{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,11]],"date-time":"2026-11-11T03:21:06Z","timestamp":1794367266659,"version":"4.9.0"},"reference-count":45,"publisher":"American Medical Association (AMA)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Cardiol"],"published-print":{"date-parts":[[2024,6,1]]},"abstract":"<jats:sec id=\"ab-hoi240014-4\">\n                    <jats:title>Importance<\/jats:title>\n                    <jats:p>Aortic stenosis (AS) is a major public health challenge with a growing therapeutic landscape, but current biomarkers do not inform personalized screening and follow-up. A video-based artificial intelligence (AI) biomarker (Digital AS Severity index [DASSi]) can detect severe AS using single-view long-axis echocardiography without Doppler characterization.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"ab-hoi240014-5\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To deploy DASSi to patients with no AS or with mild or moderate AS at baseline to identify AS development and progression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"ab-hoi240014-6\">\n                    <jats:title>Design, Setting, and Participants<\/jats:title>\n                    <jats:p>This is a cohort study that examined 2 cohorts of patients without severe AS undergoing echocardiography in the Yale New Haven Health System (YNHHS; 2015-2021) and Cedars-Sinai Medical Center (CSMC; 2018-2019). A novel computational pipeline for the cross-modal translation of DASSi into cardiac magnetic resonance (CMR) imaging was further developed in the UK Biobank. Analyses were performed between August 2023 and February 2024.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"ab-hoi240014-7\">\n                    <jats:title>Exposure<\/jats:title>\n                    <jats:p>DASSi (range, 0-1) derived from AI applied to echocardiography and CMR videos.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"ab-hoi240014-8\">\n                    <jats:title>Main Outcomes and Measures<\/jats:title>\n                    <jats:p>\n                      Annualized change in peak aortic valve velocity (AV-V\n                      <jats:sub>max<\/jats:sub>\n                      ) and late (&amp;amp;gt;6 months) aortic valve replacement (AVR).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"ab-hoi240014-9\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 12\u202f599 participants were included in the echocardiographic study (YNHHS: n\u2009=\u20098798; median [IQR] age, 71 [60-80] years; 4250 [48.3%] women; median [IQR] follow-up, 4.1 [2.4-5.4] years; and CSMC: n\u2009=\u20093801; median [IQR] age, 67 [54-78] years; 1685 [44.3%] women; median [IQR] follow-up, 3.4 [2.8-3.9] years). Higher baseline DASSi was associated with faster progression in AV-V\n                      <jats:sub>max<\/jats:sub>\n                      (per 0.1 DASSi increment: YNHHS, 0.033 m\/s per year [95% CI, 0.028-0.038] among 5483 participants; CSMC, 0.082 m\/s per year [95% CI, 0.053-0.111] among 1292 participants), with values of 0.2 or greater associated with a 4- to 5-fold higher AVR risk than values less than 0.2 (YNHHS: 715 events; adjusted hazard ratio [HR], 4.97 [95% CI, 2.71-5.82]; CSMC: 56 events; adjusted HR, 4.04 [95% CI, 0.92-17.70]), independent of age, sex, race, ethnicity, ejection fraction, and AV-V\n                      <jats:sub>max<\/jats:sub>\n                      . This was reproduced across 45\u202f474 participants (median [IQR] age, 65 [59-71] years; 23\u202f559 [51.8%] women; median [IQR] follow-up, 2.5 [1.6-3.9] years) undergoing CMR imaging in the UK Biobank (for participants with DASSi \u22650.2 vs those with DASSi &amp;amp;lt;.02, adjusted HR, 11.38 [95% CI, 2.56-50.57]). Saliency maps and phenome-wide association studies supported associations with cardiac structure and function and traditional cardiovascular risk factors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"ab-hoi240014-10\">\n                    <jats:title>Conclusions and Relevance<\/jats:title>\n                    <jats:p>In this cohort study of patients without severe AS undergoing echocardiography or CMR imaging, a new AI-based video biomarker was independently associated with AS development and progression, enabling opportunistic risk stratification across cardiovascular imaging modalities as well as potential application on handheld devices.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1001\/jamacardio.2024.0595","type":"journal-article","created":{"date-parts":[[2024,4,6]],"date-time":"2024-04-06T11:30:31Z","timestamp":1712403031000},"page":"534","source":"Crossref","is-referenced-by-count":71,"title":["A Multimodal 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