Literature DB >> 26425793

Learning curves for transfemoral transcatheter aortic valve replacement in the PARTNER-I trial: Success and safety.

Sa'ar Minha1, Ron Waksman1, Lowell P Satler1, Rebecca Torguson1, Oluseun Alli2, Charanjit S Rihal3, Michael Mack4, Lars G Svensson5,6, Jeevanantham Rajeswaran5,6, Eugene H Blackstone5,6, E Murat Tuzcu6, Vinod H Thourani7, Raj Makkar8, John Ehrlinger6, Ashley M Lowry6, Rakesh M Suri6, Kevin L Greason3, Martin B Leon5,9, David R Holmes3, Augusto D Pichard1.   

Abstract

OBJECTIVES: To identify number of cases needed to maximize device success and minimize adverse events after transfemoral transcatheter aortic valve replacement (TF-TAVR), and determine if adverse events were linked to the technical performance learning curve.
BACKGROUND: TF-TAVR is a complex procedure with an incompletely characterized learning curve for clinical outcomes.
METHODS: From 4/2007-2/2012, 1521 patients underwent TF-TAVR in the PARTNER-I trial. Outcomes learning curves were defined as number of cases needed to reach a plateau for device success, adverse events, and post-procedure length of stay. Institutional variation was accounted for by mixed-model non-linear techniques, which were also used to identify contribution of the procedure time learning curve to 30-day major adverse events and length of stay.
RESULTS: Eighty percent device success was achieved after 22 cases; major vascular complications fell below 5% after 70 cases and major bleeding below 10% after 25 cases. It took an average of 28 cases to achieve a consistent low risk of 30-day major adverse events, but institutions entering in the middle of the trial achieved it after about 26. The most significant correlate of 30-day major adverse events and post-procedure length of stay was procedure time (P < 0.0001). However, this association was related to patient and unmeasured variables, not the procedure time learning curve (P = 0.6).
CONCLUSIONS: By end of trial, a consistent low risk of adverse events was achieved after ∼26 cases. However, these improved results were due to change in patient risk profile; outcomes were not linked to the technical performance learning curve.
© 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Entities:  

Keywords:  adverse events; device success; outcomes learning curves; transcatheter aortic valve replacement; transfemoral

Mesh:

Year:  2015        PMID: 26425793     DOI: 10.1002/ccd.26121

Source DB:  PubMed          Journal:  Catheter Cardiovasc Interv        ISSN: 1522-1946            Impact factor:   2.692


  13 in total

1.  Early cerebrovascular events after transcatheter aortic valve replacement: patient- and procedure-specific predictors.

Authors:  Dale Murdoch; Jonathon P Fanning
Journal:  J Thorac Dis       Date:  2017-03       Impact factor: 2.895

Review 2.  Leadless pacing.

Authors:  J Sperzel; C Hamm; A Hain
Journal:  Herz       Date:  2018-11       Impact factor: 1.443

3.  A proctoring system to manage the learning curve associated with the introduction of transcatheter aortic valve implantation in Japan.

Authors:  Masahiro Yamawaki; Kiyotaka Iwasaki; Motoharu Araki; Tsutomu Ito; Yoshiaki Ito; Norio Tada; Kensuke Takagi; Futoshi Yamanaka; Yusuke Watanabe; Masanori Yamamoto; Shinichi Shirai; Kentaro Hayashida
Journal:  Heart Vessels       Date:  2017-12-11       Impact factor: 2.037

4.  Association Between Hospital Volume and 30-Day Readmissions Following Transcatheter Aortic Valve Replacement.

Authors:  Sahil Khera; Dhaval Kolte; Tanush Gupta; Andrew Goldsweig; Poonam Velagapudi; Ankur Kalra; Gilbert H L Tang; Wilbert S Aronow; Gregg C Fonarow; Deepak L Bhatt; Herbert D Aronow; Neal S Kleiman; Michael Reardon; Paul C Gordon; Barry Sharaf; J Dawn Abbott
Journal:  JAMA Cardiol       Date:  2017-07-01       Impact factor: 14.676

5.  Learning Alternative Access Approaches for Transcatheter Aortic Valve Replacement: Implications for New Transcatheter Aortic Valve Replacement Centers.

Authors:  Matthew C Henn; Thomas Percival; Alan Zajarias; Spencer J Melby; Brian R Lindman; Nishath Quader; Ralph J Damiano; Marc R Moon; John M Lasala; Ravinder S Rao; Jennifer Bell; Marci S Damiano; Hersh S Maniar
Journal:  Ann Thorac Surg       Date:  2016-10-17       Impact factor: 4.330

6.  Learning curves for transapical transcatheter aortic valve replacement in the PARTNER-I trial: Technical performance, success, and safety.

Authors:  Rakesh M Suri; Sa'ar Minha; Oluseun Alli; Ron Waksman; Charanjit S Rihal; Lowell P Satler; Kevin L Greason; Rebecca Torguson; Augusto D Pichard; Michael Mack; Lars G Svensson; Jeevanantham Rajeswaran; Ashley M Lowry; John Ehrlinger; Stephanie L Mick; E Murat Tuzcu; Vinod H Thourani; Raj Makkar; David Holmes; Martin B Leon; Eugene H Blackstone
Journal:  J Thorac Cardiovasc Surg       Date:  2016-04-13       Impact factor: 5.209

7.  Volume-outcome relationships for transcatheter aortic valve replacement-risk-adjusted and volume stratified analysis of TAVR outcomes.

Authors:  Divya Ratan Verma; Yash Pershad; Mohamad Lazkani; Kenith Fang; Michael Morris; Ashish Pershad
Journal:  Indian Heart J       Date:  2017-05-09

Review 8.  Patient-specific computer modelling - its role in the planning of transcatheter aortic valve implantation.

Authors:  N El Faquir; B Ren; N M Van Mieghem; J Bosmans; P P de Jaegere
Journal:  Neth Heart J       Date:  2017-02       Impact factor: 2.380

9.  Avoiding the Learning Curve for Transcatheter Aortic Valve Replacement.

Authors:  Sergey Gurevich; Ranjit John; Rosemary F Kelly; Ganesh Raveendran; Gregory Helmer; Demetris Yannopoulos; Timinder Biring; Brett Oestreich; Santiago Garcia
Journal:  Cardiol Res Pract       Date:  2017-01-26       Impact factor: 1.866

10.  The learning curve associated with the implantation of the Nanostim leadless pacemaker.

Authors:  Fleur V Y Tjong; Niek E G Beurskens; Petr Neuzil; Pascal Defaye; Peter-Paul Delnoy; John Ip; Juan Jose Garcia Guerrero; Mayer Rashtian; Rajesh Banker; Vivek Reddy; Derek Exner; Johannes Sperzel; Reinoud E Knops
Journal:  J Interv Card Electrophysiol       Date:  2018-08-13       Impact factor: 1.900

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