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Acquired valvular heart disease

  • Masatsugu Iwase
  • Iwao Sotobata
Part of the Developments in Cardiovascular Medicine book series (DICM, volume 95)

Abstract

Mitral stenosis is one of the most common acquired valvular heart diseases. Doppler ultrasound and echocardiography are the most useful method for such evaluation. Two-dimensional echocardiography provides anatomical findings that include: doming of the anterior mitral leaflet in the long axis view, and stenotic mitral orifice like the appearance of a fish mouth in the short axis view (Figure 3.1). The assessment of the mitral valve area can be obtained using parasternal short axis view by planimetry. Depending on the mitral valve area (MVA), the severity is divided into three classes: (1) Mild MVA > 2 cm2, (2) Moderate MVA 1–2 cm2, and (3) Severe MVA < 1 cm2. However, clinical symptoms do not always correspond to this assessment. Sometimes they are related to a low cardiac output state, severe mitral valve calcification and the presence of aortic regurgitation. In these patients, it is also necessary to evaluate the characteristics of the mitral valve leaflets and subvalvular apparatus. The presence of calcification and chordal shortening or fusion should be determined, because these factors have an important role in determining the surgical procedure (commissurotomy or valve replacement). In this entity, an enlarged left atrium, a small left ventricle and a small aortic root dimension are present in severe cases (Figures 3.3, 4). These findings reflect the disturbance of the transmitral flow. M-mode echocardiography provides qualitative rather than quantitative information about mitral stenosis, such as decreased E–F slope and excursion of anterior leaflet with diastolic anterior motion of posterior leaflet (Figures 3.2, 4).

Keywords

Mitral Valve Mitral Regurgitation Infective Endocarditis Aortic Regurgitation Valvular Heart Disease 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 1989

Authors and Affiliations

  • Masatsugu Iwase
    • 1
  • Iwao Sotobata
    • 1
  1. 1.1st Department of Internal MedicineNagoya University School of MedicineNagoyaJapan

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