Electrocardiographic RR Interval Dynamic Analysis to Identify Acute Stroke Patients at High Risk for Atrial Fibrillation Episodes During Stroke Unit Admission.

Patients at short-term risk of paroxysmal atrial fibrillation (PAF) often exhibit increased RR interval variability during sinus rhythm. We studied if RR dynamic analysis, applied in the first hours after stroke unit (SU) admission, identified acute ischemic stroke patients at higher risk for subsequent PAF episodes detected within the SU hospitalization. Acute ischemic stroke patients underwent continuous cardiac monitoring (CCM) using standard bedside monitors immediately after SU admission.

Improved detection of paroxysmal atrial fibrillation utilizing a software-assisted electrocardiogram approach.

Background: Automated complexity-based statistical stroke risk analysis (SRA) of electrocardiogram (ECG) recordings can be used to estimate the risk of paroxysmal atrial fibrillation (pAF). We investigated whether this method could improve the reliability of detection of patients at risk for pAF.

Methods And Results: Data from 12-lead ECGs, 24-h Holter ECGs, and SRA based on separate 1-hour Holter ECG snips were collected from three groups: 70 patients with a history of pAF but who showed no AF episode in the 12-lead ECG at study entry; 19 patients with chronic AF (at study entry); and 100 young healthy individuals.

Continuous stroke unit electrocardiographic monitoring versus 24-hour Holter electrocardiography for detection of paroxysmal atrial fibrillation after stroke.

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.