Reduced Left Atrial Appendage Flow Is Associated With Future Atrial Fibrillation After Cryptogenic Stroke.

ABSTRACT

BACKGROUND: Hemostasis within the left atrial appendage (LAA) is a common cause of stroke, especially in patients with atrial fibrillation (AF). Although LAA flow provides insights into LAA function, its potential for predicting AF has yet to be established. The aim of this study was to explore whether LAA peak flow velocities early after cryptogenic stroke are associated with future AF on prolonged rhythm monitoring. METHODS: A total of 110 patients with cryptogenic stroke were consecutively enrolled and underwent LAA pulsed-wave Doppler flow assessment using transesophageal echocardiography within the early poststroke period. Velocity measurements were analyzed offline by an investigator blinded to the results. Prolonged rhythm monitoring was conducted on all participants via 7-day Holter and implantable cardiac monitoring devices, with follow-up conducted over a period of 1.5 years to determine the incidence of AF. The end point of AF was defined as irregular supraventricular rhythm with variable RR interval and no detectable P waves lasting ≥30 sec during rhythm monitoring. RESULTS: During a median follow-up period of 539 days (interquartile range, 169-857 days), 42 patients (38%) developed AF, with a median time to AF diagnosis of 94 days (interquartile range, 51-487 days). Both LAA filling velocity and LAA emptying velocity (LAAev) were lower in patients with AF (44.3 ± 14.2 and 50.7 ± 13.3 cm/s, respectively) compared with patients without AF (59.8 ± 14.0 and 76.8 ± 17.3 cm/sec, respectively; P < .001 for both). LAAev was most strongly associated with future AF, with an area under the receiver operating characteristic curve of 0.88 and an optimal cutoff value of 55 cm/sec. Age and mitral regurgitation were independent determinants of reduced LAAev. CONCLUSIONS: Impaired LAA peak flow velocities (LAAev < 55 cm/sec) in patients with cryptogenic stroke are associated with future AF. This may facilitate the selection of appropriate candidates for prolonged rhythm monitoring to improve its diagnostic accuracy and implementation.