Literature DB >> 18041489

Evaluation of automated and semi-automated scoring of polysomnographic recordings from a clinical trial using zolpidem in the treatment of insomnia.

Vladimir Svetnik1, Junshui Ma, Keith A Soper, Scott Doran, John J Renger, Steve Deacon, Ken S Koblan.   

Abstract

OBJECTIVE: To evaluate the performance of 2 automated systems, Morpheus and Somnolyzer24X7, with various levels of human review/editing, in scoring polysomnographic (PSG) recordings from a clinical trial using zolpidem in a model of transient insomnia.
METHODS: 164 all-night PSG recordings from 82 subjects collected during 2 nights of sleep, one under placebo and one under zolpidem (10 mg) treatment were used. For each recording, 6 different methods were used to provide sleep stage scores based on Rechtschaffen & Kales criteria: 1) full manual scoring, 2) automated scoring by Morpheus 3) automated scoring by Somnolyzer24X7, 4) automated scoring by Morpheus with full manual review, 5) automated scoring by Morpheus with partial manual review, 6) automated scoring by Somnolyzer24X7 with partial manual review. Ten traditional clinical efficacy measures of sleep initiation, maintenance, and architecture were calculated.
RESULTS: Pair-wise epoch-by-epoch agreements between fully automated and manual scores were in the range of intersite manual scoring agreements reported in the literature (70%-72%). Pair-wise epoch-by-epoch agreements between automated scores manually reviewed were higher (73%-76%). The direction and statistical significance of treatment effect sizes using traditional efficacy endpoints were essentially the same whichever method was used. As the degree of manual review increased, the magnitude of the effect size approached those estimated with fully manual scoring.
CONCLUSION: Automated or semi-automated sleep PSG scoring offers valuable alternatives to costly, time consuming, and intrasite and intersite variable manual scoring, especially in large multicenter clinical trials. Reduction in scoring variability may also reduce the sample size of a clinical trial.

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Year:  2007        PMID: 18041489      PMCID: PMC2082094          DOI: 10.1093/sleep/30.11.1562

Source DB:  PubMed          Journal:  Sleep        ISSN: 0161-8105            Impact factor:   5.849


  15 in total

1.  Computer-assisted sleep staging.

Authors:  R Agarwal; J Gotman
Journal:  IEEE Trans Biomed Eng       Date:  2001-12       Impact factor: 4.538

2.  Proposed supplements and amendments to 'A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects', the Rechtschaffen & Kales (1968) standard.

Authors:  T Hori; Y Sugita; E Koga; S Shirakawa; K Inoue; S Uchida; H Kuwahara; M Kousaka; T Kobayashi; Y Tsuji; M Terashima; K Fukuda; N Fukuda
Journal:  Psychiatry Clin Neurosci       Date:  2001-06       Impact factor: 5.188

3.  Limitations of Rechtschaffen and Kales.

Authors:  Sari Leena Himanen; Joel Hasan
Journal:  Sleep Med Rev       Date:  2000-04       Impact factor: 11.609

4.  A simple format for exchange of digitized polygraphic recordings.

Authors:  B Kemp; A Värri; A C Rosa; K D Nielsen; J Gade
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1992-05

5.  Assessment of automated scoring of polysomnographic recordings in a population with suspected sleep-disordered breathing.

Authors:  Stephen D Pittman; Mary M MacDonald; Robert B Fogel; Atul Malhotra; Koby Todros; Baruch Levy; Amir B Geva; David P White
Journal:  Sleep       Date:  2004-11-01       Impact factor: 5.849

6.  An E-health solution for automatic sleep classification according to Rechtschaffen and Kales: validation study of the Somnolyzer 24 x 7 utilizing the Siesta database.

Authors:  Peter Anderer; Georg Gruber; Silvia Parapatics; Michael Woertz; Tatiana Miazhynskaia; Gerhard Klosch; Bernd Saletu; Josef Zeitlhofer; Manuel J Barbanoj; Heidi Danker-Hopfe; Sari-Leena Himanen; Bob Kemp; Thomas Penzel; Michael Grozinger; Dieter Kunz; Peter Rappelsberger; Alois Schlogl; Georg Dorffner
Journal:  Neuropsychobiology       Date:  2005-04-18       Impact factor: 2.328

7.  Sleep laboratory study on single and repeated dose effects of paroxetine, alprazolam and their combination in healthy young volunteers.

Authors:  Manuel J Barbanoj; Susana Clos; Sergio Romero; Adelaida Morte; Sandra Giménez; José L Lorenzo; Antonio Luque; Rafael Dal-Ré
Journal:  Neuropsychobiology       Date:  2005-04-18       Impact factor: 2.328

8.  Scoring variability between polysomnography technologists in different sleep laboratories.

Authors:  Nancy A Collop
Journal:  Sleep Med       Date:  2002-01       Impact factor: 3.492

9.  Interrater reliability between scorers from eight European sleep laboratories in subjects with different sleep disorders.

Authors:  Heidi Danker-Hopfe; D Kunz; G Gruber; G Klösch; J L Lorenzo; S L Himanen; B Kemp; T Penzel; J Röschke; H Dorn; A Schlögl; E Trenker; G Dorffner
Journal:  J Sleep Res       Date:  2004-03       Impact factor: 3.981

10.  The selective extrasynaptic GABAA agonist, gaboxadol, improves traditional hypnotic efficacy measures and enhances slow wave activity in a model of transient insomnia.

Authors:  James K Walsh; Stephen Deacon; Derk-Jan Dijk; Jonas Lundahl
Journal:  Sleep       Date:  2007-05       Impact factor: 5.849

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  20 in total

1.  Sleep scoring: man vs. machine?

Authors:  Christian Berthomier; Marie Brandewinder
Journal:  Sleep Breath       Date:  2012-05-06       Impact factor: 2.816

Review 2.  Rethinking sleep analysis.

Authors:  Hartmut Schulz
Journal:  J Clin Sleep Med       Date:  2008-04-15       Impact factor: 4.062

3.  Insufficient evidence for the use of automated and semi-automated scoring of polysomnographic recordings.

Authors:  Gary K Zammit
Journal:  Sleep       Date:  2008-04       Impact factor: 5.849

4.  Computer-Assisted Automated Scoring of Polysomnograms Using the Somnolyzer System.

Authors:  Naresh M Punjabi; Naima Shifa; Georg Dorffner; Susheel Patil; Grace Pien; Rashmi N Aurora
Journal:  Sleep       Date:  2015-10-01       Impact factor: 5.849

5.  EOG-based auto-staging: less is more.

Authors:  Christian Berthomier; Marie Brandewinder
Journal:  Sleep Breath       Date:  2015-02-06       Impact factor: 2.816

6.  Performance of an automated polysomnography scoring system versus computer-assisted manual scoring.

Authors:  Atul Malhotra; Magdy Younes; Samuel T Kuna; Ruth Benca; Clete A Kushida; James Walsh; Alexandra Hanlon; Bethany Staley; Allan I Pack; Grace W Pien
Journal:  Sleep       Date:  2013-04-01       Impact factor: 5.849

7.  Sleep staging based on autonomic signals: a multi-center validation study.

Authors:  Jan Hedner; David P White; Atul Malhotra; Sarah Herscovici; Stephen D Pittman; Ding Zou; Ludger Grote; Giora Pillar
Journal:  J Clin Sleep Med       Date:  2011-06-15       Impact factor: 4.062

8.  A comparison of automated and manual sleep staging and respiratory event recognition in a portable sleep diagnostic device with in-lab sleep study.

Authors:  Zhigang Zhang; Mudiaga Sowho; Tamas Otvos; Larissa Sanglard Sperandio; Joshua East; Frank Sgambati; Alan Schwartz; Hartmut Schneider
Journal:  J Clin Sleep Med       Date:  2020-04-15       Impact factor: 4.062

9.  Efficacy of vestipitant, a neurokinin-1 receptor antagonist, in primary insomnia.

Authors:  Emiliangelo Ratti; David J Carpenter; Stefano Zamuner; Sofia Fernandes; Lisa Squassante; Heidi Danker-Hopfe; Graeme Archer; Jonathan Robertson; Robert Alexander; David G Trist; Emilio Merlo-Pich
Journal:  Sleep       Date:  2013-12-01       Impact factor: 5.849

10.  Open-source logic-based automated sleep scoring software using electrophysiological recordings in rats.

Authors:  Brooks A Gross; Christine M Walsh; Apurva A Turakhia; Victoria Booth; George A Mashour; Gina R Poe
Journal:  J Neurosci Methods       Date:  2009-07-15       Impact factor: 2.390

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