{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T15:27:33Z","timestamp":1785338853754,"version":"3.55.0"},"reference-count":41,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"15","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["JAHA"],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:sec sec-type=\"background\" xml:lang=\"en\">\n            <jats:title>Background<\/jats:title>\n            <jats:p xml:lang=\"en\">Cardiac involvement can be an initial manifestation in sarcoidosis. However, little is known about the association between various clinical phenotypes of cardiac sarcoidosis (CS) and outcomes. We aimed to analyze the relation of different clinical manifestations with outcomes of CS and to investigate the relative importance of clinical features influencing overall survival.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Methods and Results<\/jats:title>\n            <jats:p xml:lang=\"en\">\n              A retrospective cohort of 141 patients with CS enrolled at 2 Swedish university hospitals was studied. Presentation, imaging studies, and outcomes of de novo CS and previously known extracardiac sarcoidosis were compared. Survival free of primary composite outcome (ventricular arrhythmias, heart transplantation, or death) was assessed. Machine learning algorithm was used to study the relative importance of clinical features in predicting outcome. Sixty\u2010two patients with de novo CS and 79 with previously known extracardiac sarcoidosis were included. De novo CS showed more advanced New York Heart Association class (\n              <jats:italic>P<\/jats:italic>\n              =0.02), higher circulating levels of NT\u2010proBNP (N\u2010terminal pro\u2010B\u2010type natriuretic peptide) (\n              <jats:italic>P<\/jats:italic>\n              &lt;0.001), and troponins (\n              <jats:italic>P<\/jats:italic>\n              &lt;0.001), as well as a higher prevalence of right ventricular dysfunction (\n              <jats:italic>P<\/jats:italic>\n              &lt;0.001). During a median (interquartile range) follow\u2010up of 61 (44\u201377) months, event\u2010free survival was shorter in patients with de novo CS (\n              <jats:italic>P<\/jats:italic>\n              &lt;0.001). The top 5 features predicting worse event\u2010free survival in order of importance were as follows: impaired tricuspid annular plane systolic excursion, de novo CS, reduced right ventricular ejection fraction, absence of \u03b2\u2010blockers, and lower left ventricular ejection fraction.\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p xml:lang=\"en\">Patients with de novo CS displayed more severe disease and worse outcomes compared with patients with previously known extracardiac sarcoidosis. Using machine learning, right ventricular dysfunction and de novo CS stand out as strong overall predictors of impaired survival.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/jaha.123.029481","type":"journal-article","created":{"date-parts":[[2023,7,25]],"date-time":"2023-07-25T11:42:16Z","timestamp":1690285336000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":12,"title":["Clinical Outcomes and Predictors of Long\u2010Term Survival in Patients With and Without Previously Known Extracardiac Sarcoidosis Using Machine Learning: A Swedish Multicenter Study"],"prefix":"10.1161","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8287-2448","authenticated-orcid":false,"given":"Emanuele","family":"Bobbio","sequence":"first","affiliation":[{"name":"Department of Cardiology Sahlgrenska University Hospital Gothenburg Sweden"},{"name":"Institute of Medicine at Sahlgrenska Academy University of Gothenburg Gothenburg 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