Assessment the Predictive Value of Left Atrial Strain (LAS) on Exercise Tolerance in HCM Patients with E/e' between 8 and 14 by Two-Dimensional Speckle Tracking and Treadmill Stress Echocardiography.

Reviews in cardiovascular medicine(2023)

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Abstract
Background:The aim of this study was to evaluate the reservoir, conduit, and contraction function of the left atrium and to evaluate the predictive value of left atrial strain (LAS) on exercise tolerance in hypertrophic cardiomyopathy (HCM) patients with an E/e' between 8 and 14 by two-dimensional speckle tracking using treadmill stress echocardiography. Methods:This was a retrospective study in which we analyzed a total of 70 patients with HCM between 2016 and 2017. According to the resting state E/e', patients were either assigned to an HCM-1 group (E/e' > 14) or an HCM-2 group (E/e' of 8 to 14). Thirty age-matched healthy controls were included in the normal group. Analysis involved the left atrial reservoir, conduit, contraction strain and reserve function. Results:The normal group had a higher left atrial reservoir and conduit strain than the HCM-2 group; the lowest values were in the HCM-1 group. The LAS reserve capacity of the HCM-1 and HCM-2 groups was lower than those of the normal group. The left atrial contraction strain reserve ( Δ LASct%) and global longitudinal strain reserve ( Δ GLS%) were lower in the HCM-2 and HCM-1 groups than in the normal group. We also found that the Δ LASct% and Δ GLS% in the HCM-2 group were higher than in the HCM-1 group. Furthermore, the metabolic equivalents (METS) in the HCM-2 group was greater than that in the HCM-1 group. Finally, the Rest-LASr indicated the highest differential diagnostic performance for METS < 6.0 (area under curve [AUC]: 0.759); the AUC of the composite model Rest-LASr+E/e'-rest was 0.8. Conclusions:Analysis showed that when the E/e' was between 8 and 14, the LAS and reserve capacity of HCM patients were significantly reduced. Our findings suggest that the routine assessment of LAS +E/e' can be a strategy with which to supplement current predictive models and facilitate clinical management strategies.
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