Evidence map›Paper›PMID 29724033›Full record

ArticleSensors (Basel, Switzerland)2018

Force Trends and Pulsatility for Catheter Contact Identification in Intracardiac Electrograms during Arrhythmia Ablation.

David Rivas-Lalaleo, Sergio Muñoz-Romero, Mónica Huerta, Mayra Erazo-Rodas, Juan José Sánchez-Muñoz, José Luis Rojo-Álvarez, Arcadi García-Alberola

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 37% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

7 authors at 4 institutions in 2 countries.

David Rivas-LalaleoDepartamento de Eléctrica y Electrónica, Universidad de las Fuerzas Armadas ESPE, Av. General Rumiñahui s/n, 170501 Sangolquí, Ecuador. drrivas@espe.edu.ec.ORCID 0000-0001-5958-6606
Sergio Muñoz-RomeroDepartment of Signal Theory and Communications and Telematic Systems and Computation, Rey Juan Carlos University, Fuenlabrada, 28943 Madrid, Spain. sergio.munoz@urjc.es.
Mónica HuertaUniversidad Politécnica Salesiana, 010105 Cuenca, Ecuador. mhuerta@ups.edu.ec.ORCID 0000-0003-4435-7987
Mayra Erazo-RodasDepartamento de Eléctrica y Electrónica, Universidad de las Fuerzas Armadas ESPE, Av. General Rumiñahui s/n, 170501 Sangolquí, Ecuador. mjerazo@espe.edu.ec.
Juan José Sánchez-MuñozArrhythmia Unit, University Clinic Hospital Virgen de la Arrixaca, El Palmar, 30120 Murcia, Spain. juanjosanchezmunoz@me.com.
José Luis Rojo-ÁlvarezDepartment of Signal Theory and Communications and Telematic Systems and Computation, Rey Juan Carlos University, Fuenlabrada, 28943 Madrid, Spain. joseluis.rojo@urjc.es.ORCID 0000-0003-0426-8912
Arcadi García-AlberolaArrhythmia Unit, University Clinic Hospital Virgen de la Arrixaca, El Palmar, 30120 Murcia, Spain. arcadi@secardiologia.es.
Hospital Universitario Virgen de la Arrixaca · ESUniversidad de las Fuerzas Armadas ESPE · ECUniversidad Rey Juan Carlos · ESPolitecnica Salesiana University · EC

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The intracardiac electrical activation maps are commonly used as a guide in the ablation of cardiac arrhythmias. The use of catheters with force sensors has been proposed in order to know if the electrode is in contact with the tissue during the registration of intracardiac electrograms (EGM). Although threshold criteria on force signals are often used to determine the catheter contact, this may be a limited criterion due to the complexity of the heart dynamics and cardiac vorticity. The present paper is devoted to determining the criteria and force signal profiles that guarantee the contact of the electrode with the tissue. In this study, we analyzed 1391 force signals and their associated EGM recorded during 2 and 8 s, respectively, in 17 patients (82 ± 60 points per patient). We aimed to establish a contact pattern by first visually examining and classifying the signals, according to their likely-contact joint profile and following the suggestions from experts in the doubtful cases. First, we used Principal Component Analysis to scrutinize the force signal dynamics by analyzing the main eigen-directions, first globally and then grouped according to the certainty of their tissue-catheter contact. Second, we used two different linear classifiers (Fisher discriminant and support vector machines) to identify the most relevant components of the previous signal models. We obtained three main types of eigenvectors, namely, pulsatile relevant, non-pulsatile relevant, and irrelevant components. The classifiers reached a moderate to sufficient discrimination capacity (areas under the curve between 0.84 and 0.95 depending on the contact certainty and on the classifier), which allowed us to analyze the relevant properties in the force signals. We conclude that the catheter-tissue contact profiles in force recordings are complex and do not depend only on the signal intensity being above a threshold at a single time instant, but also on time pulsatility and trends. These findings pave the way towards a subsystem which can be included in current intracardiac navigation systems assisted by force contact sensors, and it can provide the clinician with an estimate of the reliability on the tissue-catheter contact in the point-by-point EGM acquisition procedure.

Indexed as

Arrhythmias, CardiacCatheter AblationElectrophysiologic Techniques, CardiacHumansReproducibility of Resultsarrhythmiaselectrogramsforce signalslinear classifiersPrincipal Component Analysistissue-catheter contact

Identifiers

PMID29724033
PMCPMC5981834
OpenAlexW2800426502

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.