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Afterload Mismatch Predictive modLE for Transcatheter Edge-to-Edge Repair (AMPLE-TEER)

NCT07019935 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2025-06-13

No results posted yet for this study

Summary

Mitral regurgitation (MR) is one of the most common valvular heart diseases in China, causing heart failure. Patients with moderate to severe MR have a very poor clinical prognosis if no intervention is performed. When symptoms are still poorly controlled after guideline-directed medical therapy (GDMT) or when surgical intervention is not suitable, transcatheter mitral valve edge-to-edge repair (TEER) can improve the patient's quality of life and reduce the hospitalization rate and mortality rate. However, some patients develop into afterload mismatch (AM) after TEER, persistent adverse ventricular remodeling, and a high mortality rate, which limits the surgical benefits of TEER surgery in these MR patients. Therefore, how to scientifically predict AM and intervene as early as possible has become a research hotspot for optimizing the postoperative management of TEER patients. Afterload Mismatch Predictive modLE for Transcatheter Edge-to-Edge Repair (AMPLE-TEER) study is a prospective cohort study including adult patients undergoing TEER during hospitalization. We aim to evaluate whether the patients develop into AM after TEER, evaluate the prognostic risk factors of AM and construct a prognostic clinical model to guide clinical decision-making.

Conditions

  • Mitral Insufficiency

Sponsors & Collaborators

  • Sun Yat-sen University

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-10-01
Primary Completion
2030-10-01
Completion
2030-10-01

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07019935 on ClinicalTrials.gov