open access

Vol 22, No 2 (2015)
Original articles
Submitted: 2014-05-11
Accepted: 2014-10-24
Published online: 2015-04-28
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A new score system for predicting response to cardiac resynchronization therapy

Yu Kang, Leilei Cheng, Jie Cui, Lin Li, Shengmei Qin, Yangang Su, Jialiang Mao, Xue Gong, Haiyan Chen, Cuizhen Pan, Xuedong Shen, Ben He, Xianhong Shu
DOI: 10.5603/CJ.a2014.0089
·
Pubmed: 25428735
·
Cardiol J 2015;22(2):179-187.

open access

Vol 22, No 2 (2015)
Original articles
Submitted: 2014-05-11
Accepted: 2014-10-24
Published online: 2015-04-28

Abstract

Background: The aim of this study was to establish a score system derived from clinical, echocardiographic and electrocardiographic indexes and evaluate its clinical value for cardiac resynchronization therapy (CRT) patient selection.

Methods: Ninety-three patients receiving CRT were enrolled. A patient selection score system was generated by the clinical, echocardiographic and electrocardiographic parameters achieving a significant level by univariate and multivariate Cox regression model. The positive response to CRT was a left ventricular end systolic volume decrease of ≥ 15% and not reaching primary clinical endpoint (death or re-hospitalization for heart failure) at the end of follow-up.

Results: Thirty-nine patients were CRT non-responders (41.94%) and 54 were responders (58.06%). A 4-point score system was generated based on tricuspid annular plane systolic ex­cursion (TAPSE), longitudinal strain (LS), and complete left bundle branch block (CLBBB) combined with a wide QRS duration (QRSd). The sensitivity and specificity for prediction of a positive response to CRT at a score > 2 were 0.823 and 0.850, respectively (AUC: 0.92295% CI 0.691–0.916, p< 0.001).

Conclusions: A patient selection score system based on the integration of TAPSE, LS and CLBBB combined with a wide QRSd can help to predict positive response to CRT effectively and reliably.

Abstract

Background: The aim of this study was to establish a score system derived from clinical, echocardiographic and electrocardiographic indexes and evaluate its clinical value for cardiac resynchronization therapy (CRT) patient selection.

Methods: Ninety-three patients receiving CRT were enrolled. A patient selection score system was generated by the clinical, echocardiographic and electrocardiographic parameters achieving a significant level by univariate and multivariate Cox regression model. The positive response to CRT was a left ventricular end systolic volume decrease of ≥ 15% and not reaching primary clinical endpoint (death or re-hospitalization for heart failure) at the end of follow-up.

Results: Thirty-nine patients were CRT non-responders (41.94%) and 54 were responders (58.06%). A 4-point score system was generated based on tricuspid annular plane systolic ex­cursion (TAPSE), longitudinal strain (LS), and complete left bundle branch block (CLBBB) combined with a wide QRS duration (QRSd). The sensitivity and specificity for prediction of a positive response to CRT at a score > 2 were 0.823 and 0.850, respectively (AUC: 0.92295% CI 0.691–0.916, p< 0.001).

Conclusions: A patient selection score system based on the integration of TAPSE, LS and CLBBB combined with a wide QRSd can help to predict positive response to CRT effectively and reliably.

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Keywords

two-dimensional speckle tracking echocardiography, real-time three-dimensional echocardiography, cardiac resynchronization therapy

About this article
Title

A new score system for predicting response to cardiac resynchronization therapy

Journal

Cardiology Journal

Issue

Vol 22, No 2 (2015)

Pages

179-187

Published online

2015-04-28

Page views

2176

Article views/downloads

1618

DOI

10.5603/CJ.a2014.0089

Pubmed

25428735

Bibliographic record

Cardiol J 2015;22(2):179-187.

Keywords

two-dimensional speckle tracking echocardiography
real-time three-dimensional echocardiography
cardiac resynchronization therapy

Authors

Yu Kang
Leilei Cheng
Jie Cui
Lin Li
Shengmei Qin
Yangang Su
Jialiang Mao
Xue Gong
Haiyan Chen
Cuizhen Pan
Xuedong Shen
Ben He
Xianhong Shu

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