Literature DB >> 34527520

A single-center analysis of outcomes, risk factors, and new valves in Asian patients treated with early transcatheter aortic valve implantation.

Ying Liang1, Wei Wang2, Xu Wang2, Feilong Hei1, Yulong Guan1.   

Abstract

BACKGROUND: Transcatheter aortic valve implantation (TAVI) continues to expand as an optimal treatment in Western countries; however, Asian countries have been slower to adopt this procedure. This research aimed to explore the outcomes and status of early TAVI performed at a single center in Asia, and provide comparative outcomes of the newly designed Chinese valves.
METHODS: We enrolled 175 consecutive patients who successfully underwent TAVI from September 2012 to January 2018 at Fuwai Hospital (Beijing, China). After a preliminary assessment of age, we included 109 older patients (≥69 years) who underwent surgical aortic valve replacement (SAVR) during the same period. The primary endpoint was all-cause mortality. The inverse probability of treatment weighting (IPTW) was used to reduce potential bias. Cox regression was used to identify the risk factors of a poor prognosis.
RESULTS: The TAVI cohort had higher rates of all-cause mortality [11.4% vs. 2.4%, hazard ratio (HR): 4.79, 95% confidence interval (CI): 1.47 to 15.57, IPTW-adjusted P=0.009] and permanent pacemaker implantation (PPI; 14.6% vs. 1.6%, HR: 9.98, 95% CI: 2.71 to 36.67, IPTW-adjusted P<0.001) at 3 years than the SAVR cohort. In the multivariable Cox regression analysis based on the entire sample, liver disease was associated with all-cause mortality (HR: 5.080, 95% CI: 1.067 to 24.174, P=0.041). A smoking history was associated with an increased risk of postoperative heart failure (HF) (HR: 4.902, 95% CI: 1.265 to 18.999, P=0.022). Additionally, age (HR: 1.141, 95% CI: 1.010 to 1.288, P=0.034) and diabetes (HR: 7.301, 95% CI: 2.414 to 22.079, P<0.001) were identified as predictors of postoperative stroke. In the new valve subgroups, the 1-year composite endpoints were 38.2% (Venus A), 35.3% (TaurusOne), 34% (J-Valve), and 28% (VitaFlow) (P=0.857).
CONCLUSIONS: Not all TAVI procedures had satisfactory outcomes compared with SAVR when initiated. At first, our center faced some challenges in delivering TAVI, and this is probably one of the reasons why the use of TAVI has developed slowly in Asia. Further investigations are needed to explore the underlying factors precluding the rapid expansion of TAVI in Asia. 2021 Cardiovascular Diagnosis and Therapy. All rights reserved.

Entities:  

Keywords:  Transcatheter aortic valve implantation (TAVI); heart failure (HF); inverse probability of treatment weighting (IPTW); paravalvular leakage; stroke

Year:  2021        PMID: 34527520      PMCID: PMC8410484          DOI: 10.21037/cdt-20-928

Source DB:  PubMed          Journal:  Cardiovasc Diagn Ther        ISSN: 2223-3652


  33 in total

1.  Transcatheter Aortic Valve Implantation (TAVI) for Native Aortic Valve Regurgitation - A Systematic Review.

Authors:  Altayyeb Yousef; Zachary MacDonald; Trevor Simard; Juan J Russo; Joshua Feder; Michael V Froeschl; Alexander Dick; Christopher Glover; Ian G Burwash; Azeem Latib; Josep Rodés-Cabau; Marino Labinaz; Benjamin Hibbert
Journal:  Circ J       Date:  2017-12-28       Impact factor: 2.993

2.  Impact of Frailty Markers for Unplanned Hospital Readmission Following Transcatheter Aortic Valve Implantation.

Authors:  Mike Saji; Ryosuke Higuchi; Tetsuya Tobaru; Nobuo Iguchi; Shuichiro Takanashi; Morimasa Takayama; Mitsuaki Isobe
Journal:  Circ J       Date:  2017-12-29       Impact factor: 2.993

3.  Transapical transcatheter aortic valve implantation using the J-Valve system: A 1-year follow-up study.

Authors:  Xiang Luo; Xu Wang; Xuan Li; Xin Wang; Fei Xu; Mingzheng Liu; Bing Yu; Fei Li; Minghui Tong; Wei Wang
Journal:  J Thorac Cardiovasc Surg       Date:  2017-03-23       Impact factor: 5.209

4.  Smoking and heart failure: A call for action.

Authors:  Eva Prescott
Journal:  Eur J Prev Cardiol       Date:  2018-11-26       Impact factor: 7.804

5.  Appropriateness of Transcatheter Aortic Valve Replacement: Insight From the OCEAN-TAVI Registry.

Authors:  Taku Inohara; Sreekanth Vemulapalli; Shun Kohsaka; Fumiaki Yashima; Yusuke Watanabe; Shinichi Shirai; Norio Tada; Motoharu Araki; Toru Naganuma; Futoshi Yamanaka; Hiroshi Ueno; Minoru Tabata; Kazuki Mizutani; Akihiro Higashimori; Kensuke Takagi; Masanori Yamamoto; Hideyuki Shimizu; Keiichi Fukuda; Kentaro Hayashida
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2020-03-26

6.  Oral Anticoagulant Type and Outcomes After Transcatheter Aortic Valve Replacement.

Authors:  David Jochheim; Marco Barbanti; Giuliana Capretti; Giulio G Stefanini; Alexander Hapfelmeier; Magda Zadrozny; Moritz Baquet; Julius Fischer; Hans Theiss; Denise Todaro; Alaide Chieffo; Patrizia Presbitero; Antonio Colombo; Steffen Massberg; Corrado Tamburino; Julinda Mehilli
Journal:  JACC Cardiovasc Interv       Date:  2019-06-12       Impact factor: 11.195

7.  VitaFlow™ transcatheter valve system in the treatment of severe aortic stenosis: One-year results of a multicenter study.

Authors:  Daxin Zhou; Wenzhi Pan; Jianan Wang; Yongjian Wu; Mao Chen; Thomas Modine; Darren Mylotte; Niccolo Piazza; Junbo Ge
Journal:  Catheter Cardiovasc Interv       Date:  2019-04-24       Impact factor: 2.692

8.  Clinical Outcomes Following Transcatheter Aortic Valve Replacement in Asian Population.

Authors:  Sung-Han Yoon; Jung-Min Ahn; Kentaro Hayashida; Yusuke Watanabe; Shinichi Shirai; Hsien-Li Kao; Wei-Hsian Yin; Michael Kang-Yin Lee; Edgar Tay; Motoharu Araki; Futoshi Yamanaka; Takahide Arai; Mao-Shin Lin; Jun-Bean Park; Duk-Woo Park; Soo-Jin Kang; Seung-Whan Lee; Young-Hak Kim; Cheol Whan Lee; Seong-Wook Park; Toshiya Muramatsu; Michiya Hanyu; Ken Kozuma; Hyo-Soo Kim; Shigeru Saito; Seung-Jung Park
Journal:  JACC Cardiovasc Interv       Date:  2016-05-09       Impact factor: 11.195

9.  2-Year Outcomes in Patients Undergoing Surgical or Self-Expanding Transcatheter Aortic Valve Replacement.

Authors:  Michael J Reardon; David H Adams; Neal S Kleiman; Steven J Yakubov; Joseph S Coselli; G Michael Deeb; Thomas G Gleason; Joon Sup Lee; James B Hermiller; Stan Chetcuti; John Heiser; William Merhi; George L Zorn; Peter Tadros; Newell Robinson; George Petrossian; G Chad Hughes; J Kevin Harrison; Brijeshwar Maini; Mubashir Mumtaz; John V Conte; Jon R Resar; Vicken Aharonian; Thomas Pfeffer; Jae K Oh; Hongyan Qiao; Jeffrey J Popma
Journal:  J Am Coll Cardiol       Date:  2015-06-05       Impact factor: 24.094

10.  Improving propensity score weighting using machine learning.

Authors:  Brian K Lee; Justin Lessler; Elizabeth A Stuart
Journal:  Stat Med       Date:  2010-02-10       Impact factor: 2.373

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.