BACKGROUND AND PURPOSE: Cardioembolism in paroxysmal atrial fibrillation (pxAF) is a frequent cause of ischemic stroke. Sensitive detection of pxAF after stroke is crucial for adequate secondary stroke prevention; the optimal diagnostic modality to detect pxAF on stroke units is unknown. We compared 24-hour Holter electrocardiography (ECG) with continuous stroke unit ECG monitoring (CEM) for pxAF detection. METHODS: Patients with acute ischemic stroke or transient ischemic attack were prospectively enrolled. After a 12-channel ECG on admission, all patients received 24-hour Holter ECG and CEM. Additionally, ECG monitoring data underwent automated analysis using dedicated software to identify pxAF. Patients with a history of atrial fibrillation or with atrial fibrillation on the admission ECG were excluded. RESULTS: Four hundred ninety-six patients (median age, 69 years; 61.5% male) fulfilled all inclusion criteria (ischemic stroke: 80.4%; transient ischemic attack: 19.6%). Median stroke unit stay lasted 88.8 hours (interquartile range, 65.0-122.0). ECG data for automated CEM analysis were available for a median time of 64.0 hours (43.0-89.8). Paroxysmal AF was documented in 41 of 496 patients (8.3%). Of these, Holter detected pxAF in 34.1%; CEM in 65.9%; and automated CEM in 92.7%. CEM and automated CEM detected significantly more patients with pxAF than Holter (P<0.001), and automated CEM detected more patients than CEM (P<0.001). CONCLUSIONS: Automated analysis of CEM improves pxAF detection in patients with stroke on stroke units compared with 24-hour Holter ECG. The comparative usefulness of prolonged or repetitive Holter ECG recordings requires further evaluation.
BACKGROUND AND PURPOSE:Cardioembolism in paroxysmal atrial fibrillation (pxAF) is a frequent cause of ischemic stroke. Sensitive detection of pxAF after stroke is crucial for adequate secondary stroke prevention; the optimal diagnostic modality to detect pxAF on stroke units is unknown. We compared 24-hour Holter electrocardiography (ECG) with continuous stroke unit ECG monitoring (CEM) for pxAF detection. METHODS:Patients with acute ischemic stroke or transient ischemic attack were prospectively enrolled. After a 12-channel ECG on admission, all patients received 24-hour Holter ECG and CEM. Additionally, ECG monitoring data underwent automated analysis using dedicated software to identify pxAF. Patients with a history of atrial fibrillation or with atrial fibrillation on the admission ECG were excluded. RESULTS: Four hundred ninety-six patients (median age, 69 years; 61.5% male) fulfilled all inclusion criteria (ischemic stroke: 80.4%; transient ischemic attack: 19.6%). Median stroke unit stay lasted 88.8 hours (interquartile range, 65.0-122.0). ECG data for automated CEM analysis were available for a median time of 64.0 hours (43.0-89.8). Paroxysmal AF was documented in 41 of 496 patients (8.3%). Of these, Holter detected pxAF in 34.1%; CEM in 65.9%; and automated CEM in 92.7%. CEM and automated CEM detected significantly more patients with pxAF than Holter (P<0.001), and automated CEM detected more patients than CEM (P<0.001). CONCLUSIONS: Automated analysis of CEM improves pxAF detection in patients with stroke on stroke units compared with 24-hour Holter ECG. The comparative usefulness of prolonged or repetitive Holter ECG recordings requires further evaluation.
Authors: Karl Georg Haeusler; Klaus Gröschel; Martin Köhrmann; Stefan D Anker; Johannes Brachmann; Michael Böhm; Hans-Christoph Diener; Wolfram Doehner; Matthias Endres; Christian Gerloff; Hagen B Huttner; Manfred Kaps; Paulus Kirchhof; Darius Günther Nabavi; Christian H Nolte; Waltraud Pfeilschifter; Burkert Pieske; Sven Poli; Wolf Rüdiger Schäbitz; Götz Thomalla; Roland Veltkamp; Thorsten Steiner; Ulrich Laufs; Joachim Röther; Rolf Wachter; Renate Schnabel Journal: Clin Res Cardiol Date: 2018-04-27 Impact factor: 5.460
Authors: Shadi Yaghi; Yeseon P Moon; Consuelo Mora-McLaughlin; Joshua Z Willey; Ken Cheung; Marco R Di Tullio; Shunichi Homma; Hooman Kamel; Ralph L Sacco; Mitchell S V Elkind Journal: Stroke Date: 2015-04-23 Impact factor: 7.914