CLINICAL TRIAL
JOURNAL ARTICLE
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A structured reading algorithm improves telemetric detection of atrial fibrillation after acute ischemic stroke.

BACKGROUND AND PURPOSE: Anticoagulation is a highly effective secondary prevention in patients with cardioembolic stroke and atrial fibrillation/flutter (AF). However, the condition remains underdiagnosed, because paroxysmal AF may be missed by diagnostic tests in the acute phase. In this study, the sensitivity of AF detection was assessed for serial electrocardiographic recordings and continuous stroke unit telemetric monitoring with or without a structured algorithm to analyze telemetric data (SEA-AF).

METHODS: Three hundred forty-six consecutive patients with acute ischemic stroke were prospectively included and subjected to standard telemetric monitoring. In addition, telemetric data were separately analyzed following SEA-AF, consisting of a structured evaluation of episodes with high risk for AF and a chronological beat-to-beat screening of the full registration. Serial electrocardiograms were conducted in 24-hour intervals.

RESULTS: Median effective telemetry monitoring time was 75.5 hours (interquartile range 64-86 hours). Overall, AF was diagnosed in 119 of 346 patients (34.4%). The structured reading algorithm was the most sensitive method to detected AF. Conventional telemetry and serial electrocardiographic assessments were less effective. However, only 35% of patients with previously documented paroxysmal AF and negative baseline electrocardiogram demonstrated AF episodes during monitoring.

CONCLUSIONS: Continuous stroke unit telemetry using SEA-AF shows a significantly higher detection rate for AF compared with daily electrocardiographic assessments and standard telemetry without structured reading. The low overall probability to detect paroxysmal AF with either method during the first days after stroke demonstrates the urgent need for complementary diagnostic strategies such as long-term monitoring and frequent follow-up assessments. Clinical Trial Registration- URL: www.clinicaltrials.gov. Unique identifier: NCT01177748.

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