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| Name | Class |
|---|---|
| Ludwig-Maximilians - University of Munich | OTHER |
| University Hospital Schleswig-Holstein | OTHER |
| University of Cologne | OTHER |
| Heart Center Leipzig - University Hospital |
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The aim of this study is to enhance the predictability of therapeutic success in transcatheter tricuspid valve intervention (TTVI) for patients with severe tricuspid regurgitation (TR). This will be achieved through automated analyses of pre-interventional computed tomography (CT) scans.
Severe tricuspid regurgitation is associated with poor patient outcomes. In advanced stages, pharmacological therapy becomes ineffective, and surgical intervention carries a high mortality risk. Given this clinical challenge, catheter-based treatment of the tricuspid valve has become a focal point of research.
One well-established treatment strategy is percutaneous tricuspid valve intervention, which aims to reduce regurgitation either through annuloplasty, leaflet-based edge-to-edge repair or valve replacement. This approach has been shown to significantly decrease the severity of regurgitation, leading to a dramatic reduction in symptom burden and a marked improvement in quality of life.
However, predicting which patients will benefit most from TTVI and determining the optimal technique for each individual remain largely unresolved challenges.
Artificial intelligence (AI)-powered software, such as heart.ai by LARALAB (Munich), enables automated measurement of anatomical structures captured via CT imaging. This technology already allows for rapid and precise assessment of cardiac chambers and the tricuspid annulus throughout the entire cardiac cycle, facilitating a comprehensive three-dimensional evaluation of right heart anatomy.
To refine patient selection and optimize procedural strategies for TR treatment, the researcher work a multi-center collaboration to analyze treatment outcomes and patient response to specific therapeutic approaches.
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| Measure | Description | Time Frame |
|---|---|---|
| Mortality | Detection of mortality after transcatheter tricuspid intervention | 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Residual Tricuspid Regurgitation | Grade of residual tricuspid regurgitation after transcatheter tricuspid valve intervention | At discharge, 30 days and 1 year |
| rehospitalization rate | Detection of rehospitalization rate after transcatheter tricuspid intervention |
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Inclusion Criteria:
Exclusion Criteria:
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The study includes patients with >moderate tricuspid regurgitation who underwent cardiac computed tomography and transcatheter tricupid valve intervention.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Johannes Kirchner, Dr. med. | Contact | 0405731971258 | jkirchner@hdz-nrw.de |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Herz- und Diabeteszentrum | Recruiting | Bad Oeynhausen | North Rhine-Westphalia | 32545 | Germany |
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| ID | Term |
|---|---|
| D014262 | Tricuspid Valve Insufficiency |
| ID | Term |
|---|---|
| D006349 | Heart Valve Diseases |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
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| OTHER |
| Charite University, Berlin, Germany | OTHER |
| University of Bern | OTHER |
| University Medical Center Mainz | OTHER |
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| 1 year |
| reintervention rate | Detection of reintervention rate on the tricuspid valve after transcatheter tricuspid intervention | 1 year |
| NYHA Class | Changes on New York Heart Association functional class after transceather tricuspid valve intervention | 30 days and 1 year |
| Intraprocedural success | All of the following must be present:
| 30 days |