Statistical ranking of electromechanical dyssynchrony parameters for CRT

Objective Mechanical evaluation of dyssynchrony by echocardiography has not replaced ECG in routine cardiac resynchronisation therapy (CRT) evaluation because of its complexity and lack of reproducibility. The objective of this study was to evaluate the potential correlations between electromechanic...

Full description

Saved in:
Bibliographic Details
Main Authors: Serge Cazeau, Matthieu Toulemont, Philippe Ritter, Julien Reygner
Format: Article
Language:English
Published: BMJ Publishing Group 2019-05-01
Series:Open Heart
Online Access:https://openheart.bmj.com/content/6/1/e000933.full
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1846169863061504000
author Serge Cazeau
Matthieu Toulemont
Philippe Ritter
Julien Reygner
author_facet Serge Cazeau
Matthieu Toulemont
Philippe Ritter
Julien Reygner
author_sort Serge Cazeau
collection DOAJ
description Objective Mechanical evaluation of dyssynchrony by echocardiography has not replaced ECG in routine cardiac resynchronisation therapy (CRT) evaluation because of its complexity and lack of reproducibility. The objective of this study was to evaluate the potential correlations between electromechanical parameters (atrioventricular, interventricular and intraventricular from the dyssynchrony model presented in 2000), their ability to describe dyssynchrony and their potential use in resynchrony.Methods 455 sets of the 18 parameters of the model obtained in 91 patients submitted to various pacing configurations were evaluated two by two using a Pearson correlation test and then by groups according to their ability to describe dyssynchrony, using the Column selection method of machine learning.Results The best parameter is duration of septal contraction, which alone describes 25% of dyssynchrony. The best groups of 3, 4 and ≥8 variables describe 59%, 73% and almost 100% of dyssynchrony, respectively. Left pre-ejection interval is highly and significantly correlated to a maximum of other variables, and its decrease is associated with the favourable evolution of all other correlated parameters. Increase in filling duration and decrease in duration of septum to lateral wall contraction difference are not associated with the favourable evolution of other parameters.Conclusions No single electromechanical parameter alone can fully describe dyssynchrony. The 18-parameter model can be simplified, but still requires at least 4–8 parameters. Decrease in left pre-ejection interval favourably drives resynchrony in a maximum of other parameters. Increase in filling duration and decrease in septum–lateral wall difference do not appear to be good CRT targets.
format Article
id doaj-art-43144f7c342649ae907c29bba811e53f
institution Kabale University
issn 2053-3624
language English
publishDate 2019-05-01
publisher BMJ Publishing Group
record_format Article
series Open Heart
spelling doaj-art-43144f7c342649ae907c29bba811e53f2024-11-12T07:15:08ZengBMJ Publishing GroupOpen Heart2053-36242019-05-016110.1136/openhrt-2018-000933Statistical ranking of electromechanical dyssynchrony parameters for CRTSerge Cazeau0Matthieu Toulemont1Philippe Ritter2Julien Reygner31 Service de Cardiologie, Hôpital Saint-Joseph, Paris, France3 Ecole des Ponts Paristech, Marne-la-Vallée, France4 Cardiology Department, University Hospital of Bordeaux, Pessac, France5 Center for Training and Research in MathematIcs and Scientific Computing (CERMICS), Université Paris-Est, ENPC, Marne-la-Vallée, FranceObjective Mechanical evaluation of dyssynchrony by echocardiography has not replaced ECG in routine cardiac resynchronisation therapy (CRT) evaluation because of its complexity and lack of reproducibility. The objective of this study was to evaluate the potential correlations between electromechanical parameters (atrioventricular, interventricular and intraventricular from the dyssynchrony model presented in 2000), their ability to describe dyssynchrony and their potential use in resynchrony.Methods 455 sets of the 18 parameters of the model obtained in 91 patients submitted to various pacing configurations were evaluated two by two using a Pearson correlation test and then by groups according to their ability to describe dyssynchrony, using the Column selection method of machine learning.Results The best parameter is duration of septal contraction, which alone describes 25% of dyssynchrony. The best groups of 3, 4 and ≥8 variables describe 59%, 73% and almost 100% of dyssynchrony, respectively. Left pre-ejection interval is highly and significantly correlated to a maximum of other variables, and its decrease is associated with the favourable evolution of all other correlated parameters. Increase in filling duration and decrease in duration of septum to lateral wall contraction difference are not associated with the favourable evolution of other parameters.Conclusions No single electromechanical parameter alone can fully describe dyssynchrony. The 18-parameter model can be simplified, but still requires at least 4–8 parameters. Decrease in left pre-ejection interval favourably drives resynchrony in a maximum of other parameters. Increase in filling duration and decrease in septum–lateral wall difference do not appear to be good CRT targets.https://openheart.bmj.com/content/6/1/e000933.full
spellingShingle Serge Cazeau
Matthieu Toulemont
Philippe Ritter
Julien Reygner
Statistical ranking of electromechanical dyssynchrony parameters for CRT
Open Heart
title Statistical ranking of electromechanical dyssynchrony parameters for CRT
title_full Statistical ranking of electromechanical dyssynchrony parameters for CRT
title_fullStr Statistical ranking of electromechanical dyssynchrony parameters for CRT
title_full_unstemmed Statistical ranking of electromechanical dyssynchrony parameters for CRT
title_short Statistical ranking of electromechanical dyssynchrony parameters for CRT
title_sort statistical ranking of electromechanical dyssynchrony parameters for crt
url https://openheart.bmj.com/content/6/1/e000933.full
work_keys_str_mv AT sergecazeau statisticalrankingofelectromechanicaldyssynchronyparametersforcrt
AT matthieutoulemont statisticalrankingofelectromechanicaldyssynchronyparametersforcrt
AT philipperitter statisticalrankingofelectromechanicaldyssynchronyparametersforcrt
AT julienreygner statisticalrankingofelectromechanicaldyssynchronyparametersforcrt