dc.date.accessioned | 2021-02-03T20:53:35Z | |
dc.date.available | 2021-02-03T20:53:35Z | |
dc.date.created | 2021-01-20T16:23:57Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Kristiansen, Stein Traaen, Gunn Marit Øverland, Britt Plagemann, Thomas Peter Gullestad, Lars Akre, Harriet Nikolaidis, Konstantinos Aakerøy, Lars Hunt, Tove Elizabeth Frances Loennechen, Jan Pål Steinshamn, Sigurd Loe Bendz, Christina Anfinsen, Ole-Gunnar Goebel, Vera Hermine . Comparing manual and automatic scoring of sleep monitoring data from portable polygraphy. Journal of Sleep Research. 2020 | |
dc.identifier.uri | http://hdl.handle.net/10852/82872 | |
dc.description.abstract | We used sleep monitoring data from a study that investigated the prevalence, characteristics, risk factors and type of sleep apnea (SA) in 579 patients with paroxysmal atrial fibrillation. Most patients were screened for two nights, resulting in 1,043 sleep recordings that each contained data from one night. SA was diagnosed using the Nox T3 portable sleep monitor. An experienced sleep specialist scored the recordings manually using Noxturnal software. A total of 157 women (27%) and 422 men (73%) were examined; 477 (82.7%) had an apnea–hypopnea index (AHI) ≥ 5/hr, whereas moderate to severe SA (AHI ≥ 15/hr) was diagnosed in 243 patients (42.1%). The AHI derived from automatic and manual scoring showed a good agreement (Pearson's r coefficient of 0.96). The median difference in AHI was very small (i.e., 0.72 [mean difference, 1.06]), but was statistically significant (p < .0001). Automatic scoring classified sleep recordings with more than 90% accuracy into SA categories of mild (AHI ≥ 5/hr), moderate (AHI ≥ 15/hr) and severe (AHI ≥ 30/hr). We found a minor (11%–21%) mis‐estimation of the number of recordings right above and below the boundary separating mild and moderate SA. The accuracy of automatic scoring differed from recording to recording, especially regarding the sensitivity of detecting disrupted breathing events. We found low to moderate agreement for the duration of disrupted breathing events (r = .53), for which the automatic scoring led to a statistically significant overestimation by 5.22 s (p < .0001). | |
dc.language | EN | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.title | Comparing manual and automatic scoring of sleep monitoring data from portable polygraphy | |
dc.type | Journal article | |
dc.creator.author | Kristiansen, Stein | |
dc.creator.author | Traaen, Gunn Marit | |
dc.creator.author | Øverland, Britt | |
dc.creator.author | Plagemann, Thomas Peter | |
dc.creator.author | Gullestad, Lars | |
dc.creator.author | Akre, Harriet | |
dc.creator.author | Nikolaidis, Konstantinos | |
dc.creator.author | Aakerøy, Lars | |
dc.creator.author | Hunt, Tove Elizabeth Frances | |
dc.creator.author | Loennechen, Jan Pål | |
dc.creator.author | Steinshamn, Sigurd Loe | |
dc.creator.author | Bendz, Christina | |
dc.creator.author | Anfinsen, Ole-Gunnar | |
dc.creator.author | Goebel, Vera Hermine | |
cristin.unitcode | 185,15,5,75 | |
cristin.unitname | DIS Digital infrastruktur og sikkerhet | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |
dc.identifier.cristin | 1875828 | |
dc.identifier.bibliographiccitation | info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal of Sleep Research&rft.volume=&rft.spage=&rft.date=2020 | |
dc.identifier.jtitle | Journal of Sleep Research | |
dc.identifier.doi | https://doi.org/10.1111/jsr.13036 | |
dc.identifier.urn | URN:NBN:no-85679 | |
dc.type.document | Tidsskriftartikkel | |
dc.type.peerreviewed | Peer reviewed | |
dc.source.issn | 0962-1105 | |
dc.identifier.fulltext | Fulltext https://www.duo.uio.no/bitstream/handle/10852/82872/4/jsr.13036.pdf | |
dc.type.version | PublishedVersion | |
cristin.articleid | e13036 | |