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18 results on '"Slostad, Brody"'

1. Unicuspid Aortic Valve: Demographics, Comorbidities, Echocardiographic Features, and Long-Term Outcomes.

Author

Slostad, Brody D., Witt, Chance M., O'Leary, Patrick W., Maleszewski, Joseph J., Scott, Christopher G., Dearani, Joseph A., and Pellikka, Patricia A.

Subjects
*AORTIC valve, *AORTIC valve diseases, *HEART valve diseases, *AORTIC valve transplantation, *AORTIC stenosis, *AORTIC coarctation
Abstract

Keywords: aortic valve; aortic valve stenosis; cardiac surgical procedures; echocardiography; heart valve diseases Unicuspid aortic valve pathology characteristics and long-term outcomes.A, Surgically resected unicuspid (unicommissural) aortic valve (UAV) that exhibits 2 discrete raphes (asterisks) and a single commissure (arrow). Aortic valve, aortic valve stenosis, cardiac surgical procedures, echocardiography, heart valve diseases. [Extracted from the article]

Published
2019
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6. ARTIFICIAL INTELLIGENCE-ASSISTED CLASSIFICATION OF AORTIC STENOSIS SEVERITY.

Author

Arnold, Joshua H., Desai, Kevin V., Slostad, Brody, Bhayani, Siddharth, Ouwerkerk, Wouter, Hummel, Yoran M., Lam, Carolyn S.P., Ezekowitz, Justin A., Frost, Matthew, Jiang, Zhubo, Equilbec, Cyril, Twing, Aamir, Pellikka, Patricia A., Frazin, Leon J., Kansal, Mayank Mohan, and Krishna, Hema

Subjects
*AORTIC stenosis, *CLASSIFICATION
Published
2024
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7. Abstract 12808: Unicuspid Aortic Valve: Demographics, Comorbidities, Echocardiographic Features and Long-Term Outcomes.

Author

Slostad, Brody, Witt, Chance, O'Leary, Patrick, and Pellikka, Patricia

Subjects
*AORTIC valve, *AORTA surgery, *PATENT ductus arteriosus, *NATURAL history, AORTIC valve surgery
Abstract

Introduction: Unicuspid aortic valve (UAV) is a rare disease typically diagnosed by surgical inspection. This study assessed the natural history and outcomes of pathologically confirmed UAV. Methods: The institutional databases (echocardiographic, pathology) and medical record were searched for demographic, echocardiographic and outcome data of all UAV diagnoses. Only UAVs pathologically confirmed post-surgery or at autopsy were included. Results: 81 patients (mean±SD age, 29 ±18 years (range 0-81); male sex, 62%) were identified with pathologically confirmed UAV (83% post-surgery, 17% at autopsy). 67% had ascending aorta dilatation. Aortic stenosis (AS) or aortic regurgitation (AR) of any degree, mixed AR/AS, pure AS, and pure AR was present in 77%, 74%, 58%, 21 %, and 18% of patients, respectively (Table 1). Additional abnormalities included patent foramen ovale (5%), patent ductus arteriosus (5%) and coarctation (4%). At follow up (median 9.9 years) 67 (83%) and 34 (42%) patients had aortic valve surgery (mean ±SD age at surgery, 37 ± 14 years (range 0.1-81); 85% aortic valve replacement (AVR), 4% Ross procedure, 4% heart transplant, 6% unknown type) and ascending aorta surgery (mean ±SD age at aorta surgery, 43 ± 11 years (range 19-67); 82% aortic graft, 9% aortic repair, 9% Ross procedure), respectively (Table 1). 13% of patients had valvotomy prior to surgery. Mean ±SD time to AVR and aorta surgery from diagnosis was 3 ± 9 years and 8 ± 13 years, respectively. Surgical indications were AS (44%), mixed AS/AR (31%), AR (12%) and ascending aortic dilatation (7%). AVR alone and AVR with aorta surgery had similar outcomes (post-surgical survival 100% and 92% for both at 5 and 10 years, respectively (p = 0.32)). Conclusions: To our knowledge this is the largest and most comprehensive natural history and outcomes study of pathologically confirmed UAV. AS and AR were common in UAV and AS was the most common surgery indication. AVR alone and AVR with aorta surgery had similar outcomes. [ABSTRACT FROM AUTHOR]

Published
2018

11. APPLICATION OF MACHINE LEARNING TECHNOLOGY TO AUTOMATE PROXIMAL AORTA DIMENSION BY ECHOCARDIOGRAPHY.

Author

Dohse, Carlos Andres, Kansal, Mayank Mohan, Twing, Aamir, Frost, Matthew, Equilbec, Cyril, Hill, Michael C., Ziccardi, Mary Carolina Rodriguez, Slostad, Brody, Carter, Ashley, Smith, Dale, Tiu, David, Lam, Carolyn S.P., Ezekowitz, Justin A., Pellikka, Patricia A., Behan, Sean, and Krishna, Hema

Subjects
*MACHINE learning, *ECHOCARDIOGRAPHY, *AORTA
Published
2024
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