Why the study?
The study assessed the association of 2D and 3D left atrial strain and low-voltage area with atrial fibrillation recurrence following pulmonary vein isolation.
Does 3D left atrial strain predict recurrence of atrial fibrillation in patients undergoing pulmonary vein isolation?
Does 3D left atrial strain predict recurrence of atrial fibrillation in patients undergoing pulmonary vein isolation?
3D left atrial reservoir and pump strain are independent predictors of atrial fibrillation recurrence after pulmonary vein isolation, offering improved risk stratification.
Lower 3D LAS may aid post-PVI recurrence risk stratification; hypothesis-generating pending validation in larger cohorts.
Aims: Association of two-(2D) and three-dimensional (3D) left atrial strain (LAS) and low-voltage area (LVA) with recurrence of atrial fibrillation (AF) after pulmonary vein isolation (PVI) was assessed. Methods and results: 3D LAS, 2D LAS, and LVA were obtained in 93 consecutive patients undergoing PVI and recurrence of AF was analyzed prospectively. AF recurred in 12 patients (13%). The 3D left atrial reservoir strain (LARS) and pump strain (LAPS) were lower in patients with recurrent AF than without (p = 0.008 and p = 0.009, respectively). In univariable Cox regression, 3D LARS or LAPS were associated with recurrent AF (LARS: HR = 0.89 (0.81–0.99), p = 0.025; LAPS: HR = 1.40 (1.02–1.92), p = 0.040), while other values were not. Association of 3D LARS or LAPS with recurrent AF was independent of age, body mass index, arterial hypertension, left ventricular ejection fraction, and end-diastolic volume index and left atrial volume index in multivariable models. Kaplan–Meier curves revealed that patients with 3D LAPS < −5.9% did not exhibit recurrent AF, while those >−5.9% had a significant risk of recurrent AF. Conclusions: 3D LARS and LAPS were associated with recurrent AF after PVI. Association of 3D LAS was independent of relevant clinical and echocardiographic parameters and improved their predictive value. Hence, they may be applied for outcome prediction in patients undergoing PVI.
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Krizanovic-Grgic et al. (2023) studied this question.
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