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Updated: May 19, 2026

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
Left atrial stiffness as a predictor of one-year mortality after transcatheter aortic valve replacement
Aranna Wicheantawatchai1,2, Chalermchai Komaenthammasophon3, Kullaya Takkavatakarn4
1Division of Cardiology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Background:
In patients with aortic stenosis (AS), risk stratification for valve intervention is primarily based on valve severity, symptom burden, and left ventricular (LV) function. However, cardiac damage may extend beyond the LV to involve the left atrium (LA), which can contribute to adverse outcomes.
Objective:
This study aimed to evaluate the prognostic value of the left atrial stiffness (LAS) in predicting one-year all-cause mortality in patients undergoing transcatheter aortic valve replacement (TAVR).
Method:
We conducted a retrospective study of patients with severe AS who underwent TAVR between 2010 and 2023 at a single tertiary center. LAS was calculated as the ratio of E/e' to LA reservoir strain (LASr) using speckle-tracking echocardiography. Univariable and multivariable Cox regression analyses were performed to identify predictors of one-year mortality. The optimal cutoff value of LAS was determined using receiver operating characteristic (ROC) curve analysis.
Results:
Among 260 patients, LAS was significantly higher in non-survivors than survivors (p < 0.001). In Cox regression analysis, LAS was strongly associated with one-year all-cause mortality (HR, 1.19; 95% CI, 1.11-1.27; p < 0.001) and remained an independent predictor after adjustment for multiple clinical and echocardiographic risk factors. ROC analysis identified an optimal cutoff of 1.69 (AUC 0.88; sensitivity 82%, specificity 80%), which was confirmed by bootstrap validation.
Conclusion:
LAS independently predicts one-year mortality after TAVR and may serve as a valuable addition to established risk stratification models.
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