ID | 32648 |
JaLCDOI | |
FullText URL | |
Author |
Shigenobu, Masaharu
Sogabe, Osanori
Tsuji, Kazuhiro
Senoo, Yoshimasa
Komoto, Yoshiaki
Teramoto, Shigeru
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Abstract | DeVega's annuloplasty was performed on 41 patients with tricuspid regurgitation (TR) associated with combined valvular disease and results were assessed based on Doppler echocardiographic findings in an attempt to examine the applicability of this surgical technique. TR was quantitatively evaluated via Doppler echocardiography before and after surgery. Clinical symptoms, cardiac function, and surgical results were assessed, and the severity of left ventricular myocardial degeneration was determined using electron microscopy. There were no differences in the following factors between the TR recurrence and TR improvement groups: previous heart surgery, number of involved valves, presence or absence of a giant left atrium, preoperative New York Heart Association (NYHA) functional class, and type of prosthetic valve (Bjork-Shiley vs. St. Jude Medical). We found no differences between these two groups in TR severity and tricuspid annulus diameter measured during surgery. Severity of myocardial degeneration was closely associated with the recurrence of TR. Clinically, most had diminished cardiac function before surgery. DeVega's technique appears to be remarkably effective in patients with well-preserved myocardium because no TR recurrence was detected even in examinations with the most accurate Doppler echocardiography. However, such long-term effectiveness of DeVega's technique cannot be expected in patients with degenerated myocardium. |
Keywords | tricuspid reguritation
DeVega's annuloplasty
Doppler echocardiography
myocardial score
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Amo Type | Article
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Publication Title |
Acta Medica Okayama
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Published Date | 1992-04
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Volume | volume46
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Issue | issue2
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Publisher | Okayama University Medical School
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Start Page | 123
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End Page | 128
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ISSN | 0386-300X
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NCID | AA00508441
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Content Type |
Journal Article
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language |
English
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File Version | publisher
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Refereed |
True
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PubMed ID | |
Web of Science KeyUT |