HELSENORGE

Sammenligning av manuell og automatisk scoring av polygrafidata (Nox T3)

Forskere fra Universitetet i Oslo, Rikshospitalet, Lovisenberg diakonale sykehus, St. Olavs hospital og NTNU har i denne studien undersøkt prevalens, egenskaper, risikofaktorer og type søvnapné (SA) blant 579 pasienter (144 kvinner/422 menn) med paroksysmal atrieflimmer. De fleste pasientene ble screenet i to netter, noe som resulterte i 1 043 søvnregistreringer som hver inneholder data fra en natt. Søvnapné ble diagnostisert ved bruk av bærbar Nox T3, og manuell skåring ble gjort av en erfaren søvnspesialist. Resultatene i studien viste relativt godt samsvar av AHI skåret både automatisk og manuelt.




Stein Kristiansen, Gunn Marit Traaen, Britt Øverland, Thomas Plagemann, Lars Gullestad, Harriet Akre, Konstantinos Nikolaidis, Lars Aakerøy, Tove E Hunt, Jan Pål Loennechen, Sigurd Steinshamn, Christina Bendz, Ole-Gunnar Anfinsen, Vera Goebel

Studien er publisert i Journal of Sleep Resarch

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).