Literature DB >> 29552617

Aortic valve anatomy and outcomes after transcatheter aortic valve implantation in bicuspid aortic valves.

Chiara De Biase1, Antonios Mastrokostopoulos1, Raphael Philippart1, Louis Marie Desroche1, Stephanie Blanco1, Kamel Rehal1, Nicolas Dumonteil1, Didier Tchetche1.   

Abstract

This original clinical research study id focused on description of baseline anatomy and outcomes after transcatheter aortic valve implantation (TAVI) in patients presenting with severe aortic stenosis (AS) and bicuspid aortic valve (BAV). We compared this BAV population with a population of patients with AS and tricuspid aortic valves after a propensity score matching developed by a multivariate logistic regression according to a non-parsimonious approach. Baseline anatomical characteristics were obtained by transthoracic echocardiography (TTE) and multi-sliced computed tomography (MSCT) and compared by chi-square and t-student tests. Outcomes were evaluated by correct fisher test at in hospital and 30 days follow-up. We found that BAV patients presents more complicated baseline anatomy as compared to patients with tricuspid valves. These anatomical features lead to higher procedural complications as the need for a second device implantation. However this does not translate into increase in mortality rate at 30 days follow-up but rather correlate to a lower device success rate.

Entities:  

Year:  2018        PMID: 29552617      PMCID: PMC5852276          DOI: 10.1016/j.dib.2018.01.020

Source DB:  PubMed          Journal:  Data Brief        ISSN: 2352-3409


Specifications Table Value of the data Aortic stenosis in bicuspid aortic valve (BAV) remains a challenge for transcatheter aortic valve implantation (TAVI). BAV patients presenting severe aortic stenosis are increasing in clinical practice There is little evidence concerning TAVI in this population. Our data can be an additional evidence for the feasibility of TAVI in BAV. Indeed many questions are still open to optimize the sizing and find some dedicated devices for this population. Registries and sizing comparisons between operators could find a way to improve TAVI procedures in this subset.

Data

This study is a comparison analysis between patients with bicuspid or tricuspid aortic valves undergoing TAVI for severe AS. Patients with AS and BAV present more complicated baseline anatomy as compared to patients with tricuspid valves. These anatomical features correlate to a lower device success rate but are not related to increase in mortality rate at 30 days follow-up. The lower device success rate reported was mainly related to a second device implantation need since nor PVL or mean gradient and mortality rate were significantly different. Pre-procedural imaging and novel device technologies will help to address proper sizing and valve choice in the future.

Experimental design, materials, and methods

From January to December 2016, 460 patients with tricuspid aortic valve underwent TAVI procedure in our institution for symptomatic severe AS. From January 2015 to April 2017, 83 consecutive patients with BAV had TAVI at our institution. The majority of these patients were indeed treated in 2016 (87%). Patients undergoing TAVI due to bio-prosthesis degeneration were not included. BAV were classified following the Sievers classification as reported in Fig. 1 [1]. Multi-detector computed tomography (MDCT) and transthoracic echocardiogram (TTE) were assessed at baseline. BAV anatomy was identified by baseline MDCT after analysis using the 3mensio Structural Heart software version 8.0 (Pie Medical Imaging, Maastricht, the Netherlands) Workstation software. MDCT was the method of choice for sizing using the perimeter-derived diameter of the aortic annulus. In the BAV group, we used as additional measurement for sizing the inter-commissural distance 4 mm above the annulus.
Fig. 1

Bicuspid valve anatomy. L-N: left-non coronary cusps; L-R: left-right cusps; R-N: right-non coronary cusps.

Bicuspid valve anatomy. L-N: left-non coronary cusps; L-R: left-right cusps; R-N: right-non coronary cusps. Continue variables were compared using a Student’s T test and categorical variables with a chi-square test. A propensity-score matching was applied to account for differences in baseline characteristics of both groups. A 1:2 propensity-score matching was performed on the basis of clinical risk factors for cardiovascular mortality and was developed by a multivariate logistic regression according to a non-parsimonious approach [2], [3]. A total amount of 249 patients, 83 with bicuspid and 166 with tricuspid aortic valve, were included in the final analysis. Baseline anatomical features and procedural characteristics were compared between the two groups as previously described. Outcomes were evaluated following the Valve Academic Research Consortium-2 definitions (VARC)-2 definitions. PPM values were classified into mild, moderate, severe and were analyzed at both in-hospital and 30 days follow-up [4], [5], [6], [7] as reported in Fig. 2. Device success was evaluated at in-hospital follow-up and the early safety at 30 days [8].
Fig. 2

In-hospital and 30 days Prosthesis-patient mismatch (PPM).

In-hospital and 30 days Prosthesis-patient mismatch (PPM). The primary endpoint was all-cause mortality and early safety at 30 days. Secondary endpoint included device success. Statistical significance was considered as p Value ≤ 0.05. All results were obtained using the Statistical Package for the Social Sciences version 21.0 (SPSS v21.0, SPSS Inc, Chicago, IL).
Subject areaInterventional Cardiology
More specific subject areaPercutaneous valve implantation
Type of dataTable, text file, figure
How data was acquiredStatistical Package for the Social Sciences version 21.0 (SPSS v21.0, SPSS Inc, Chicago, IL). Student’s T test. Chi-square test.
Data formatContinuous variables are presented as mean ± standard deviation. Categorical variables are presented as count and percentages.
Experimental factorsNone
Experimental featuresNone
Data source locationCity: Toulouse, country: France.
Data accessibilityThe data are available with this article
Related research articleYoon SH, Bleiziffer S, De Backer O, Delgado V, Arai T, Ziegelmueller J, et al. Outcomes in Transcatheter Aortic Valve Replacement for Bicuspid Versus Tricuspid Aortic Valve Stenosis. Journal of the American College of Cardiology. 2017;69(21):2579-89. Epub 2017/03/24.
  8 in total

Review 1.  Prosthesis-patient mismatch: definition, clinical impact, and prevention.

Authors:  P Pibarot; J G Dumesnil
Journal:  Heart       Date:  2005-10-26       Impact factor: 5.994

2.  Variable selection for propensity score models.

Authors:  M Alan Brookhart; Sebastian Schneeweiss; Kenneth J Rothman; Robert J Glynn; Jerry Avorn; Til Stürmer
Journal:  Am J Epidemiol       Date:  2006-04-19       Impact factor: 4.897

3.  Prosthesis-patient mismatch and clinical outcomes: the evidence continues to accumulate.

Authors:  Jean G Dumesnil; Philippe Pibarot
Journal:  J Thorac Cardiovasc Surg       Date:  2006-05       Impact factor: 5.209

4.  A classification system for the bicuspid aortic valve from 304 surgical specimens.

Authors:  Hans-H Sievers; Claudia Schmidtke
Journal:  J Thorac Cardiovasc Surg       Date:  2007-05       Impact factor: 5.209

5.  Impact of prosthesis-patient mismatch on cardiac events and midterm mortality after aortic valve replacement in patients with pure aortic stenosis.

Authors:  Giordano Tasca; Zen Mhagna; Silvano Perotti; Pietro Berra Centurini; Tony Sabatini; Andrea Amaducci; Federico Brunelli; Marco Cirillo; Margherita Dalla Tomba; Eugenio Quaini; Eugenio Quiani; Giovanni Troise; Philippe Pibarot
Journal:  Circulation       Date:  2006-01-09       Impact factor: 29.690

Review 6.  Recommendations for the imaging assessment of prosthetic heart valves: a report from the European Association of Cardiovascular Imaging endorsed by the Chinese Society of Echocardiography, the Inter-American Society of Echocardiography, and the Brazilian Department of Cardiovascular Imaging.

Authors:  Patrizio Lancellotti; Philippe Pibarot; John Chambers; Thor Edvardsen; Victoria Delgado; Raluca Dulgheru; Mauro Pepi; Bernard Cosyns; Mark R Dweck; Madalina Garbi; Julien Magne; Koen Nieman; Raphael Rosenhek; Anne Bernard; Jorge Lowenstein; Marcelo Luiz Campos Vieira; Arnaldo Rabischoffsky; Rodrigo Hernández Vyhmeister; Xiao Zhou; Yun Zhang; Jose-Luis Zamorano; Gilbert Habib
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2016-05-03       Impact factor: 6.875

7.  Updated standardized endpoint definitions for transcatheter aortic valve implantation: the Valve Academic Research Consortium-2 consensus document (VARC-2).

Authors:  Arie Pieter Kappetein; Stuart J Head; Philippe Généreux; Nicolo Piazza; Nicolas M van Mieghem; Eugene H Blackstone; Thomas G Brott; David J Cohen; Donald E Cutlip; Gerrit-Anne van Es; Rebecca T Hahn; Ajay J Kirtane; Mitchell W Krucoff; Susheel Kodali; Michael J Mack; Roxana Mehran; Josep Rodés-Cabau; Pascal Vranckx; John G Webb; Stephan Windecker; Patrick W Serruys; Martin B Leon
Journal:  Eur J Cardiothorac Surg       Date:  2012-10-01       Impact factor: 4.191

8.  An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies.

Authors:  Peter C Austin
Journal:  Multivariate Behav Res       Date:  2011-06-08       Impact factor: 5.923

  8 in total

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