Clinical trial NCT03779490: Transcatheter Repair of Tricuspid Regurgitation With Edwards Cardioband TR System Post Market Study (TriBAND)
Official title: Transcatheter Repair of Tricuspid Regurgitation With Cardioband TR System Post-Market Clinical Follow-Up Study (TriBAND): A European Prospective, Multicenter Post-market Clinical Follow-up Study to Assess Transcatheter Tricuspid Valve Repair With Edwards Cardioband TR System in Patients With Symptomatic Chronic Functional Tricuspid Regurgitation.
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Tricuspid Regurgitation
Tricuspid Insufficiency
Keywords: Edwards Cardioband TR
Annuloplasty
Tricuspid Repair
Tricuspid Valve
Lead sponsor: Edwards Lifesciences
Sponsor class: INDUSTRY
First posted: 2018-12-19
Enrollment: 150
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Symptomatic patients with chronic functional tricuspid regurgitation (FTR)

Brief summary: The purpose of the study is to assess the safety and the effectiveness of the Cardioband Tricuspid Reconstruction System.

Detailed description: The purpose of the study is to assess the safety and the effectiveness of the Cardioband Tricuspid Reconstruction System. This is a multi-center, prospective, single-arm Post-Market Clinical Follow up Study.

Eligibility criteria: * Inclusion Criteria:

  * Eighteen (18) years of age or older
  * Moderate or greater functional Tricuspid Regurgitation (TR)
  * Patient is eligible to receive the Edwards Cardioband TR System per the current approved indications for use.
* Exclusion Criteria:

  * Patients deemed anatomically unsuitable for the device by echocardiography
  * Patients in whom transesophageal echocardiography (TEE) is contraindicated
  * Previous tricuspid valve repair or replacement
  * Severe aortic, mitral and / or pulmonic valve stenosis
  * Severe aortic, mitral and / or pulmonic valve regurgitation
  * Renal Insufficiency requiring dialysis or severe kidney renal disease
  * Life expectancy of less than twelve months
  * Patient is pregnant or lactating

Primary outcomes:
measure: Procedure Success
timeFrame: Hospital discharge, 2-7 days post-procedure
Secondary outcomes:
measure: Major Adverse Event Rate
timeFrame: 30 days, 6 months, 1 year, 2 years, 3 years, 4 years, 5 years
measure: Procedure Success
timeFrame: 30 days, 6 months, 1 year, 2 years, 3 years, 4 years, 5 years
measure: Change in Quality of Life - KCCQ
timeFrame: 30 days, 6 months, 1 year, 2 years, 3 years, 4 years, 5 years
measure: Change in Quality of Life - EQ-5D-5L
timeFrame: 30 days, 6 months, 1 year, 2 years, 3 years, 4 years, 5 years
Other outcomes:
Locations:
city: Ulm
country: Germany
facility: Ulm University
state: Bayern
city: Bad Oeynhausen
country: Germany
facility: Universitätsklinik der Ruhr-Universität Bochum
state: North Rhine Westphalia
city: Cologne
country: Germany
facility: Herzzentrum der UniKlinik Köln
state: NRW
city: Berlin
country: Germany
facility: Charité - Universitätsmedizin Campus Mitte
city: Berlin
country: Germany
facility: Berlin Charité-Benjamin Franklin
city: Bonn
country: Germany
facility: Universitätsklinikum Bonn
city: Dresden
country: Germany
facility: Herzzentrum Universitätsklinik Dresden
city: Erlangen
country: Germany
facility: University Hospital Erlangen
city: Göttingen
country: Germany
facility: Universitätsmedizin Göttingen, Herzzentrum Göttingen
city: Hamburg
country: Germany
facility: Asklepios Klinik St. Georg
city: Hamburg
country: Germany
facility: UKE Hamburg
city: Hamburg
country: Germany
facility: Katholisches Marienkrankenhaus
city: Madrid
country: Spain
facility: Hospital Universitario Ramón y Cahal
city: Bern
country: Switzerland
facility: Universitätsspital Bern (Inselspital)
Study officials:
affiliation: Universitätsklinikum Bonn, Germany
name: Georg Nickenig, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Vernikouskaya I, Bertsche D, Rottbauer W, Rasche V. Deep learning-based framework for motion-compensated image fusion in catheterization procedures. Comput Med Imaging Graph. 2022 Jun;98:102069. doi: 10.1016/j.compmedimag.2022.102069. Epub 2022 May 13.