Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacement
Objective A novel artificial intelligence-based phenotyping approach to stratify patients with severe aortic stenosis (AS) prior to transcatheter aortic valve replacement (TAVR) has been proposed, based on echocardiographic and haemodynamic data. This study aimed to analyse the recovery of extra-aor...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2022-08-01
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| Series: | Open Heart |
| Online Access: | https://openheart.bmj.com/content/9/2/e002068.full |
| _version_ | 1797781010329370624 |
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| author | Tibor Schuster Adnan Kastrati Shinsuke Yuasa Erion Xhepa Christian Kupatt Michael Joner Karl-Ludwig Laugwitz Heribert Schunkert Mark Lachmann Elena Rippen Moritz von Scheidt Teresa Trenkwalder Costanza Pellegrini Tobias Rheude Amelie Hesse Anja Stundl Gerhard Harmsen |
| author_facet | Tibor Schuster Adnan Kastrati Shinsuke Yuasa Erion Xhepa Christian Kupatt Michael Joner Karl-Ludwig Laugwitz Heribert Schunkert Mark Lachmann Elena Rippen Moritz von Scheidt Teresa Trenkwalder Costanza Pellegrini Tobias Rheude Amelie Hesse Anja Stundl Gerhard Harmsen |
| author_sort | Tibor Schuster |
| collection | DOAJ |
| description | Objective A novel artificial intelligence-based phenotyping approach to stratify patients with severe aortic stenosis (AS) prior to transcatheter aortic valve replacement (TAVR) has been proposed, based on echocardiographic and haemodynamic data. This study aimed to analyse the recovery of extra-aortic valve cardiac damage in accordance with this novel stratification system following TAVR.Methods The proposed phenotyping approach was previously established employing data from 366 patients with severe AS from a bicentric registry. For this consecutive study, echocardiographic follow-up data, obtained on day 147±75.1 after TAVR, were available from 247 patients (67.5%).Results Correction of severe AS by TAVR significantly reduced the proportion of patients suffering from concurrent severe mitral regurgitation (from 9.29% to 3.64%, p value: 0.0015). Moreover, pulmonary artery pressures were ameliorated (estimated systolic pulmonary artery pressure: from 47.2±15.8 to 43.3±15.1 mm Hg, p value: 0.0079). However, right heart dysfunction as well as the proportion of patients with severe tricuspid regurgitation remained unchanged. Clusters with persistent right heart dysfunction ultimately displayed 2-year survival rates of 69.2% (95% CI 56.6% to 84.7%) and 74.6% (95% CI 65.9% to 84.4%), which were significantly lower compared with clusters with little or no persistent cardiopulmonary impairment (88.3% (95% CI 83.3% to 93.5%) and 85.5% (95% CI 77.1% to 94.8%)).Conclusions This phenotyping approach preprocedurally identifies patients with severe AS, who will not recover from extra-aortic valve cardiac damage following TAVR and whose survival is therefore significantly reduced. Importantly, not the degree of pulmonary hypertension at initial presentation, but the irreversibility of right heart dysfunction determines prognosis. |
| first_indexed | 2024-03-12T23:51:45Z |
| format | Article |
| id | doaj.art-e7d13f294b5942d49abaacca1883ec72 |
| institution | Directory Open Access Journal |
| issn | 2053-3624 |
| language | English |
| last_indexed | 2024-03-12T23:51:45Z |
| publishDate | 2022-08-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | Open Heart |
| spelling | doaj.art-e7d13f294b5942d49abaacca1883ec722023-07-13T14:30:07ZengBMJ Publishing GroupOpen Heart2053-36242022-08-019210.1136/openhrt-2022-002068Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacementTibor Schuster0Adnan Kastrati1Shinsuke Yuasa2Erion Xhepa3Christian Kupatt4Michael Joner5Karl-Ludwig Laugwitz6Heribert Schunkert7Mark Lachmann8Elena Rippen9Moritz von Scheidt10Teresa Trenkwalder11Costanza Pellegrini12Tobias Rheude13Amelie Hesse14Anja Stundl15Gerhard Harmsen16Department of Family Medicine, McGill University, Montreal, Quebec, CanadaDZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, GermanyDepartment of Cardiology, Keio University School of Medicine, Tokyo, JapanDZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, GermanyFirst Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, GermanyDZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, GermanyFirst Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, GermanyDepartment of Cardiology, Deutsches Herzzentrum München, Technical University of Munich, Munich, GermanyFirst Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, GermanyFirst Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, GermanyDZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, GermanyDZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, GermanyDepartment of Cardiology, Deutsches Herzzentrum München, Technical University of Munich, Munich, GermanyDepartment of Cardiology, Deutsches Herzzentrum München, Technical University of Munich, Munich, GermanyFirst Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, GermanyFirst Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, GermanyDepartment of Physics, University of Johannesburg, Auckland Park, South AfricaObjective A novel artificial intelligence-based phenotyping approach to stratify patients with severe aortic stenosis (AS) prior to transcatheter aortic valve replacement (TAVR) has been proposed, based on echocardiographic and haemodynamic data. This study aimed to analyse the recovery of extra-aortic valve cardiac damage in accordance with this novel stratification system following TAVR.Methods The proposed phenotyping approach was previously established employing data from 366 patients with severe AS from a bicentric registry. For this consecutive study, echocardiographic follow-up data, obtained on day 147±75.1 after TAVR, were available from 247 patients (67.5%).Results Correction of severe AS by TAVR significantly reduced the proportion of patients suffering from concurrent severe mitral regurgitation (from 9.29% to 3.64%, p value: 0.0015). Moreover, pulmonary artery pressures were ameliorated (estimated systolic pulmonary artery pressure: from 47.2±15.8 to 43.3±15.1 mm Hg, p value: 0.0079). However, right heart dysfunction as well as the proportion of patients with severe tricuspid regurgitation remained unchanged. Clusters with persistent right heart dysfunction ultimately displayed 2-year survival rates of 69.2% (95% CI 56.6% to 84.7%) and 74.6% (95% CI 65.9% to 84.4%), which were significantly lower compared with clusters with little or no persistent cardiopulmonary impairment (88.3% (95% CI 83.3% to 93.5%) and 85.5% (95% CI 77.1% to 94.8%)).Conclusions This phenotyping approach preprocedurally identifies patients with severe AS, who will not recover from extra-aortic valve cardiac damage following TAVR and whose survival is therefore significantly reduced. Importantly, not the degree of pulmonary hypertension at initial presentation, but the irreversibility of right heart dysfunction determines prognosis.https://openheart.bmj.com/content/9/2/e002068.full |
| spellingShingle | Tibor Schuster Adnan Kastrati Shinsuke Yuasa Erion Xhepa Christian Kupatt Michael Joner Karl-Ludwig Laugwitz Heribert Schunkert Mark Lachmann Elena Rippen Moritz von Scheidt Teresa Trenkwalder Costanza Pellegrini Tobias Rheude Amelie Hesse Anja Stundl Gerhard Harmsen Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacement Open Heart |
| title | Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacement |
| title_full | Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacement |
| title_fullStr | Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacement |
| title_full_unstemmed | Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacement |
| title_short | Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacement |
| title_sort | artificial intelligence enabled phenotyping of patients with severe aortic stenosis on the recovery of extra aortic valve cardiac damage after transcatheter aortic valve replacement |
| url | https://openheart.bmj.com/content/9/2/e002068.full |
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