{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T03:06:52Z","timestamp":1793243212264,"version":"4.5.0"},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2023,2,3]],"date-time":"2023-02-03T00:00:00Z","timestamp":1675382400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"name":"Else Kr\u00f6ner-Fresenius Foundation"},{"DOI":"10.13039\/501100005971","name":"Deutsche Herzstiftung","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100005971","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100005713","name":"Technical University of Munich","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100005713","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,4,24]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Patients with mitral regurgitation (MR) present with considerable heterogeneity in cardiac damage depending on underlying aetiology, disease progression, and comorbidities. This study aims to capture their cardiopulmonary complexity by employing a machine-learning (ML)-based phenotyping approach.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>Data were obtained from 1426 patients undergoing mitral valve transcatheter edge-to-edge repair (MV TEER) for MR. The ML model was developed using 609 patients (derivation cohort) and validated on 817 patients from two external institutions. Phenotyping was based on echocardiographic data, and ML-derived phenotypes were correlated with 5-year outcomes. Unsupervised agglomerative clustering revealed four phenotypes among the derivation cohort: Cluster 1 showed preserved left ventricular ejection fraction (LVEF; 56.5 \u00b1 7.79%) and regular left ventricular end-systolic diameter (LVESD; 35.2 \u00b1 7.52 mm); 5-year survival in Cluster 1, hereinafter serving as a reference, was 60.9%. Cluster 2 presented with preserved LVEF (55.7 \u00b1 7.82%) but showed the largest mitral valve effective regurgitant orifice area (0.623 \u00b1 0.360 cm2) and highest systolic pulmonary artery pressures (68.4 \u00b1 16.2 mmHg); 5-year survival ranged at 43.7% (P-value: 0.032). Cluster 3 was characterized by impaired LVEF (31.0 \u00b1 10.4%) and enlarged LVESD (53.2 \u00b1 10.9 mm); 5-year survival was reduced to 38.3% (P-value: &amp;lt;0.001). The poorest 5-year survival (23.8%; P-value: &amp;lt;0.001) was observed in Cluster 4 with biatrial dilatation (left atrial volume: 312 \u00b1 113 mL; right atrial area: 46.0 \u00b1 8.83 cm2) although LVEF was only slightly reduced (51.5 \u00b1 11.0%). Importantly, the prognostic significance of ML-derived phenotypes was externally confirmed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>ML-enabled phenotyping captures the complexity of extra-mitral valve cardiac damage, which does not necessarily occur in a sequential fashion. This novel phenotyping approach can refine risk stratification in patients undergoing MV TEER in the future.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ehjci\/jead013","type":"journal-article","created":{"date-parts":[[2023,1,18]],"date-time":"2023-01-18T15:58:20Z","timestamp":1674057500000},"page":"574-587","source":"Crossref","is-referenced-by-count":25,"title":["Machine learning identifies pathophysiologically and prognostically informative phenotypes among patients with mitral regurgitation undergoing transcatheter edge-to-edge repair"],"prefix":"10.1093","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9077-1447","authenticated-orcid":false,"given":"Teresa","family":"Trenkwalder","sequence":"first","affiliation":[{"name":"Department of Cardiology, German Heart Center Munich, Technical University of Munich , Lazarettstrasse 36, 80636 Munich , Germany"},{"name":"DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance , 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