{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T23:57:10Z","timestamp":1763596630640,"version":"3.45.0"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Quality of life (QoL) improvement is a primary driver for atrial fibrillation (AF) catheter ablation (CA), yet its determinants remain unclear. We aimed to identify patient phenotypes with distinct post-ablation QoL trajectories, determine their key predictors, and clarify their association with arrhythmia recurrence and reintervention.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>We prospectively followed 213 patients (median age 60 years, 31% female) undergoing AF CA at a tertiary hospital for 2.2 years [interquartile range (IQR): 1.6\u20132.6]. A digital health application collected real-time electronic patient-reported outcomes (PROs), including the AF Effect on QoL (AFEQT) questionnaire. Reference charts were generated from QoL trajectories of recurrence-free patients. Machine learning (ML) identified subgroups with distinct QoL trajectories, and explainable artificial intelligence (AI) highlighted key predictors. Quality of life improved by +26 AFEQT points [95% confidence interval (CI): 18\u201333] within 3 months post-ablation and remained stable thereafter, despite significant heterogeneity in individual responses. Patients with AF recurrence showed significantly lower QoL gains (P = 0.010). Machine learning identified three phenotypes: a younger cluster with the largest QoL improvements, an emotive cluster with higher recurrence rates and minimal QoL benefits despite additional antiarrhythmic reinterventions, and an older cluster with established cardiovascular risk factors. Anxiety, age, and AF duration emerged as key discriminators.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>ML defined three clinically coherent phenotypes, each exhibiting distinct QoL trajectories and ablation outcomes. Explainable AI clarified how individual psychological and biological traits interact to shape these outcomes, highlighting the potential for tailored multidisciplinary care beyond individualized rhythm control strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ehjdh\/ztaf090","type":"journal-article","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:46:11Z","timestamp":1754567171000},"page":"1181-1193","source":"Crossref","is-referenced-by-count":0,"title":["Predicting patient-related outcomes after atrial fibrillation ablation: insights from explainable artificial intelligence and digital health"],"prefix":"10.1093","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8151-4024","authenticated-orcid":false,"given":"Rafael","family":"Silva-Teixeira","sequence":"first","affiliation":[{"name":"Department of Cardiology, Gaia Hospital Center , Rua Concei\u00e7\u00e3o Fernandes, 4434-502 Vila Nova de Gaia ,","place":["Portugal"]},{"name":"Center for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra , Azinhaga de Santa Comba, Celas, 3000-548 Coimbra ,","place":["Portugal"]},{"name":"Clinical Academic Center of Coimbra (CACC) , Praceta Professor Mota Pinto, Celas, 3004-561 Coimbra ,","place":["Portugal"]},{"name":"Faculty of Medicine, Coimbra Institute for Clinical and Biomedical Research (iCBR) Area of Environment Genetics and Oncobiology (CIMAGO), Institute of Biophysics, University of Coimbra , Azinhaga de Santa Comba, Celas 3000-548 ,","place":["Portugal"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9434-7061","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Almeida","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Gaia Hospital Center , Rua Concei\u00e7\u00e3o Fernandes, 4434-502 Vila Nova de Gaia ,","place":["Portugal"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0015-8604","authenticated-orcid":false,"given":"Francisco A","family":"Caramelo","sequence":"additional","affiliation":[{"name":"Center for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra , Azinhaga de Santa Comba, Celas, 3000-548 Coimbra ,","place":["Portugal"]},{"name":"Clinical Academic Center of Coimbra (CACC) , Praceta Professor Mota Pinto, Celas, 3004-561 Coimbra ,","place":["Portugal"]},{"name":"Faculty of Medicine, Coimbra Institute for Clinical and Biomedical Research (iCBR) Area of Environment Genetics and Oncobiology (CIMAGO), Institute of Biophysics, University of Coimbra , Azinhaga de Santa Comba, Celas 3000-548 ,","place":["Portugal"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5790-9483","authenticated-orcid":false,"given":"Paulo","family":"Fonseca","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Gaia Hospital Center , Rua Concei\u00e7\u00e3o Fernandes, 4434-502 Vila Nova de Gaia ,","place":["Portugal"]}]},{"given":"Marco","family":"Oliveira","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Gaia Hospital Center , Rua Concei\u00e7\u00e3o Fernandes, 4434-502 Vila Nova de Gaia ,","place":["Portugal"]}]},{"given":"Helena","family":"Gon\u00e7alves","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Gaia Hospital Center , Rua Concei\u00e7\u00e3o Fernandes, 4434-502 Vila Nova de Gaia ,","place":["Portugal"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9717-6202","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Primo","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Gaia Hospital Center , Rua Concei\u00e7\u00e3o Fernandes, 4434-502 Vila Nova de Gaia ,","place":["Portugal"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2306-8393","authenticated-orcid":false,"given":"Ricardo","family":"Fontes-Carvalho","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Gaia Hospital Center , Rua Concei\u00e7\u00e3o Fernandes, 4434-502 Vila Nova de Gaia ,","place":["Portugal"]},{"name":"Department of Surgery and Physiology, Faculty of Medicine of the University of Porto , Alameda Professor Hern\u00e2ni Monteiro 4200-319 Porto ,","place":["Portugal"]},{"name":"Cardiovascular R&D Centre-UnIC@RISE, Faculty of Medicine of the University of Porto , Alameda Professor Hern\u00e2ni Monteiro, 4200-319 Porto ,","place":["Portugal"]}]}],"member":"286","published-online":{"date-parts":[[2025,8,7]]},"reference":[{"key":"2025111918524703500_ztaf090-B1","doi-asserted-by":"crossref","first-page":"3314","DOI":"10.1093\/eurheartj\/ehae176","article-title":"2024 ESC Guidelines for the management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS)","volume":"45","author":"Van Gelder","year":"2024","journal-title":"Eur Heart 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