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 in | JACC. Cardiovascular imaging Vol. 10; no. 10; pp. 1139 - 1147 |
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Main Authors | , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.10.2017
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Subjects | |
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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.
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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 |
Author_xml | – sequence: 1 givenname: Yoshio surname: Maeno fullname: Maeno, Yoshio – sequence: 2 givenname: Yigal surname: Abramowitz fullname: Abramowitz, Yigal – sequence: 3 givenname: Hiroyuki surname: Kawamori fullname: Kawamori, Hiroyuki – sequence: 4 givenname: Yoshio surname: Kazuno fullname: Kazuno, Yoshio – sequence: 5 givenname: Shunsuke surname: Kubo fullname: Kubo, Shunsuke – sequence: 6 givenname: Nobuyuki surname: Takahashi fullname: Takahashi, Nobuyuki – sequence: 7 givenname: Geeteshwar surname: Mangat fullname: Mangat, Geeteshwar – sequence: 8 givenname: Kazuaki surname: Okuyama fullname: Okuyama, Kazuaki – sequence: 9 givenname: Mohammad surname: Kashif fullname: Kashif, Mohammad – sequence: 10 givenname: Tarun 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 – sequence: 14 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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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 |
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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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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 |
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