not cause false positive results.

conclusionsQuantifying the coupling between electrical and perfusion signals increases reliability of discrimination between VF and artifacts that ICDs may interpret as VF. Incorporating such methods into future ICDs may safely permit reductions of inappropriate shocks.

Indexed as

Defibrillators, ImplantableElectric CountershockElectrocardiographyEquipment FailureLaser-Doppler FlowmetrySignal Processing, Computer-AssistedAgedAlgorithmsElectrophysiologic Techniques, CardiacExerciseFemaleHumansMaleMiddle AgedSensitivity and SpecificityTachycardia, Sinusarrhythmia discriminationhemodynamic monitoringimplantable cardioverter-defibrillatorinappropriate therapylaser Doppler perfusion monitoring

Identifiers

PMID31221358
PMCPMC6597902

What OpenQuestion holds

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LicenceCC BY
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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.