Literature DB >> 30387545

Performance of an atrial fibrillation detection algorithm using continuous pulse wave monitoring.

Asami Kashiwa1, Fumio Koyama2, Koji Miyamoto1, Tsukasa Kamakura1, Mitsuru Wada1, Kenichiro Yamagata1, Kohei Ishibashi1, Yuko Inoue1, Hideo Okamura1, Satoshi Nagase1, Takashi Noda1, Takeshi Aiba1, Shinichiro Watanabe2, Akihiro Goto2, Satoshi Yasuda1, Kengo Kusano1.   

Abstract

BACKGROUND: Detecting asymptomatic and undiagnosed atrial fibrillation (AF) is increasingly important. Recently, we developed a wristwatch-based pulse wave monitor (PWM; Seiko Epson, Japan) capable of long-term recording, with an automatic diagnosis algorithm that uses frequency-based pulse wave analysis. The aim of this study was to evaluate the validity of continuous pulse wave monitoring for detection of AF.
METHODS: During the electrophysiological study (EPS) in patients with AF, simultaneous pulse wave monitoring and Holter electrocardiograms (ECG) were recorded (n = 136, mean age 62.7 ± 10.9 years). The diagnostic accuracy of the PWM for AF was compared to the Holter ECG diagnosis. Standard performance metrics (sensitivity [Se], specificity [Sp], positive predictive value [PPV], and negative predictive value [NPV]) were calculated. The duration-based measurements were based on the diagnosis concordance ratios for the duration of time between diagnosis detected by the PWM and true diagnosis by the Holter ECG (AF or not AF). The episode-based performance metrics were based on the proportion of episodes appropriately detected with the PWM relative to episodes determined by the Holter ECG.
RESULTS: The total recording time was 1,542,770 s (AF: 270,945 s). A high diagnostic Sp (patient average: 96.4%, cumulative: 97.7%) and NPV (patient average: 95.1%, cumulative: 96.8%) were obtained in the duration-based results. In the episode-based metrics, all indices significantly improved with longer AF episode durations.
CONCLUSIONS: Continuous pulse wave monitoring can provide accurate and dependable information to aid in AF diagnosis. A high validity in confirming freedom from AF was shown by a high NPV.
© 2018 Wiley Periodicals, Inc.

Entities:  

Keywords:  atrial fibrillation; monitoring; pulse wave

Mesh:

Year:  2018        PMID: 30387545      PMCID: PMC6931792          DOI: 10.1111/anec.12615

Source DB:  PubMed          Journal:  Ann Noninvasive Electrocardiol        ISSN: 1082-720X            Impact factor:   1.468


  28 in total

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Journal:  Diabet Med       Date:  2015-08-18       Impact factor: 4.359

2.  Subclinical atrial fibrillation and the risk of stroke.

Authors:  Jeff S Healey; Stuart J Connolly; Michael R Gold; Carsten W Israel; Isabelle C Van Gelder; Alessandro Capucci; C P Lau; Eric Fain; Sean Yang; Christophe Bailleul; Carlos A Morillo; Mark Carlson; Ellison Themeles; Elizabeth S Kaufman; Stefan H Hohnloser
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3.  Screening for atrial fibrillation: sensitivity and specificity of a new methodology.

Authors:  Malcolm Lewis; Dawood Parker; Clive Weston; Mark Bowes
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4.  Meta-analysis: antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation.

Authors:  Robert G Hart; Lesly A Pearce; Maria I Aguilar
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Authors:  Leif Friberg; Mårten Rosenqvist; Arne Lindgren; Andreas Terént; Bo Norrving; Kjell Asplund
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8.  Performance of an atrial fibrillation detection algorithm using continuous pulse wave monitoring.

Authors:  Asami Kashiwa; Fumio Koyama; Koji Miyamoto; Tsukasa Kamakura; Mitsuru Wada; Kenichiro Yamagata; Kohei Ishibashi; Yuko Inoue; Hideo Okamura; Satoshi Nagase; Takashi Noda; Takeshi Aiba; Shinichiro Watanabe; Akihiro Goto; Satoshi Yasuda; Kengo Kusano
Journal:  Ann Noninvasive Electrocardiol       Date:  2018-11-02       Impact factor: 1.468

9.  Device-detected atrial fibrillation and risk for stroke: an analysis of >10,000 patients from the SOS AF project (Stroke preventiOn Strategies based on Atrial Fibrillation information from implanted devices).

Authors:  Giuseppe Boriani; Taya V Glotzer; Massimo Santini; Teena M West; Mirko De Melis; Milan Sepsi; Maurizio Gasparini; Thorsten Lewalter; John A Camm; Daniel E Singer
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Authors:  Tijn Hendrikx; Martin Sundqvist; Herbert Sandström; Carin Sahlin; Morteza Rohani; Faris Al-Khalili; Rolf Hörnsten; Anders Blomberg; Per Wester; Mårten Rosenqvist; Karl A Franklin
Journal:  PLoS One       Date:  2017-02-08       Impact factor: 3.240

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  4 in total

1.  Performance of an atrial fibrillation detection algorithm using continuous pulse wave monitoring.

Authors:  Asami Kashiwa; Fumio Koyama; Koji Miyamoto; Tsukasa Kamakura; Mitsuru Wada; Kenichiro Yamagata; Kohei Ishibashi; Yuko Inoue; Hideo Okamura; Satoshi Nagase; Takashi Noda; Takeshi Aiba; Shinichiro Watanabe; Akihiro Goto; Satoshi Yasuda; Kengo Kusano
Journal:  Ann Noninvasive Electrocardiol       Date:  2018-11-02       Impact factor: 1.468

2.  A New Measure of Pulse Rate Variability and Detection of Atrial Fibrillation Based on Improved Time Synchronous Averaging.

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Review 3.  Atrial fibrillation monitoring with wrist-worn photoplethysmography-based wearables: State-of-the-art review.

Authors:  Linda M Eerikäinen; Alberto G Bonomi; Lukas R C Dekker; Rik Vullings; Ronald M Aarts
Journal:  Cardiovasc Digit Health J       Date:  2020-08-26

4.  Continuous 24-h Photoplethysmogram Monitoring Enables Detection of Atrial Fibrillation.

Authors:  Eemu-Samuli Väliaho; Jukka A Lipponen; Pekka Kuoppa; Tero J Martikainen; Helena Jäntti; Tuomas T Rissanen; Maaret Castrén; Jari Halonen; Mika P Tarvainen; Tiina M Laitinen; Tomi P Laitinen; Onni E Santala; Olli Rantula; Noora S Naukkarinen; Juha E K Hartikainen
Journal:  Front Physiol       Date:  2022-01-04       Impact factor: 4.566

  4 in total

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