Proof of principle study: diagnostic accuracy of a novel algorithm for the estimation of sleep stages and disease severity in patients with sleep-disordered breathing based on actigraphy and respiratory inductance plethysmography
PURPOSE: In this proof of principle study, we evaluated the diagnostic accuracy of the novel Nox BodySleep(TM) 1.0 algorithm (Nox Medical, Iceland) for the estimation of disease severity and sleep stages based on features extracted from actigraphy and respiratory inductance plethysmography (RIP) bel...
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Online Access: | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590674/ http://www.ncbi.nlm.nih.gov/pubmed/33594617 https://doi.org/10.1007/s11325-021-02316-0 |
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ftpubmed:oai:pubmedcentral.nih.gov:8590674 2023-05-15T16:52:06+02:00 Proof of principle study: diagnostic accuracy of a novel algorithm for the estimation of sleep stages and disease severity in patients with sleep-disordered breathing based on actigraphy and respiratory inductance plethysmography Dietz-Terjung, Sarah Martin, Amelie Ricarda Finnsson, Eysteinn Ágústsson, Jón Skínir Helgason, Snorri Helgadóttir, Halla Welsner, Matthias Taube, Christian Weinreich, Gerhard Schöbel, Christoph 2021-02-16 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590674/ http://www.ncbi.nlm.nih.gov/pubmed/33594617 https://doi.org/10.1007/s11325-021-02316-0 en eng Springer International Publishing http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590674/ http://www.ncbi.nlm.nih.gov/pubmed/33594617 http://dx.doi.org/10.1007/s11325-021-02316-0 © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . CC-BY Sleep Breath Sleep Breathing Physiology and Disorders • Original Article Text 2021 ftpubmed https://doi.org/10.1007/s11325-021-02316-0 2021-11-28T01:26:30Z PURPOSE: In this proof of principle study, we evaluated the diagnostic accuracy of the novel Nox BodySleep(TM) 1.0 algorithm (Nox Medical, Iceland) for the estimation of disease severity and sleep stages based on features extracted from actigraphy and respiratory inductance plethysmography (RIP) belts. Validation was performed against in-lab polysomnography (PSG) in patients with sleep-disordered breathing (SDB). METHODS: Patients received PSG according to AASM. Sleep stages were manually scored using the AASM criteria and the recording was evaluated by the novel algorithm. The results were analyzed by descriptive statistics methods (IBM SPSS Statistics 25.0). RESULTS: We found a strong Pearson correlation (r=0.91) with a bias of 0.2/h for AHI estimation as well as a good correlation (r=0.81) and an overestimation of 14 min for total sleep time (TST). Sleep efficiency (SE) was also valued with a good Pearson correlation (r=0.73) and an overestimation of 2.1%. Wake epochs were estimated with a sensitivity of 0.65 and a specificity of 0.59 while REM and non-REM (NREM) phases were evaluated a sensitivity of 0.72 and 0.74, respectively. Specificity was 0.74 for NREM and 0.68 for REM. Additionally, a Cohen’s kappa of 0.62 was found for this 3-class classification problem. CONCLUSION: The algorithm shows a moderate diagnostic accuracy for the estimation of sleep. In addition, the algorithm determines the AHI with good agreement with the manual scoring and it shows good diagnostic accuracy in estimating wake-sleep transition. The presented algorithm seems to be an appropriate tool to increase the diagnostic accuracy of portable monitoring. The validated diagnostic algorithm promises a more appropriate and cost-effective method if integrated in out-of-center (OOC) testing of patients with suspicion for SDB. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11325-021-02316-0. Text Iceland PubMed Central (PMC) Rip ENVELOPE(-19.509,-19.509,65.690,65.690) Sleep and Breathing 25 4 1945 1952 |
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PubMed Central (PMC) |
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Sleep Breathing Physiology and Disorders • Original Article |
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Sleep Breathing Physiology and Disorders • Original Article Dietz-Terjung, Sarah Martin, Amelie Ricarda Finnsson, Eysteinn Ágústsson, Jón Skínir Helgason, Snorri Helgadóttir, Halla Welsner, Matthias Taube, Christian Weinreich, Gerhard Schöbel, Christoph Proof of principle study: diagnostic accuracy of a novel algorithm for the estimation of sleep stages and disease severity in patients with sleep-disordered breathing based on actigraphy and respiratory inductance plethysmography |
topic_facet |
Sleep Breathing Physiology and Disorders • Original Article |
description |
PURPOSE: In this proof of principle study, we evaluated the diagnostic accuracy of the novel Nox BodySleep(TM) 1.0 algorithm (Nox Medical, Iceland) for the estimation of disease severity and sleep stages based on features extracted from actigraphy and respiratory inductance plethysmography (RIP) belts. Validation was performed against in-lab polysomnography (PSG) in patients with sleep-disordered breathing (SDB). METHODS: Patients received PSG according to AASM. Sleep stages were manually scored using the AASM criteria and the recording was evaluated by the novel algorithm. The results were analyzed by descriptive statistics methods (IBM SPSS Statistics 25.0). RESULTS: We found a strong Pearson correlation (r=0.91) with a bias of 0.2/h for AHI estimation as well as a good correlation (r=0.81) and an overestimation of 14 min for total sleep time (TST). Sleep efficiency (SE) was also valued with a good Pearson correlation (r=0.73) and an overestimation of 2.1%. Wake epochs were estimated with a sensitivity of 0.65 and a specificity of 0.59 while REM and non-REM (NREM) phases were evaluated a sensitivity of 0.72 and 0.74, respectively. Specificity was 0.74 for NREM and 0.68 for REM. Additionally, a Cohen’s kappa of 0.62 was found for this 3-class classification problem. CONCLUSION: The algorithm shows a moderate diagnostic accuracy for the estimation of sleep. In addition, the algorithm determines the AHI with good agreement with the manual scoring and it shows good diagnostic accuracy in estimating wake-sleep transition. The presented algorithm seems to be an appropriate tool to increase the diagnostic accuracy of portable monitoring. The validated diagnostic algorithm promises a more appropriate and cost-effective method if integrated in out-of-center (OOC) testing of patients with suspicion for SDB. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11325-021-02316-0. |
format |
Text |
author |
Dietz-Terjung, Sarah Martin, Amelie Ricarda Finnsson, Eysteinn Ágústsson, Jón Skínir Helgason, Snorri Helgadóttir, Halla Welsner, Matthias Taube, Christian Weinreich, Gerhard Schöbel, Christoph |
author_facet |
Dietz-Terjung, Sarah Martin, Amelie Ricarda Finnsson, Eysteinn Ágústsson, Jón Skínir Helgason, Snorri Helgadóttir, Halla Welsner, Matthias Taube, Christian Weinreich, Gerhard Schöbel, Christoph |
author_sort |
Dietz-Terjung, Sarah |
title |
Proof of principle study: diagnostic accuracy of a novel algorithm for the estimation of sleep stages and disease severity in patients with sleep-disordered breathing based on actigraphy and respiratory inductance plethysmography |
title_short |
Proof of principle study: diagnostic accuracy of a novel algorithm for the estimation of sleep stages and disease severity in patients with sleep-disordered breathing based on actigraphy and respiratory inductance plethysmography |
title_full |
Proof of principle study: diagnostic accuracy of a novel algorithm for the estimation of sleep stages and disease severity in patients with sleep-disordered breathing based on actigraphy and respiratory inductance plethysmography |
title_fullStr |
Proof of principle study: diagnostic accuracy of a novel algorithm for the estimation of sleep stages and disease severity in patients with sleep-disordered breathing based on actigraphy and respiratory inductance plethysmography |
title_full_unstemmed |
Proof of principle study: diagnostic accuracy of a novel algorithm for the estimation of sleep stages and disease severity in patients with sleep-disordered breathing based on actigraphy and respiratory inductance plethysmography |
title_sort |
proof of principle study: diagnostic accuracy of a novel algorithm for the estimation of sleep stages and disease severity in patients with sleep-disordered breathing based on actigraphy and respiratory inductance plethysmography |
publisher |
Springer International Publishing |
publishDate |
2021 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590674/ http://www.ncbi.nlm.nih.gov/pubmed/33594617 https://doi.org/10.1007/s11325-021-02316-0 |
long_lat |
ENVELOPE(-19.509,-19.509,65.690,65.690) |
geographic |
Rip |
geographic_facet |
Rip |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
Sleep Breath |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590674/ http://www.ncbi.nlm.nih.gov/pubmed/33594617 http://dx.doi.org/10.1007/s11325-021-02316-0 |
op_rights |
© The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1007/s11325-021-02316-0 |
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