{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T17:19:56Z","timestamp":1790875196045,"version":"4.1.0"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T00:00:00Z","timestamp":1671494400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,2,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Aims<\/jats:title>\n                  <jats:p>Our goal was to evaluate a previously validated artificial intelligence\u2013augmented electrocardiography (AI-ECG) screening tool for left ventricular systolic dysfunction (LVSD) in patients undergoing high-sensitivity-cardiac troponin T (hs-cTnT).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods and results<\/jats:title>\n                  <jats:p>Retrospective application of AI-ECG for LVSD in emergency department (ED) patients undergoing hs-cTnT. AI-ECG scores (0\u20131) for probability of LVSD (left ventricular ejection fraction \u2264 35%) were obtained. An AI-ECG score \u22650.256 indicates a positive screen. The primary endpoint was a composite of post-discharge major adverse cardiovascular events (MACEs) at two years follow-up. Among 1977 patients, 248 (13%) had a positive AI-ECG. When compared with patients with a negative AI-ECG, those with a positive AI-ECG had a higher risk for MACE [48 vs. 21%, P &amp;lt; 0.0001, adjusted hazard ratio (HR) 1.39, 95% confidence interval (CI) 1.11\u20131.75]. This was largely because of a higher rate of deaths (32 vs. 14%, P &amp;lt; 0.0001; adjusted HR 1.26, 95% 0.95\u20131.66) and heart failure hospitalizations (26 vs. 6.1%, P &amp;lt; 0.001; adjusted HR 1.75, 95% CI 1.25\u20132.45). Together, hs-cTnT and AI-ECG resulted in the following MACE rates and adjusted HRs: hs-cTnT &amp;lt; 99th percentile and negative AI-ECG: 116\/1176 (11%; reference), hs-cTnT &amp;lt; 99th percentile and positive AI-ECG: 28\/107 (26%; adjusted HR 1.54, 95% CI 1.01\u20132.36), hs-cTnT &amp;gt; 99th percentile and negative AI-ECG: 233\/553 (42%; adjusted HR 2.12, 95% CI 1.66, 2.70), and hs-cTnT &amp;gt; 99th percentile and positive AI-ECG: 91\/141 (65%; adjusted HR 2.83, 95% CI 2.06, 3.87).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Among ED patients evaluated with hs-cTnT, a positive AI-ECG for LVSD identifies patients at high risk for MACE. The conjoint use of hs-cTnT and AI-ECG facilitates risk stratification.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/ehjacc\/zuac156","type":"journal-article","created":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T17:36:08Z","timestamp":1671557768000},"page":"106-114","source":"Crossref","is-referenced-by-count":5,"title":["Artificial intelligence\u2013augmented electrocardiography for left ventricular systolic dysfunction in patients undergoing high-sensitivity cardiac troponin T"],"prefix":"10.1093","volume":"12","author":[{"given":"Laura","family":"De Michieli","sequence":"first","affiliation":[{"name":"Department of Cardiovascular Diseases, Mayo Clinic , Rochester, MN , USA"},{"name":"Department of Cardiac, Thoracic and Vascular Sciences and Public Health, University of Padova , Padova , Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan D","family":"Knott","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, Mayo Clinic , Rochester, MN , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9706-7900","authenticated-orcid":false,"given":"Zachi I","family":"Attia","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Diseases, Mayo Clinic , Rochester, MN , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olatunde","family":"Ola","sequence":"additional","affiliation":[{"name":"Department of Hospital Internal Medicine, Mayo Clinic Health System , La Crosse, WI , USA"},{"name":"Center for Clinical and Translational Science, Mayo Clinic Graduate School of Biomedical Sciences , Rochester MN , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramila A","family":"Mehta","sequence":"additional","affiliation":[{"name":"Department of Quantitative Health Sciences, Mayo College of Medicine , Rochester, MN , 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