Fortmeier, Vera; Lachmann, Mark; Stolz, Lukas; von Stein, Jennifer; Unterhuber, Matthias; Kassar, Mohammad; Gerçek, Muhammed; Schöber, Anne R; Stocker, Thomas J; Omran, Hazem; Körber, Maria I; Hesse, Amelie; Harmsen, Gerhard; Friedrichs, Kai Peter; Yuasa, Shinsuke; Rudolph, Tanja K; Joner, Michael; Pfister, Roman; Baldus, Stephan; Laugwitz, Karl-Ludwig; ... (2024). "Artificial Intelligence-Enabled Assessment of Right Ventricular to Pulmonary Artery Coupling in Patients Undergoing Transcatheter Tricuspid Valve Intervention". European heart journal - cardiovascular imaging, 25(4), pp. 558-572. Oxford University Press 10.1093/ehjci/jead324
Full text not available from this repository.BACKGROUND
Right ventricular to pulmonary artery (RV-PA) coupling has been established as a prognostic marker in patients with severe tricuspid regurgitation (TR) undergoing transcatheter tricuspid valve interventions (TTVI). RV-PA coupling assesses right ventricular systolic function related to pulmonary artery pressure levels, which are ideally measured by right heart catheterization. This study aims to improve the RV-PA coupling concept by relating tricuspid annular plane systolic excursion (TAPSE) to mean pulmonary artery pressure (mPAP) levels. Moreover, instead of right heart catheterization, this study sought to employ an extreme gradient boosting (XGB) algorithm to predict mPAP levels based on standard echocardiographic parameters.
METHODS AND RESULTS
This multicenter study included 737 patients undergoing TTVI for severe TR; among them, 55 patients from one institution served for external validation. Complete echocardiography and right heart catheterization data were available from all patients. The XGB algorithm trained on 10 echocardiographic parameters could reliably predict mPAP levels as evaluated on right heart catheterization data from external validation (Pearson correlation coefficient R: 0.68; p-value: 1.3x10-8). Moreover, predicted mPAP (mPAPpredicted) levels were superior to echocardiographic systolic pulmonary artery pressure (sPAPechocardiography) levels in predicting 2-year mortality after TTVI (area under the curve [AUC]: 0.607 vs. 0.520; p-value: 1.9x10-6). Furthermore, TAPSE/mPAPpredicted was superior to TAPSE/sPAPechocardiography in predicting 2-year mortality after TTVI (AUC: 0.633 vs. 0.586; p-value: 0.008). Finally, patients with preserved RV-PA coupling (defined as TAPSE/mPAPpredicted > 0.617 mm/mmHg) showed significantly higher 2-year survival rates after TTVI than patients with reduced RV-PA coupling (81.5% vs. 58.8%, p-value: < 0.001). Moreover, independent association between TAPSE/mPAPpredicted levels and 2-year mortality after TTVI was confirmed by multivariate regression analysis (p-value: 6.3x10-4).
CONCLUSIONS
Artificial intelligence-enabled RV-PA coupling assessment can refine risk stratification prior to TTVI without necessitating invasive right heart catheterization. A comparison with conservatively treated patients is mandatory to quantify the benefit of TTVI in accordance with RV-PA coupling.
Item Type: |
Journal Article (Original Article) |
|---|---|
Division/Institute: |
04 Faculty of Medicine > Department of Cardiovascular Disorders (DHGE) > Clinic of Cardiology |
UniBE Contributor: |
Kassar, Mohammad, Windecker, Stephan, Praz, Fabien Daniel |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
2047-2412 |
Publisher: |
Oxford University Press |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
24 Nov 2023 13:01 |
Last Modified: |
28 Mar 2024 00:14 |
Publisher DOI: |
10.1093/ehjci/jead324 |
PubMed ID: |
37996066 |
Uncontrolled Keywords: |
Tricuspid regurgitation artificial intelligence right ventricular to pulmonary artery coupling transcatheter tricuspid valve intervention |
URI: |
https://boris.unibe.ch/id/eprint/189341 |
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