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1.
JAMA Cardiol ; 9(6): 534-544, 2024 Jun 01.
Article in English | MEDLINE | ID: mdl-38581644

ABSTRACT

Importance: 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. Objective: To deploy DASSi to patients with no AS or with mild or moderate AS at baseline to identify AS development and progression. Design, Setting, and Participants: 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. Exposure: DASSi (range, 0-1) derived from AI applied to echocardiography and CMR videos. Main Outcomes and Measures: Annualized change in peak aortic valve velocity (AV-Vmax) and late (>6 months) aortic valve replacement (AVR). Results: A total of 12 599 participants were included in the echocardiographic study (YNHHS: n = 8798; 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 = 3801; 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-Vmax (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-Vmax. This was reproduced across 45 474 participants (median [IQR] age, 65 [59-71] years; 23 559 [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 ≥0.2 vs those with DASSi <.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. Conclusions and Relevance: 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.


Subject(s)
Aortic Valve Stenosis , Artificial Intelligence , Disease Progression , Echocardiography , Severity of Illness Index , Humans , Aortic Valve Stenosis/diagnostic imaging , Aortic Valve Stenosis/surgery , Aortic Valve Stenosis/physiopathology , Female , Male , Aged , Echocardiography/methods , Middle Aged , Biomarkers , Aged, 80 and over , Cohort Studies , Video Recording , Multimodal Imaging/methods , Magnetic Resonance Imaging/methods
2.
Circ Cardiovasc Qual Outcomes ; 16(1): e009032, 2023 01.
Article in English | MEDLINE | ID: mdl-36603043

ABSTRACT

The COVID-19 pandemic exposed the consequences of systemic racism in the United States with Black, Hispanic, and other racial and ethnic diverse populations dying at disproportionately higher rates than White Americans. Addressing the social and health disparities amplified by COVID-19 requires in part restructuring of the healthcare system, particularly the diversity of the healthcare workforce to better reflect that of the US population. In January 2021, the Association of Black Cardiologists hosted a virtual roundtable designed to discuss key issues pertaining to medical workforce diversity and to identify strategies aimed at improving racial and ethnic diversity in medical school, graduate medical education, faculty, and leadership positions. The Nurturing Diverse Generations of the Medical Workforce for Success with Authenticity roundtable brought together diverse stakeholders and champions of diversity and inclusion to discuss innovative ideas, solutions, and opportunities to address workforce diversification.


Subject(s)
COVID-19 , Cardiologists , Humans , United States/epidemiology , Pandemics , Ethnicity , Workforce
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