Literature DB >> 29275955

Inter- and intra-observer variability of visual fragmented QRS scoring in ischemic and non-ischemic cardiomyopathy.

Bert Vandenberk1, Tomas Robyns2, Griet Goovaerts3, Mathias Claeys2, Frederik Helsen2, Sofie Van Soest4, Christophe Garweg2, Joris Ector2, Sabine Van Huffel3, Rik Willems2.   

Abstract

BACKGROUND: Fragmented QRS (fQRS) on a 12-lead ECG has been linked with adverse outcome. However, the visual scoring of ECGs is prone to inter- and intra-observer variability.
METHODS: Five observers, two experienced and three novel, assessed fQRS in 712 digital ECGs, 100 were re-evaluated to assess intra-observer variability. Fleiss and Cohen's Kappa were calculated and compared between subgroups.
RESULTS: The inter-observer variability for assessing fQRS in all leads combined was substantial with a Kappa of 0.651. Experienced observers only had a better agreement with a Kappa of 0.823. Intra-observer variability ranged from 0.736 to 0.880. In the subgroup with ventricular pacing the inter-observer variability was even significantly larger when compared to ECGs with normal QRS duration (Kappa 0.493 vs 0.664, p<0.001).
CONCLUSION: The visual assessment of QRS fragmentation is prone to inter- and intra-observer variability, mainly influenced by the experience of the observers, the underlying rhythm and QRS morphology.
Copyright © 2017. Published by Elsevier Inc.

Entities:  

Keywords:  Fragmented QRS; Inter-observer variability; Intra-observer variability

Mesh:

Year:  2017        PMID: 29275955     DOI: 10.1016/j.jelectrocard.2017.12.002

Source DB:  PubMed          Journal:  J Electrocardiol        ISSN: 0022-0736            Impact factor:   1.438


  7 in total

1.  Genotype-phenotype relationship and risk stratification in loss-of-function SCN5A mutation carriers.

Authors:  Tomas Robyns; Dieter Nuyens; Bert Vandenberk; Cuno Kuiperi; Anniek Corveleyn; Jeroen Breckpot; Christophe Garweg; Joris Ector; Rik Willems
Journal:  Ann Noninvasive Electrocardiol       Date:  2018-04-30       Impact factor: 1.468

2.  Life-threatening ventricular arrhythmia prediction in patients with dilated cardiomyopathy using explainable electrocardiogram-based deep neural networks.

Authors:  Arjan Sammani; Rutger R van de Leur; Michiel T H M Henkens; Mathias Meine; Peter Loh; Rutger J Hassink; Daniel L Oberski; Stephane R B Heymans; Pieter A Doevendans; Folkert W Asselbergs; Anneline S J M Te Riele; René van Es
Journal:  Europace       Date:  2022-10-13       Impact factor: 5.486

3.  Measuring agreement among experts in classifying camera images of similar species.

Authors:  T J Gooliaff; Karen E Hodges
Journal:  Ecol Evol       Date:  2018-10-30       Impact factor: 2.912

Review 4.  Fragmented QRS - Its significance.

Authors:  R N Supreeth; Johnson Francis
Journal:  Indian Pacing Electrophysiol J       Date:  2019-12-13

5.  Repolarization abnormalities on admission predict 1-year outcome in COVID-19 patients.

Authors:  Bert Vandenberk; Matthias M Engelen; Greet Van De Sijpe; Jonas Vermeulen; Stefan Janssens; Thomas Vanassche; Peter Verhamme; Paul De Munter; Natalie Lorent; Rik Willems
Journal:  Int J Cardiol Heart Vasc       Date:  2021-11-03

6.  A machine learning algorithm for electrocardiographic fQRS quantification validated on multi-center data.

Authors:  Amalia Villa; Bert Vandenberk; Tuomas Kenttä; Sebastian Ingelaere; Heikki V Huikuri; Markus Zabel; Tim Friede; Christian Sticherling; Anton Tuinenburg; Marek Malik; Sabine Van Huffel; Rik Willems; Carolina Varon
Journal:  Sci Rep       Date:  2022-04-26       Impact factor: 4.996

7.  Fragmented QRS is associated with intraventricular dyssynchrony and independently predicts nonresponse to cardiac resynchronization therapy-Systematic review and meta-analysis.

Authors:  Raymond Pranata; Emir Yonas; Rachel Vania; Alexander Edo Tondas; Yoga Yuniadi
Journal:  Ann Noninvasive Electrocardiol       Date:  2020-03-18       Impact factor: 1.468

  7 in total

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