BACKGROUND AND PURPOSE: Occult paroxysmal atrial fibrillation (AF) is found in a substantial minority of patients with cryptogenic stroke. Identifying reliable predictors of paroxysmal AF after cryptogenic stroke would allow clinicians to more effectively use outpatient cardiac monitoring and ultimately reduce secondary stroke burden. METHODS: We analyzed a retrospective cohort of consecutive patients who underwent 28-day mobile cardiac outpatient telemetry after cryptogenic stroke or transient ischemic stroke. Univariate and multivariable analyses were performed to identify clinical, echocardiographic, and radiographic features associated with the detection of paroxysmal AF. RESULTS: Of 227 patients with cryptogenic stroke (179) or transient ischemic stroke (48), 14% (95% confidence interval, 9%-18%) had AF detected on mobile cardiac outpatient telemetry, 58% of which was ≥30 seconds in duration. Age >60 years (odds ratio, 3.7; 95% confidence interval, 1.3-11) and prior cortical or cerebellar infarction seen on neuroimaging (odds ratio, 3.0; 95% confidence interval, 1.2-7.6) were independent predictors of AF. AF was detected in 33% of patients with both factors, but only 4% of patients with neither. No other clinical features (including demographics, CHA2DS2-VASc [combined stroke risk score: congestive heart failure, hypertension, age, diabetes, prior stroke/transient ischemic attack, vascular disease, sex] score, or stroke symptoms), echocardiographic findings (including left atrial size or ejection fraction), or radiographic characteristics of the acute infarction (including location, topology, or number) were associated with AF detection. CONCLUSIONS: Mobile cardiac outpatient telemetry detects AF in a substantial proportion of cryptogenic stroke patients. Age >60 years and radiographic evidence of prior cortical or cerebellar infarction are robust indicators of occult AF. Patients with neither had a low prevalence of AF.
BACKGROUND AND PURPOSE:Occult paroxysmal atrial fibrillation (AF) is found in a substantial minority of patients with cryptogenic stroke. Identifying reliable predictors of paroxysmal AF after cryptogenic stroke would allow clinicians to more effectively use outpatient cardiac monitoring and ultimately reduce secondary stroke burden. METHODS: We analyzed a retrospective cohort of consecutive patients who underwent 28-day mobile cardiac outpatient telemetry after cryptogenic stroke or transient ischemic stroke. Univariate and multivariable analyses were performed to identify clinical, echocardiographic, and radiographic features associated with the detection of paroxysmal AF. RESULTS: Of 227 patients with cryptogenic stroke (179) or transient ischemic stroke (48), 14% (95% confidence interval, 9%-18%) had AF detected on mobile cardiac outpatient telemetry, 58% of which was ≥30 seconds in duration. Age >60 years (odds ratio, 3.7; 95% confidence interval, 1.3-11) and prior cortical or cerebellar infarction seen on neuroimaging (odds ratio, 3.0; 95% confidence interval, 1.2-7.6) were independent predictors of AF. AF was detected in 33% of patients with both factors, but only 4% of patients with neither. No other clinical features (including demographics, CHA2DS2-VASc [combined stroke risk score: congestive heart failure, hypertension, age, diabetes, prior stroke/transient ischemic attack, vascular disease, sex] score, or stroke symptoms), echocardiographic findings (including left atrial size or ejection fraction), or radiographic characteristics of the acute infarction (including location, topology, or number) were associated with AF detection. CONCLUSIONS: Mobile cardiac outpatient telemetry detects AF in a substantial proportion of cryptogenic strokepatients. Age >60 years and radiographic evidence of prior cortical or cerebellar infarction are robust indicators of occult AF. Patients with neither had a low prevalence of AF.
Authors: Vincent N Thijs; Johannes Brachmann; Carlos A Morillo; Rod S Passman; Tommaso Sanna; Richard A Bernstein; Hans-Christoph Diener; Vincenzo Di Lazzaro; Marilyn M Rymer; Laurence Hogge; Tyson B Rogers; Paul D Ziegler; Manish D Assar Journal: Neurology Date: 2015-12-18 Impact factor: 9.910
Authors: Hebun Erdur; Lennart S Milles; Jan F Scheitz; Kersten Villringer; Karl Georg Haeusler; Matthias Endres; Heinrich J Audebert; Jochen B Fiebach; Christian H Nolte Journal: Eur Radiol Date: 2018-08-23 Impact factor: 5.315
Authors: Ben Freedman; Giuseppe Boriani; Taya V Glotzer; Jeff S Healey; Paulus Kirchhof; Tatjana S Potpara Journal: Nat Rev Cardiol Date: 2017-07-06 Impact factor: 32.419