Literature DB >> 25538198

Reliability and limitations of automated arrhythmia detection in telemetric monitoring after stroke.

Natalia Kurka1, Tobias Bobinger2, Bernd Kallmünzer2, Julia Koehn2, Peter D Schellinger2, Stefan Schwab2, Martin Köhrmann2.   

Abstract

BACKGROUND AND
PURPOSE: Guidelines recommend continuous ECG monitoring in patients with cerebrovascular events. Studies on intensive care units (ICU) demonstrated high sensitivity but high rates of false alarms of monitoring systems resulting in desensitization of medical personnel potentially endangering patient safety. Data on patients with acute stroke are lacking.
METHODS: One-hundred fifty-one consecutive patients with acute cerebrovascular events were prospectively included. Automatically identified arrhythmia events were analyzed by manual ECG analysis. Muting of alarms was registered. Sensitivity was evaluated by beat-to-beat analysis of the entire recorded ECG data in a subset of patients. Ethics approval was obtained by University of Erlangen-Nuremberg.
RESULTS: A total of 4809.5 hours of ECG registration and 22 509 alarms were analyzed. The automated detection algorithm missed no events but the overall rate of false alarms was 27.4%. Only 0.6% of all alarms indicated acute life-threatening events and 91.4% of these alarms were incorrect. Transient muting of acoustic alarms was observed in 20.5% patients.
CONCLUSIONS: Continuous ECG monitoring using automated arrhythmia detection is highly sensitive in acute stroke. However, high rates of false alarms and alarms without direct therapeutic consequence cause desensitization of personnel. Therefore, acoustic alarms may be limited to life-threatening events but standardized manual evaluation of all alarms should complement automated systems to identify clinically relevant arrhythmias.
© 2014 American Heart Association, Inc.

Entities:  

Keywords:  arrhythmia; electrocardiography; monitoring; stroke

Mesh:

Year:  2014        PMID: 25538198     DOI: 10.1161/STROKEAHA.114.007892

Source DB:  PubMed          Journal:  Stroke        ISSN: 0039-2499            Impact factor:   7.914


  1 in total

Review 1.  Detection of Atrial Fibrillation in Cryptogenic Stroke.

Authors:  Karl Georg Haeusler; Serdar Tütüncü; Renate B Schnabel
Journal:  Curr Neurol Neurosci Rep       Date:  2018-08-08       Impact factor: 5.081

  1 in total

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