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Application of left ventricular strain in patients with aortic and mitral valve disease.
Current Opinion in Cardiology 2018 September
PURPOSE OF REVIEW: Left ventricular (LV) global longitudinal strain (GLS) is widely recognized as a more sensitive measure of LV systolic function compared with LV ejection fraction (LVEF). In addition, the measurement of LVGLS is more reproducible than two-dimensional LVEF. Current guidelines for diagnosis and treatment of valvular heart disease include LVEF as one of the parameters to take into consideration in the clinical decision-making. However, a large body of evidence is showing that LVGLS may be a better prognosticator than LVEF in various valvular heart diseases. In this timely state-of-the-art review, the evidence and role of LVGLS as a clinical tool in patients with aortic and mitral valve disease is appraised.
RECENT FINDINGS: Majority of research on LVGLS and valvular heart disease focused on high-gradient aortic stenosis. Increasingly, LVGLS has also been shown to be prognostic in low-flow, low-gradient severe aortic stenosis with preserved LVEF, and in low-flow, low-gradient severe aortic stenosis with reduced LVEF. The role of LV GLS in patients with aortic regurgitation and mitral regurgitation is less well established.
SUMMARY: LVGLS is increasingly used to identify subclinical myocardial dysfunction in patients with valvular heart disease to identify optimal timing for surgery and prognosticate outcomes after surgery.
RECENT FINDINGS: Majority of research on LVGLS and valvular heart disease focused on high-gradient aortic stenosis. Increasingly, LVGLS has also been shown to be prognostic in low-flow, low-gradient severe aortic stenosis with preserved LVEF, and in low-flow, low-gradient severe aortic stenosis with reduced LVEF. The role of LV GLS in patients with aortic regurgitation and mitral regurgitation is less well established.
SUMMARY: LVGLS is increasingly used to identify subclinical myocardial dysfunction in patients with valvular heart disease to identify optimal timing for surgery and prognosticate outcomes after surgery.
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