A correlation of the ratio of left atrial volume to left ventricular ejection fraction in predicting atrial fibrillation in ischemic stroke
Left atrial volume index and ischemic stroke
Keywords:
ischemic stroke, atrial fibrillation, left atrial volume, ejection fractionAbstract
Background/Aim: The enlargement of left atrial volume index (LAVI) in diastolic dysfunction (DD) may predispose one to atrial fibrillation (AF) and is an important etiological reason for ischemic stroke (IS). The ratio of LAVI increase to left ventricular ejection fraction (LVEF) is a new parameter, and this work investigates the correlation between DD parameters, LAVI, LAVI/LVEF ratio, and AF in patients with sinus rhythm presenting with IS.
Methods: Here, 108 consecutive individuals who were diagnosed with IS were included in the case-control study. The patients were divided into two groups: Those with AF events on rhythm Holters (AF group, n=57) and those without (control group, n=51). LAVI was calculated from the apical four- and two-chamber views before the mitral valve was opened. LVEF was calculated by Simpson's method.
Results: The mean age of the AF group was 73.9 (6.3) years, and the control group was 72.1 (3.9) years. Hypertension, diabetes mellitus, glucose, HbA1c, CHA₂DS₂-VASc score, and previous stroke were higher in the AF group (P<0.05). LAVI (35.7 [25.3-38.2] vs 29.6 [27.7-30.9], P<0.001), the LAVI/LVEF ratio (0.7 [0.63-0.77] vs 0.5 [0.50-0.54], P<0.001), and the E/é ratio (14.6 [13.9-15.0] vs 10.7 [9.0-11.8], P<0.001) were higher in patients with AF. Multivariable analyses showed that LAVI (OR:7.985, 95%CI [2.586-4.767], P<0.001) and the LAVI/LVEF ratio (OR:0.010, 95% CI [0.000-0.007], P=0.015) were potential independent risk factors for AF events. A positive correlation was found between the CHA₂DS₂-VASc score and LAVI (P=0.032, r=0.407) and LAVI/LVEF ratio (P=0.041, r=0.253).
Conclusion: We concluded that the increase in LAVI and LAVI/LVEF ratio increases the risk of IS by increasing the tendency to AF. These parameters are useful in predicting IS.
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