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American Heart Association

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Final ID: MDP662

Deep Learning-Enabled Assessment of Right Ventricular Function Using 2D Echocardiograms Improves 1-Year Mortality Prediction in Patients with Severe Mitral Regurgitation Undergoing Transcatheter Edge-to-Edge Repair

Abstract Body (Do not enter title and authors here): Background:
Right ventricular (RV) function has a well-established prognostic role in patients with severe mitral regurgitation (MR) undergoing transcatheter edge-to-edge repair (TEER) and is typically assessed using echocardiography-measured tricuspid annular plane systolic excursion (TAPSE). Recently, a deep learning model has been proposed that accurately predicts RV ejection fraction (RVEF) from 2D echocardiographic videos, with similar diagnostic accuracy as 3D imaging.

Aims:
This study aimed to evaluate the prognostic utility of the deep learning-predicted RVEF values in patients with severe MR undergoing TEER.

Methods:
This multicenter registry study analyzed the associations between the predicted RVEF values and 1-year mortality in patients with severe MR undergoing TEER. To predict RVEF, 2D apical four-chamber view videos from preprocedural transthoracic echocardiographic studies were exported and processed by a rigorously validated deep learning model.

Results:
From 1,366 patients undergoing TEER between 2017 and 2023, good-quality 2D apical four-chamber view videos could be retrieved for 1,154 patients (84.5%). Survival at one year after TEER was 84.7%. The predicted RVEF values ranged from 26.6% to 64.0% and correlated only modestly with TAPSE (Pearson correlation coefficient R: 0.33; p-value: <0.001). Importantly, predicted RVEF levels were superior to TAPSE levels in predicting 1-year mortality after TEER (area under the curve: 0.687 vs. 0.625; p-value: 0.029). Furthermore, Kaplan-Meier survival analysis revealed that patients with preserved RV function (defined as a predicted RVEF of ≥45%) had significantly better 1-year survival rates than patients with reduced RV function (92.1% [95% CI: 89.5-94.7%] vs. 80.3% [95% CI: 77.4-83.3%], respectively, hazard ratio for 1-year mortality: 2.67, p-value: <0.001).

Conclusion:
Deep learning-enabled assessment of RV function using standard 2D echocardiographic videos can refine the prognostication of patients with severe MR undergoing TEER. Thus, it can be used to screen for patients with RV dysfunction who might benefit from intensified follow-up care.
  • Lachmann, Mark  ( Klinikum rechts der Isar, Technical University of Munich , Munich , Germany )
  • Hausleiter, Jorg  ( Medizinische Klinik und Poliklinik I, Klinikum der Universität München, Ludwig Maximilians University of Munich , Munich , Germany )
  • Rudolph, Volker  ( Department of General and Interventional Cardiology, Heart and Diabetes Center Northrhine-Westfalia, Ruhr University Bochum , Bad Oeynhausen , Germany )
  • Trenkwalder, Teresa  ( Department of Cardiology, German Heart Center Munich, Technical University of Munich , Munich , Germany )
  • Fortmeier, Vera  ( Department of General and Interventional Cardiology, Heart and Diabetes Center Northrhine-Westfalia, Ruhr University Bochum , Bad Oeynhausen , Germany )
  • Stolz, Lukas  ( Medizinische Klinik und Poliklinik I, Klinikum der Universität München, Ludwig Maximilians University of Munich , Munich , Germany )
  • Tokodi, Marton  ( Heart and Vascular Center, Semmelweis University , Budapest , Hungary )
  • Yuasa, Shinsuke  ( Department of Cardiology, Keio University School of Medicine , Tokyo , Japan )
  • Mayr, N. Patrick  ( Institute of Anesthesiology, German Heart Center Munich, Technical University of Munich , Munich , Germany )
  • Joner, Michael  ( Department of Cardiology, German Heart Center Munich, Technical University of Munich , Munich , Germany )
  • Xhepa, Erion  ( Department of Cardiology, German Heart Center Munich, Technical University of Munich , Munich , Germany )
  • Laugwitz, Karl-ludwig  ( Klinikum rechts der Isar, Technical University of Munich , Munich , Germany )
  • Author Disclosures:
    Mark Lachmann: DO NOT have relevant financial relationships | jorg hausleiter: No Answer | Volker Rudolph: No Answer | Teresa Trenkwalder: No Answer | Vera Fortmeier: No Answer | Lukas Stolz: No Answer | Marton Tokodi: DO have relevant financial relationships ; Consultant:CardioSight:Past (completed) | Shinsuke Yuasa: No Answer | N. Patrick Mayr: No Answer | Michael Joner: No Answer | Erion Xhepa: No Answer | Karl-Ludwig Laugwitz: No Answer
Meeting Info:

Scientific Sessions 2024

2024

Chicago, Illinois

Session Info:

Deep Dive into Transcatheter Mitral Valve Therapies

Saturday, 11/16/2024 , 12:50PM - 02:15PM

Moderated Digital Poster Session

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