{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T08:23:37Z","timestamp":1792657417120,"version":"4.5.0"},"reference-count":35,"publisher":"American Medical Association (AMA)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Cardiol"],"published-print":{"date-parts":[[2026,2,1]]},"abstract":"\n Importance<\/jats:title>\n Transthyretin amyloid cardiomyopathy (ATTR-CM) is underdiagnosed despite expanding treatment options.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To develop and evaluate an artificial intelligence (AI)\u2013augmented clinical program for ATTR-CM detection.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This nonrandomized clinical trial involved constructing an AI model, ATTRACTnet, using electrocardiogram waveforms, echocardiographic measurements, demographics, and diagnosis codes for orthopedic manifestations of amyloidosis. A single-system, multisite, single-arm, open-label trial was conducted to evaluate its real-world performance. The model was trained and validated at a large academic referral site for ATTR-CM with external validation at an academic site. The trial was conducted as a single-system, multisite trial. Patients with left ventricular (LV) wall thickness 12 mm or more and an ATTRACTnet score 0.5 or higher were eligible. Exclusions included prior ATTR-CM testing, hypertrophic cardiomyopathy, expected life span less than 1 year, nursing home residence, advanced dementia, or LV wall thickness less than 14 mm explained by uncontrolled hypertension or moderate\/severe aortic stenosis.<\/jats:p>\n <\/jats:sec>\n \n Intervention<\/jats:title>\n Eligible patients were notified and offered nuclear scintigraphy testing, monoclonal protein testing, and follow-up care on agreement from the treating physician.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measure<\/jats:title>\n The primary outcome was a diagnosis of ATTR-CM by consensus criteria. ATTR-CM testing positivity was compared with historical and contemporary controls.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n ATTRACTnet was developed in an internal test set of 799 patients (mean [SD] age, 75.1 [11.1] years; 516 [64.7%] male and 283 [35.3%] female) using 5-fold cross-validation with an additional external test set of 422 patients. It had good discrimination for ATTR-CM detection with an area under the receiver operator characteristic curve of 0.85 (5-fold cross-validation, 0.77-0.85) in the internal set and 0.82 (95% CI, .81-0.83) in the external test set with similar performance in Hispanic, non-Hispanic Black, and non-Hispanic White patients. A total of 1471 patients were identified with positive AI model scores 0.5 or more during the study period, with 256 eligible patients who met study criteria. Of these patients, 50 underwent amyloidosis testing after physician and patient approval; 24 (48%) were diagnosed with ATTR-CM, and 21 (88%) initiated treatment within 3 months. The positivity rate was more than 2.8 times higher than historical controls (15.3%; 95% CI, 13.1%-17.9%;\n P<\/jats:italic>\n \u2009&amp;lt;\u2009.001), with an 18% relative increase in new diagnoses vs the prior year.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n AI-augmented screening may improve ATTR-CM detection and identify patients who are missed by usual care. Prospective randomized trials are needed to determine if outcomes are improved.<\/jats:p>\n <\/jats:sec>\n \n Trial Registration<\/jats:title>\n \n ClinicalTrials.gov Identifier:\n NCT06469372<\/jats:ext-link>\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamacardio.2025.4591","type":"journal-article","created":{"date-parts":[[2025,11,10]],"date-time":"2025-11-10T20:30:18Z","timestamp":1762806618000},"page":"117","source":"Crossref","is-referenced-by-count":14,"title":["Detecting Transthyretin Cardiac Amyloidosis With Artificial Intelligence"],"prefix":"10.1001","volume":"11","author":[{"given":"Sneha S.","family":"Jain","sequence":"first","affiliation":[{"name":"Division of Cardiovascular Medicine and the Cardiovascular Institute, Stanford University, Palo Alto, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tony","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Columbia University, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emma","family":"Pierson","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of California, Berkeley"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francisco","family":"Roedan Oliver","sequence":"additional","affiliation":[{"name":"Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center and New York\u2013Presbyterian Hospital, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paloma","family":"Malta","sequence":"additional","affiliation":[{"name":"Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center and New York\u2013Presbyterian Hospital, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michelle","family":"Castillo","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Columbia University, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ningxin","family":"Wan","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Weill Cornell Medicine, New York, New York"},{"name":"Department of Cardiology, New York\u2013Presbyterian Queens Hospital, Flushing"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shudhanshu","family":"Alishetti","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Weill Cornell Medicine, New York, New York"},{"name":"Department of Cardiology, New York\u2013Presbyterian Brooklyn Methodist Hospital, Brooklyn"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heidi","family":"Hartman","sequence":"additional","affiliation":[{"name":"Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center and New York\u2013Presbyterian Hospital, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joshua","family":"Finer","sequence":"additional","affiliation":[{"name":"Information Technology Data Science, New York\u2013Presbyterian Hospital, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kathleen L.","family":"Brown","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Columbia University, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vijendra","family":"Ramlall","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Columbia University, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicholas","family":"Tatonetti","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Columbia University, New York, New York"},{"name":"Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, California"},{"name":"Cedars-Sinai Cancer, Cedars-Sinai Medical Center, Los Angeles, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"No\u00e9mie","family":"Elhadad","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Columbia University, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fatima","family":"Rodriguez","sequence":"additional","affiliation":[{"name":"Division of Cardiovascular Medicine and the Cardiovascular Institute, Stanford University, Palo Alto, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ronald","family":"Witteles","sequence":"additional","affiliation":[{"name":"Division of Cardiovascular Medicine and the Cardiovascular Institute, Stanford University, Palo Alto, California"},{"name":"Stanford Amyloid Center, Stanford, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Parag","family":"Goyal","sequence":"additional","affiliation":[{"name":"Program for the Care and Study of the Aging Heart, Department of Medicine, Weill Cornell Medicine, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shunichi","family":"Homma","sequence":"additional","affiliation":[{"name":"Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center and New York\u2013Presbyterian Hospital, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew J.","family":"Einstein","sequence":"additional","affiliation":[{"name":"Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center and New York\u2013Presbyterian Hospital, New York"},{"name":"Department of Radiology, New York\u2013Presbyterian Hospital and Columbia University Irving Medical Center, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mathew S.","family":"Maurer","sequence":"additional","affiliation":[{"name":"Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center and New York\u2013Presbyterian Hospital, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pierre","family":"Elias","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Columbia University, New York, New York"},{"name":"Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center and New York\u2013Presbyterian Hospital, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy J.","family":"Poterucha","sequence":"additional","affiliation":[{"name":"Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center and New York\u2013Presbyterian Hospital, New York"},{"name":"Department of Cardiology, Mayo Clinic, Rochester, Minnesota"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10","reference":[{"issue":"11","key":"hoi250070r1","doi-asserted-by":"publisher","first-page":"1007","DOI":"10.1056\/NEJMoa1805689","article-title":"Tafamidis treatment for patients with transthyretin amyloid cardiomyopathy.","volume":"379","author":"Maurer","year":"2018","journal-title":"N Engl J Med"},{"issue":"7","key":"hoi250070r2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0254104","article-title":"Wild-type TTR amyloidosis among patients with unexplained heart failure and systolic LV dysfunction.","volume":"16","author":"Goland","year":"2021","journal-title":"PLoS One"},{"issue":"5","key":"hoi250070r3","doi-asserted-by":"publisher","first-page":"S35","DOI":"10.1016\/j.cardfail.2022.03.095","article-title":"Heart failure with reduced ejection fraction: an under-appreciated clinical phenotype of transthyretin cardiac amyloid (ATTR-CA).","volume":"28","author":"Bhattacharya","year":"2022","journal-title":"J Card Fail"},{"issue":"3","key":"hoi250070r4","doi-asserted-by":"publisher","first-page":"171","DOI":"10.3109\/13506129.2015.1051219","article-title":"Prevalence of the amyloidogenic transthyretin (TTR) V122I allele in 14?333 African-Americans.","volume":"22","author":"Jacobson","year":"2015","journal-title":"Amyloid"},{"issue":"7","key":"hoi250070r5","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1056\/NEJM199702133360703","article-title":"Variant-sequence transthyretin (isoleucine 122) in late-onset cardiac amyloidosis in Black Americans.","volume":"336","author":"Jacobson","year":"1997","journal-title":"N Engl J Med"},{"issue":"4","key":"hoi250070r6","first-page":"372","article-title":"Ethnic distribution of amyloidosis: an autopsy study.","volume":"2","author":"Buck","year":"1989","journal-title":"Mod Pathol"},{"issue":"6","key":"hoi250070r7","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCHEARTFAILURE.115.002558","article-title":"Transthyretin cardiac amyloidosis in Black Americans.","volume":"9","author":"Shah","year":"2016","journal-title":"Circ Heart Fail"},{"issue":"6","key":"hoi250070r8","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1007\/s12170-021-00670-y","article-title":"Racial and ethnic disparities in transthyretin cardiac amyloidosis.","volume":"15","author":"Spencer-Bonilla","year":"2021","journal-title":"Curr Cardiovasc Risk Rep"},{"issue":"1","key":"hoi250070r9","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1056\/NEJMoa1404852","article-title":"The amyloidogenic V122I transthyretin variant in elderly Black Americans.","volume":"372","author":"Quarta","year":"2015","journal-title":"N Engl J Med"},{"issue":"9","key":"hoi250070r10","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1001\/jamacardio.2018.2093","article-title":"Geographic disparities in reported US amyloidosis mortality from 1979 to 2015: potential underdetection of cardiac amyloidosis.","volume":"3","author":"Alexander","year":"2018","journal-title":"JAMA Cardiol"},{"issue":"7","key":"hoi250070r11","doi-asserted-by":"publisher","first-page":"733","DOI":"10.1038\/gim.2016.200","article-title":"Transthyretin V122I (pV142I)* cardiac amyloidosis: an age-dependent autosomal dominant cardiomyopathy too common to be overlooked as a cause of significant heart disease in elderly African Americans.","volume":"19","author":"Buxbaum","year":"2017","journal-title":"Genet Med"},{"issue":"15","key":"hoi250070r12","doi-asserted-by":"publisher","DOI":"10.1161\/JAHA.123.030802","article-title":"Transthyretin cardiac amyloidosis: underrecognized in the underrepresented.","volume":"12","author":"Leedy","year":"2023","journal-title":"J Am Heart Assoc"},{"issue":"15","key":"hoi250070r13","doi-asserted-by":"publisher","DOI":"10.1161\/JAHA.122.028973","article-title":"Clinical penetrance of the transthyretin V122I variant in older Black patients with heart failure: the SCAN-MP (Screening for Cardiac Amyloidosis With Nuclear Imaging in Minority Populations) study.","volume":"12","author":"Madhani","year":"2023","journal-title":"J Am Heart Assoc"},{"issue":"5","key":"hoi250070r14","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCGEN.121.003356","article-title":"Prevalence and outcomes of p.Val142Ile TTR amyloidosis cardiomyopathy: a systematic review.","volume":"14","author":"Chandrashekar","year":"2021","journal-title":"Circ Genom Precis Med"},{"issue":"22","key":"hoi250070r15","doi-asserted-by":"publisher","first-page":"2191","DOI":"10.1001\/jama.2019.17935","article-title":"Association of the V122I hereditary transthyretin amyloidosis genetic variant with heart failure among individuals of African or Hispanic\/Latino ancestry.","volume":"322","author":"Damrauer","year":"2019","journal-title":"JAMA"},{"issue":"2","key":"hoi250070r16","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1007\/s10741-015-9480-0","article-title":"Cardiac amyloidosis: the great pretender.","volume":"20","author":"Rapezzi","year":"2015","journal-title":"Heart Fail Rev"},{"issue":"1","key":"hoi250070r17","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/s40119-021-00219-5","article-title":"Impact of delayed diagnosis and misdiagnosis for patients with transthyretin amyloid cardiomyopathy (ATTR-CM): a targeted literature review.","volume":"10","author":"Rozenbaum","year":"2021","journal-title":"Cardiol Ther"},{"issue":"10","key":"hoi250070r18","doi-asserted-by":"publisher","first-page":"1014","DOI":"10.1016\/j.jacc.2016.06.033","article-title":"Natural history of wild-type transthyretin cardiac amyloidosis and risk stratification using a novel staging system.","volume":"68","author":"Grogan","year":"2016","journal-title":"J Am Coll Cardiol"},{"issue":"6","key":"hoi250070r19","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1093\/ehjci\/jeab226","article-title":"Tafamidis treatment delays structural and functional changes of the left ventricle in patients with transthyretin amyloid cardiomyopathy.","volume":"23","author":"Rettl","year":"2022","journal-title":"Eur Heart J Cardiovasc Imaging"},{"issue":"1","key":"hoi250070r20","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1056\/NEJMoa2409134","article-title":"Vutrisiran in patients with transthyretin amyloidosis with cardiomyopathy.","volume":"392","author":"Fontana","year":"2024","journal-title":"N Engl J Med"},{"issue":"10","key":"hoi250070r21","doi-asserted-by":"publisher","first-page":"1036","DOI":"10.1001\/jamacardio.2022.1781","article-title":"A simple score to identify increased risk of transthyretin amyloid cardiomyopathy in heart failure with preserved ejection fraction.","volume":"7","author":"Davies","year":"2022","journal-title":"JAMA Cardiol"},{"issue":"1","key":"hoi250070r22","doi-asserted-by":"publisher","first-page":"2725","DOI":"10.1038\/s41467-021-22876-9","article-title":"A machine learning model for identifying patients at risk for wild-type transthyretin amyloid cardiomyopathy.","volume":"12","author":"Huda","year":"2021","journal-title":"Nat Commun"},{"issue":"1","key":"hoi250070r23","doi-asserted-by":"publisher","first-page":"2726","DOI":"10.1038\/s41467-021-22877-8","article-title":"Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms.","volume":"12","author":"Goto","year":"2021","journal-title":"Nat Commun"},{"issue":"7","key":"hoi250070r24","article-title":"ASNC\/AHA\/ASE\/EANM\/HFSA\/ISA\/SCMR\/SNMMI Expert consensus recommendations for multimodality imaging in cardiac amyloidosis: part 1 of 2, evidence base and standardized methods of imaging.","volume":"14","author":"Dorbala","year":"2021","journal-title":"Circ Cardiovasc Imaging"},{"issue":"7","key":"hoi250070r25","doi-asserted-by":"publisher","DOI":"10.1161\/HCI.0000000000000030","article-title":"ASNC\/AHA\/ASE\/EANM\/HFSA\/ISA\/SCMR\/SNMMI Expert consensus recommendations for multimodality imaging in cardiac amyloidosis: part 2 of 2, diagnostic criteria and appropriate utilization.","volume":"14","author":"Dorbala","year":"2021","journal-title":"Circ Cardiovasc Imaging"},{"issue":"3","key":"hoi250070r26","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1002\/mgg3.224","article-title":"Medical genetics and genomic medicine in the Dominican Republic: challenges and opportunities.","volume":"4","author":"Estrada-Veras","year":"2016","journal-title":"Mol Genet Genomic Med"},{"issue":"1","key":"hoi250070r27","doi-asserted-by":"publisher","first-page":"6596","DOI":"10.1038\/ncomms7596","article-title":"Unravelling the hidden ancestry of American admixed populations.","volume":"6","author":"Montinaro","year":"2015","journal-title":"Nat Commun"},{"issue":"37","key":"hoi250070r29","doi-asserted-by":"publisher","first-page":"3651","DOI":"10.1093\/eurheartj\/ehaf450","article-title":"Artificial intelligence-enabled electrocardiography and echocardiography to track preclinical progression of transthyretin amyloid cardiomyopathy.","volume":"46","author":"Oikonomou","year":"2025","journal-title":"Eur Heart J"},{"issue":"8","key":"hoi250070r30","doi-asserted-by":"publisher","DOI":"10.1161\/JAHA.124.036533","article-title":"Value of artificial intelligence for enhancing suspicion of cardiac amyloidosis using electrocardiography and echocardiography: a narrative review.","volume":"14","author":"Grogan","year":"2025","journal-title":"J Am Heart Assoc"},{"issue":"11","key":"hoi250070r31","doi-asserted-by":"publisher","first-page":"2768","DOI":"10.1016\/j.mayocp.2021.04.023","article-title":"Artificial intelligence-enhanced electrocardiogram for the early detection of cardiac amyloidosis.","volume":"96","author":"Grogan","year":"2021","journal-title":"Mayo Clin Proc"},{"issue":"4","key":"hoi250070r32","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1001\/jamacardio.2021.6059","article-title":"High-throughput precision phenotyping of left ventricular hypertrophy with cardiovascular deep learning.","volume":"7","author":"Duffy","year":"2022","journal-title":"JAMA Cardiol"},{"issue":"40","key":"hoi250070r33","doi-asserted-by":"publisher","first-page":"4090","DOI":"10.1093\/eurheartj\/ehaf387","article-title":"Cardiac amyloidosis detection from a single echocardiographic video clip: a novel artificial intelligence-based screening tool.","volume":"46","author":"Slivnick","year":"2025","journal-title":"Eur Heart J"},{"issue":"6464","key":"hoi250070r34","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1126\/science.aax2342","article-title":"Dissecting racial bias in an algorithm used to manage the health of populations.","volume":"366","author":"Obermeyer","year":"2019","journal-title":"Science"},{"issue":"8","key":"hoi250070r35","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacadv.2025.101901","article-title":"Evaluating the performance and potential bias of predictive models for detection of transthyretin cardiac amyloidosis.","volume":"4","author":"Hourmozdi","year":"2025","journal-title":"JACC Adv"},{"key":"hoi250070r28","unstructured":"GitHub. IntroECG: \/8-CADNet ATTR Model. Accessed October 24, 2025. https:\/\/github.com\/PierreElias\/IntroECG\/tree\/master\/8-CADNet%20ATTR%20Model"}],"container-title":["JAMA Cardiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/jamanetwork.com\/journals\/jamacardiology\/articlepdf\/2841169\/jamacardiology_jain_2025_oi_250070_1770405046.00595.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T16:00:24Z","timestamp":1770825624000},"score":1,"resource":{"primary":{"URL":"https:\/\/jamanetwork.com\/journals\/jamacardiology\/fullarticle\/2841169"}},"subtitle":["A Nonrandomized Clinical Trial"],"short-title":[],"issued":{"date-parts":[[2026,2,1]]},"references-count":35,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,2,1]]}},"URL":"https:\/\/doi.org\/10.1001\/jamacardio.2025.4591","relation":{},"ISSN":["2380-6583"],"issn-type":[{"value":"2380-6583","type":"print"}],"subject":[],"published":{"date-parts":[[2026,2,1]]}}}