Literature DB >> 8425594

Validation of automated sleep stage and apnoea analysis in suspected obstructive sleep apnoea.

S Andreas1, B von Breska, K Magnusson, H Kreuzer.   

Abstract

Full-night polysomnography is necessary for the diagnosis of obstructive sleep apnoea (OSA). However, analysis of the sleep stages and apnoeas is time-consuming. Computer systems for automated analysis have, thus, been developed to alleviate this task. We investigated 27 consecutive patients referred to our sleep laboratory with suspected OSA. The analysis of sleep stages and apnoeas was performed by visual scoring, according to Rechtschaffen and Kales, and by commercially available automated analysis device. The mean difference between visual scoring and automated analysis was -1, 111, -140, -3, 1 and 27 min, for sleep stages awake, I, II, III, IV and rapid eye movement (REM) respectively. For the apnoea index, the automated analysis rated a lower figure (mean difference 7.h-1, 95% confidence interval 2-12.h-1). The diagnosis of OSA was performed with a sensitivity of 85% and a specificity of 93% by automated analysis. Comparison of two independent handscores showed good agreement, with a mean difference of 6, 4, 3, -7, 1 and -1 min, for sleep stages awake, I, II, III, IV and REM, respectively. In conclusion, the automated analysis underestimates stage I sleep and the apnoea index. Visual scoring is advisable for control of the results. Automated analysis should only be used by those who are able to perform a visual analysis.

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Year:  1993        PMID: 8425594

Source DB:  PubMed          Journal:  Eur Respir J        ISSN: 0903-1936            Impact factor:   16.671


  3 in total

1.  The use of epochs to stage sleep results in incorrect computer-generated AHI values.

Authors:  Mark B Norman; Sally Middleton; Colin E Sullivan
Journal:  Sleep Breath       Date:  2010-04-13       Impact factor: 2.816

2.  Comparison of manual sleep staging with automated neural network-based analysis in clinical practice.

Authors:  Jennifer Caffarel; G John Gibson; J Phil Harrison; Clive J Griffiths; Michael J Drinnan
Journal:  Med Biol Eng Comput       Date:  2006-03       Impact factor: 2.602

3.  Manual vs. automated analysis of polysomnographic recordings in patients with chronic obstructive pulmonary disease.

Authors:  Gerben Stege; Petra J E Vos; P N Richard Dekhuijzen; Pieter H E Hilkens; Marjo J T van de Ven; Yvonne F Heijdra; Frank J J van den Elshout
Journal:  Sleep Breath       Date:  2012-05-10       Impact factor: 2.816

  3 in total

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