A Highly Predictive Risk Model for Pacemaker Implantation After TAVR

This study sought to develop a robust and definitive risk model for new permanent pacemaker implantation (PPMI) after SAPIEN 3 (third generation balloon expandable valve) (Edwards Lifesciences, Irvine, California) transcatheter aortic valve replacement (third generation balloon expandable valve TAVR...

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Published inJACC. Cardiovascular imaging Vol. 10; no. 10; pp. 1139 - 1147
Main Authors Maeno, Yoshio, Abramowitz, Yigal, Kawamori, Hiroyuki, Kazuno, Yoshio, Kubo, Shunsuke, Takahashi, Nobuyuki, Mangat, Geeteshwar, Okuyama, Kazuaki, Kashif, Mohammad, Chakravarty, Tarun, Nakamura, Mamoo, Cheng, Wen, Friedman, John, Berman, Daniel, Makkar, Raj R., Jilaihawi, Hasan
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.10.2017
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Abstract This study sought to develop a robust and definitive risk model for new permanent pacemaker implantation (PPMI) after SAPIEN 3 (third generation balloon expandable valve) (Edwards Lifesciences, Irvine, California) transcatheter aortic valve replacement (third generation balloon expandable valve TAVR), including calcification in the aortic-valvular complex (AVC). The association between calcium in the AVC and need for PPMI is poorly delineated after third generation balloon expandable valve TAVR. At Cedars-Sinai Heart Institute in Los Angeles, California, a total of 240 patients with severe aortic stenosis underwent third generation balloon expandable valve TAVR and had contrast computed tomography. AVC was characterized precisely by leaflet sector and region. The total new PPMI rate was 14.6%. On multivariate analysis for predictors of PPMI, pre-procedure third generation balloon expandable valve TAVR, right bundle branch block (RBBB), shorter membranous septum (MS) length, and noncoronary cusp device-landing zone calcium volume (NCC-DLZ CA) were included. Predictive probabilities were generated using this logistic regression model. If 3 pre-procedural risk factors were present, the c-statistic of the model for PPMI was area under the curve of 0.88, sensitivity of 77.1%, and specificity of 87.1%; this risk model had high negative predictive value (95.7%). The addition of the procedural factor of device depth to the model, with the parameter of difference between implantation depth and MS length, combined with RBBB and NCC-DLZ CA increased the c-statistic to 0.92, sensitivity to 94.3%, specificity to 83.8%, and negative predictive value to 98.8% By using a precise characterization of distribution of calcification in the AVC in a single-center, retrospective study, NCC-DLZ CA was found to be an independent predictor of new PPMI post–third generation balloon expandable valve TAVR. The findings also reinforce the importance of short MS length, pre-existing RBBB, and ventricular implantation depth as important synergistic PPMI risk factors. This risk model will need validation by future prospective multicenter studies. [Display omitted]
AbstractList This study sought to develop a robust and definitive risk model for new permanent pacemaker implantation (PPMI) after SAPIEN 3 (third generation balloon expandable valve) (Edwards Lifesciences, Irvine, California) transcatheter aortic valve replacement (third generation balloon expandable valve TAVR), including calcification in the aortic-valvular complex (AVC).OBJECTIVESThis study sought to develop a robust and definitive risk model for new permanent pacemaker implantation (PPMI) after SAPIEN 3 (third generation balloon expandable valve) (Edwards Lifesciences, Irvine, California) transcatheter aortic valve replacement (third generation balloon expandable valve TAVR), including calcification in the aortic-valvular complex (AVC).The association between calcium in the AVC and need for PPMI is poorly delineated after third generation balloon expandable valve TAVR.BACKGROUNDThe association between calcium in the AVC and need for PPMI is poorly delineated after third generation balloon expandable valve TAVR.At Cedars-Sinai Heart Institute in Los Angeles, California, a total of 240 patients with severe aortic stenosis underwent third generation balloon expandable valve TAVR and had contrast computed tomography. AVC was characterized precisely by leaflet sector and region.METHODSAt Cedars-Sinai Heart Institute in Los Angeles, California, a total of 240 patients with severe aortic stenosis underwent third generation balloon expandable valve TAVR and had contrast computed tomography. AVC was characterized precisely by leaflet sector and region.The total new PPMI rate was 14.6%. On multivariate analysis for predictors of PPMI, pre-procedure third generation balloon expandable valve TAVR, right bundle branch block (RBBB), shorter membranous septum (MS) length, and noncoronary cusp device-landing zone calcium volume (NCC-DLZ CA) were included. Predictive probabilities were generated using this logistic regression model. If 3 pre-procedural risk factors were present, the c-statistic of the model for PPMI was area under the curve of 0.88, sensitivity of 77.1%, and specificity of 87.1%; this risk model had high negative predictive value (95.7%). The addition of the procedural factor of device depth to the model, with the parameter of difference between implantation depth and MS length, combined with RBBB and NCC-DLZ CA increased the c-statistic to 0.92, sensitivity to 94.3%, specificity to 83.8%, and negative predictive value to 98.8% CONCLUSIONS: By using a precise characterization of distribution of calcification in the AVC in a single-center, retrospective study, NCC-DLZ CA was found to be an independent predictor of new PPMI post-third generation balloon expandable valve TAVR. The findings also reinforce the importance of short MS length, pre-existing RBBB, and ventricular implantation depth as important synergistic PPMI risk factors. This risk model will need validation by future prospective multicenter studies.RESULTSThe total new PPMI rate was 14.6%. On multivariate analysis for predictors of PPMI, pre-procedure third generation balloon expandable valve TAVR, right bundle branch block (RBBB), shorter membranous septum (MS) length, and noncoronary cusp device-landing zone calcium volume (NCC-DLZ CA) were included. Predictive probabilities were generated using this logistic regression model. If 3 pre-procedural risk factors were present, the c-statistic of the model for PPMI was area under the curve of 0.88, sensitivity of 77.1%, and specificity of 87.1%; this risk model had high negative predictive value (95.7%). The addition of the procedural factor of device depth to the model, with the parameter of difference between implantation depth and MS length, combined with RBBB and NCC-DLZ CA increased the c-statistic to 0.92, sensitivity to 94.3%, specificity to 83.8%, and negative predictive value to 98.8% CONCLUSIONS: By using a precise characterization of distribution of calcification in the AVC in a single-center, retrospective study, NCC-DLZ CA was found to be an independent predictor of new PPMI post-third generation balloon expandable valve TAVR. The findings also reinforce the importance of short MS length, pre-existing RBBB, and ventricular implantation depth as important synergistic PPMI risk factors. This risk model will need validation by future prospective multicenter studies.
This study sought to develop a robust and definitive risk model for new permanent pacemaker implantation (PPMI) after SAPIEN 3 (third generation balloon expandable valve) (Edwards Lifesciences, Irvine, California) transcatheter aortic valve replacement (third generation balloon expandable valve TAVR), including calcification in the aortic-valvular complex (AVC). The association between calcium in the AVC and need for PPMI is poorly delineated after third generation balloon expandable valve TAVR. At Cedars-Sinai Heart Institute in Los Angeles, California, a total of 240 patients with severe aortic stenosis underwent third generation balloon expandable valve TAVR and had contrast computed tomography. AVC was characterized precisely by leaflet sector and region. The total new PPMI rate was 14.6%. On multivariate analysis for predictors of PPMI, pre-procedure third generation balloon expandable valve TAVR, right bundle branch block (RBBB), shorter membranous septum (MS) length, and noncoronary cusp device-landing zone calcium volume (NCC-DLZ CA) were included. Predictive probabilities were generated using this logistic regression model. If 3 pre-procedural risk factors were present, the c-statistic of the model for PPMI was area under the curve of 0.88, sensitivity of 77.1%, and specificity of 87.1%; this risk model had high negative predictive value (95.7%). The addition of the procedural factor of device depth to the model, with the parameter of difference between implantation depth and MS length, combined with RBBB and NCC-DLZ CA increased the c-statistic to 0.92, sensitivity to 94.3%, specificity to 83.8%, and negative predictive value to 98.8% By using a precise characterization of distribution of calcification in the AVC in a single-center, retrospective study, NCC-DLZ CA was found to be an independent predictor of new PPMI post–third generation balloon expandable valve TAVR. The findings also reinforce the importance of short MS length, pre-existing RBBB, and ventricular implantation depth as important synergistic PPMI risk factors. This risk model will need validation by future prospective multicenter studies. [Display omitted]
This study sought to develop a robust and definitive risk model for new permanent pacemaker implantation (PPMI) after SAPIEN 3 (third generation balloon expandable valve) (Edwards Lifesciences, Irvine, California) transcatheter aortic valve replacement (third generation balloon expandable valve TAVR), including calcification in the aortic-valvular complex (AVC). The association between calcium in the AVC and need for PPMI is poorly delineated after third generation balloon expandable valve TAVR. At Cedars-Sinai Heart Institute in Los Angeles, California, a total of 240 patients with severe aortic stenosis underwent third generation balloon expandable valve TAVR and had contrast computed tomography. AVC was characterized precisely by leaflet sector and region. The total new PPMI rate was 14.6%. On multivariate analysis for predictors of PPMI, pre-procedure third generation balloon expandable valve TAVR, right bundle branch block (RBBB), shorter membranous septum (MS) length, and noncoronary cusp device-landing zone calcium volume (NCC-DLZ CA) were included. Predictive probabilities were generated using this logistic regression model. If 3 pre-procedural risk factors were present, the c-statistic of the model for PPMI was area under the curve of 0.88, sensitivity of 77.1%, and specificity of 87.1%; this risk model had high negative predictive value (95.7%). The addition of the procedural factor of device depth to the model, with the parameter of difference between implantation depth and MS length, combined with RBBB and NCC-DLZ CA increased the c-statistic to 0.92, sensitivity to 94.3%, specificity to 83.8%, and negative predictive value to 98.8% CONCLUSIONS: By using a precise characterization of distribution of calcification in the AVC in a single-center, retrospective study, NCC-DLZ CA was found to be an independent predictor of new PPMI post-third generation balloon expandable valve TAVR. The findings also reinforce the importance of short MS length, pre-existing RBBB, and ventricular implantation depth as important synergistic PPMI risk factors. This risk model will need validation by future prospective multicenter studies.
Abstract Objectives This study sought to develop a robust and definitive risk model for new permanent pacemaker implantation (PPMI) after SAPIEN 3 (third generation balloon expandable valve) (Edwards Lifesciences, Irvine, California) transcatheter aortic valve replacement (third generation balloon expandable valve TAVR), including calcification in the aortic-valvular complex (AVC). Background The association between calcium in the AVC and need for PPMI is poorly delineated after third generation balloon expandable valve TAVR. Methods At Cedars-Sinai Heart Institute in Los Angeles, California, a total of 240 patients with severe aortic stenosis underwent third generation balloon expandable valve TAVR and had contrast computed tomography. AVC was characterized precisely by leaflet sector and region. Results The total new PPMI rate was 14.6%. On multivariate analysis for predictors of PPMI, pre-procedure third generation balloon expandable valve TAVR, right bundle branch block (RBBB), shorter membranous septum (MS) length, and noncoronary cusp device-landing zone calcium volume (NCC-DLZ CA) were included. Predictive probabilities were generated using this logistic regression model. If 3 pre-procedural risk factors were present, the c-statistic of the model for PPMI was area under the curve of 0.88, sensitivity of 77.1%, and specificity of 87.1%; this risk model had high negative predictive value (95.7%). The addition of the procedural factor of device depth to the model, with the parameter of difference between implantation depth and MS length, combined with RBBB and NCC-DLZ CA increased the c-statistic to 0.92, sensitivity to 94.3%, specificity to 83.8%, and negative predictive value to 98.8% Conclusions By using a precise characterization of distribution of calcification in the AVC in a single-center, retrospective study, NCC-DLZ CA was found to be an independent predictor of new PPMI post–third generation balloon expandable valve TAVR. The findings also reinforce the importance of short MS length, pre-existing RBBB, and ventricular implantation depth as important synergistic PPMI risk factors. This risk model will need validation by future prospective multicenter studies.
Author Chakravarty, Tarun
Kazuno, Yoshio
Kawamori, Hiroyuki
Jilaihawi, Hasan
Abramowitz, Yigal
Maeno, Yoshio
Mangat, Geeteshwar
Nakamura, Mamoo
Takahashi, Nobuyuki
Kashif, Mohammad
Okuyama, Kazuaki
Makkar, Raj R.
Berman, Daniel
Cheng, Wen
Kubo, Shunsuke
Friedman, John
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  givenname: Yoshio
  surname: Maeno
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  givenname: Yigal
  surname: Abramowitz
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  surname: Kawamori
  fullname: Kawamori, Hiroyuki
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  givenname: Yoshio
  surname: Kazuno
  fullname: Kazuno, Yoshio
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  givenname: Shunsuke
  surname: Kubo
  fullname: Kubo, Shunsuke
– sequence: 6
  givenname: Nobuyuki
  surname: Takahashi
  fullname: Takahashi, Nobuyuki
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  givenname: Geeteshwar
  surname: Mangat
  fullname: Mangat, Geeteshwar
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  givenname: Kazuaki
  surname: Okuyama
  fullname: Okuyama, Kazuaki
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  surname: Chakravarty
  fullname: Chakravarty, Tarun
– sequence: 11
  givenname: Mamoo
  surname: Nakamura
  fullname: Nakamura, Mamoo
– sequence: 12
  givenname: Wen
  surname: Cheng
  fullname: Cheng, Wen
– sequence: 13
  givenname: John
  surname: Friedman
  fullname: Friedman, John
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  givenname: Daniel
  surname: Berman
  fullname: Berman, Daniel
– sequence: 15
  givenname: Raj R.
  surname: Makkar
  fullname: Makkar, Raj R.
– sequence: 16
  givenname: Hasan
  surname: Jilaihawi
  fullname: Jilaihawi, Hasan
  email: hasanjilaihawi@gmail.com
BackLink https://www.ncbi.nlm.nih.gov/pubmed/28412434$$D View this record in MEDLINE/PubMed
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Issue 10
Keywords predictors
transcatheter aortic valve implantation
pacemaker
BE
MS
LVOT
TAVR
NCC
DLZ
Δ MSID
RBBB
transcatheter aortic valve replacement
PPMI
calcification
CA
right bundle branch block
left ventricular outflow tract
calcium volume
noncoronary cusp
balloon-expandable
difference between membranous septum length and implantation depth
permanent pacemaker implantation
device landing zone
membranous septum
Language English
License This article is made available under the Elsevier license.
Copyright © 2017. Published by Elsevier Inc.
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Snippet This study sought to develop a robust and definitive risk model for new permanent pacemaker implantation (PPMI) after SAPIEN 3 (third generation balloon...
Abstract Objectives This study sought to develop a robust and definitive risk model for new permanent pacemaker implantation (PPMI) after SAPIEN 3 (third...
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StartPage 1139
SubjectTerms Aged
Aged, 80 and over
Aortic Valve - diagnostic imaging
Aortic Valve - pathology
Aortic Valve - physiopathology
Aortic Valve - surgery
Aortic Valve Stenosis - diagnostic imaging
Aortic Valve Stenosis - physiopathology
Aortic Valve Stenosis - surgery
Balloon Valvuloplasty - adverse effects
Bundle-Branch Block - diagnosis
Bundle-Branch Block - etiology
Bundle-Branch Block - physiopathology
Bundle-Branch Block - therapy
calcification
Calcinosis - diagnostic imaging
Calcinosis - physiopathology
Calcinosis - surgery
Cardiac Pacing, Artificial
Cardiovascular
Databases, Factual
Decision Support Techniques
Female
Humans
Logistic Models
Los Angeles
Male
Multidetector Computed Tomography
Multivariate Analysis
pacemaker
Pacemaker, Artificial
Predictive Value of Tests
predictors
Retrospective Studies
Risk Factors
Severity of Illness Index
Time Factors
transcatheter aortic valve implantation
transcatheter aortic valve replacement
Transcatheter Aortic Valve Replacement - adverse effects
Treatment Outcome
Title A Highly Predictive Risk Model for Pacemaker Implantation After TAVR
URI https://www.clinicalkey.com/#!/content/1-s2.0-S1936878X17301523
https://www.clinicalkey.es/playcontent/1-s2.0-S1936878X17301523
https://dx.doi.org/10.1016/j.jcmg.2016.11.020
https://www.ncbi.nlm.nih.gov/pubmed/28412434
https://www.proquest.com/docview/1888957880
Volume 10
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