{"doi":"10.1016/j.jacep.2025.06.001","title":"Phenotyping of Mitral Valve Prolapse Without Severe Mitral Regurgitation Using Electrocardiographic and Echocardiographic Data","abstract":"BACKGROUND: Arrhythmic risk stratification in mitral valve prolapse (MVP) without significant mitral regurgitation (MR) remains elusive. Unsupervised machine learning may reveal phenotypic variation among arrhythmic MVP without severe MR. OBJECTIVES: In this study, the authors hypothesized that hierarchical clustering of echocardiographic and 12-lead electrocardiographic (ECG) parameters alone could identify MVP phenotypes without severe MR associated with sustained ventricular arrhythmia and excess mortality. METHODS: The authors identified 343 consecutive MVPs (58 ± 16 years; 51% female) with ≤moderate MR and comprehensive echocardiographic, 12-lead and ambulatory ECG data. They used hierarchical clustering analysis to identify distinctive MVP phenotypes and investigated their association with: 1) arrhythmic events (sudden cardiac arrest, ventricular fibrillation/tachycardia, or frequent ventricular ectopy); and 2) overall mortality (mean follow-up: 5.4 ± 2.7 years). RESULTS: Three clusters were identified: Cluster 1 (83% of MVP cases), Cluster 2 (9%), and Cluster 3 (8%). Despite mostly trace/mild MR, Cluster 3 exhibited more abnormal parameters of left atrial (LA) and left ventricular structure and function compared with Clusters 1 and 2 (all P < 0.001). Top clustering features included ECG intervals, LA systolic strain, and LA function index. Arrhythmic presentations (n = 77) were identified in 19%, 38%, and 43% of Clusters 1, 2, and 3 (P < 0.001), respectively. Compared with Cluster 1, Clusters 2 (HR: 5.01; P < 0.001) and 3 (HR: 5.85; P < 0.001) had significantly increased mortality risk. CONCLUSIONS: Hierarchical clustering based on standard ECG and echocardiographic data alone identifies 3 MVP clusters with distinct arrhythmic profiles and excess mortality, highlighting LA function as a novel risk parameter in MVP without significant MR.","journal":"JACC. Clinical electrophysiology","year":2025,"id":523894,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9562,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1105423,"name":"Minhaj Ansari","orcid":null,"position":1,"is_corresponding":false},{"id":63396,"name":"JOSHUA BARRIOS","orcid":"0000-0003-1618-6244","position":2,"is_corresponding":false},{"id":1228680,"name":"Luca Cristin","orcid":"0009-0003-2932-8659","position":3,"is_corresponding":false},{"id":1229133,"name":"Rohit Jhawar","orcid":null,"position":4,"is_corresponding":false},{"id":1397360,"name":"Amy H. Rich","orcid":null,"position":5,"is_corresponding":false},{"id":1053489,"name":"Dwight Bibby","orcid":null,"position":6,"is_corresponding":false},{"id":279879,"name":"Qizhi Fang","orcid":null,"position":7,"is_corresponding":false},{"id":1064163,"name":"Farzin Arya","orcid":null,"position":8,"is_corresponding":false},{"id":63402,"name":"GEOFFREY H. TISON","orcid":"0000-0002-0310-3326","position":9,"is_corresponding":false},{"id":98913,"name":"Francesca N. Delling","orcid":"0000-0002-5224-4096","position":10,"is_corresponding":false},{"id":641058,"name":"Lionel Tastet","orcid":"0000-0002-6374-5398","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-19T02:50:07.396155Z","pmid":"40673846","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}