Literature DB >> 15721084

Inter-rater reliability of sleep cyclic alternating pattern (CAP) scoring and validation of a new computer-assisted CAP scoring method.

Raffaele Ferri1, Oliviero Bruni, Silvia Miano, Arianna Smerieri, Karen Spruyt, Mario G Terzano.   

Abstract

OBJECTIVE: To assess inter-rater reliability between different scorers, from different qualified sleep research groups, in scoring visually the Cyclic Alternating Pattern (CAP), to evaluate the performances of a new tool for the computer-assisted detection of CAP, and to compare its output with the data from the different scorers.
METHODS: CAP was scored in 11 normal sleep recordings by four different raters, coming from three sleep laboratories. CAP was also scored in the same recordings by means of a new computer-assisted method, implemented in the Hypnolab 1.2 (SWS Soft, Italy) software. Data analysis was performed according to the following steps: (a) the inter-rater reliability of CAP parameters between the four different scorers was carried out by means of the Kendall W coefficient of concordance; (b) the analysis of the agreement between the results of the visual and computer-assisted analysis of CAP parameters was also carried out by means of the Kendall W coefficient; (c) a 'consensus' scoring was obtained, for each recording, from the four scorings provided by the different raters, based on the score of the majority of scorers; (d) the degree of agreement between each scorer and the consensus score and between the computer-assisted analysis and the consensus score was quantified by means of the Cohen's k coefficient; (e) the differences between the number of false positive and false negative detections obtained in the visual and in the computer-assisted analysis were also evaluated by means of the non-parametric Wilcoxon test.
RESULTS: The inter-rater reliability of CAP parameters quantified by the Kendall W coefficient of concordance between the four different scorers was high for all the parameters considered and showed values above 0.9 for total CAP time, CAP time in sleep stage 2 and percentage of A phases in sequence; also CAP rate showed a high value (0.829). The most important global parameters of CAP, including total CAP rate and CAP time, scored by the computer-assisted analysis showed a significant concordance with those obtained by the raters. The agreement between the computer-assisted analysis and the consensus scoring for the assignment of the CAP A phase subtype was not distinguishable from that expected from a human scorer. However, the computer-assisted analysis provided a number of false positives and false negatives significantly higher than that of the visual scoring of CAP.
CONCLUSIONS: CAP scoring shows good inter-rater reliability and might be compared in different laboratories the results of which might also be pooled together; however, caution should always be taken because of the variability which can be expected in the classical sleep staging. The computer-assisted detection of CAP can be used with some supervision and correction in large studies when only general parameters such as CAP rate are considered; more editing is necessary for the correct use of the other results. SIGNIFICANCE: This article describes the first attempt in the literature to evaluate in a detailed way the inter-rater reliability in scoring CAP parameters of normal sleep and the performances of a human-supervised computerized automatic detection system.

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Year:  2004        PMID: 15721084     DOI: 10.1016/j.clinph.2004.09.021

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  12 in total

1.  Efficient automatic classifiers for the detection of A phases of the cyclic alternating pattern in sleep.

Authors:  Sara Mariani; Elena Manfredini; Valentina Rosso; Andrea Grassi; Martin O Mendez; Alfonso Alba; Matteo Matteucci; Liborio Parrino; Mario G Terzano; Sergio Cerutti; Anna M Bianchi
Journal:  Med Biol Eng Comput       Date:  2012-03-20       Impact factor: 2.602

2.  Analysis of A-phase transitions during the cyclic alternating pattern under normal sleep.

Authors:  Martin Oswaldo Mendez; Ioanna Chouvarda; Alfonso Alba; Anna Maria Bianchi; Andrea Grassi; Edgar Arce-Santana; Guilia Milioli; Mario Giovanni Terzano; Liborio Parrino
Journal:  Med Biol Eng Comput       Date:  2015-08-08       Impact factor: 2.602

Review 3.  A review of signals used in sleep analysis.

Authors:  A Roebuck; V Monasterio; E Gederi; M Osipov; J Behar; A Malhotra; T Penzel; G D Clifford
Journal:  Physiol Meas       Date:  2013-12-17       Impact factor: 2.833

4.  Characterization of cyclic alternating pattern during sleep in older men and women using large population studies.

Authors:  Simon Hartmann; Oliviero Bruni; Raffaele Ferri; Susan Redline; Mathias Baumert
Journal:  Sleep       Date:  2020-07-13       Impact factor: 5.849

5.  A-phase classification using convolutional neural networks.

Authors:  Edgar R Arce-Santana; Alfonso Alba; Martin O Mendez; Valdemar Arce-Guevara
Journal:  Med Biol Eng Comput       Date:  2020-03-02       Impact factor: 2.602

6.  Deep learning in the cross-time frequency domain for sleep staging from a single-lead electrocardiogram.

Authors:  Qiao Li; Qichen Li; Chengyu Liu; Supreeth P Shashikumar; Shamim Nemati; Gari D Clifford
Journal:  Physiol Meas       Date:  2018-12-21       Impact factor: 2.833

7.  Acute dopamine-agonist treatment in restless legs syndrome: effects on sleep architecture and NREM sleep instability.

Authors:  Raffaele Ferri; Mauro Manconi; Debora Aricò; Carolina Sagrada; Marco Zucconi; Oliviero Bruni; Alessandro Oldani; Luigi Ferini-Strambi
Journal:  Sleep       Date:  2010-06       Impact factor: 5.849

8.  Sleep cyclic alternating pattern in otherwise healthy overweight school-age children.

Authors:  Rodrigo Chamorro; Raffaele Ferri; Cecilia Algarín; Marcelo Garrido; Betsy Lozoff; Patricio Peirano
Journal:  Sleep       Date:  2014-03-01       Impact factor: 5.849

9.  Cyclic alternating pattern in children with obstructive sleep apnea and its relationship with adenotonsillectomy, behavior, cognition, and quality of life.

Authors:  Simon Hartmann; Oliviero Bruni; Raffaele Ferri; Susan Redline; Mathias Baumert
Journal:  Sleep       Date:  2021-01-21       Impact factor: 5.849

10.  Type 2 diabetes and pre-diabetes are associated with obstructive sleep apnea in extremely obese subjects: a cross-sectional study.

Authors:  Jan Magnus Fredheim; Jan Rollheim; Torbjørn Omland; Dag Hofsø; Jo Røislien; Kristian Vegsgaard; Jøran Hjelmesæth
Journal:  Cardiovasc Diabetol       Date:  2011-09-25       Impact factor: 9.951

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