KMID : 0361020210640030169
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Korean Journal of Otolaryngology - Head and Neck Surgery 2021 Volume.64 No. 3 p.169 ~ p.175
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Performance of an Automated Polysomnography Scoring Using Noxturnal Program versus Manual Scoring
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Jeong Su-Jeong
Seong Jong-Yuap Kim Ji-Su Park Jong-Min Sung Chung-Man Yang Hyung-Chae Lim Sang-Chul
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Abstract
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Background and Objectives : A lack of investigators for polysomnography has risen due toincreased demand since health insurance started to cover the cost of the test. We examined thereliability of the automated scoring of polysomnography, which has been deployed to improvethis imbalance.
Subjects and Method : We analyzed the data of 20 patients who underwent level 1 polysomnographyfrom April 1 to July 27, 2019. The software from Noxturnal (Nox Medical) was usedfor the scoring of the Polysomnography data. Each of the polysomnographic data was scoredboth by the automated scoring system and by a skilled technician.
Results : Twenty patients were analyzed. There was no significant difference between automatedscoring and manual scoring in sleep latency, apnea index, and rapid eye movementsleep stage ratio. However, the concordance rate of the sleep stage by epoch was 83.32%, andthere was a significant difference with regards to apnea-hypoapnea index (AHI) and respiratorydisturbance index (RDI). Two obvious errors were noted in the automated scoring that couldbe easily fixed; the failure to recognize wakefulness during sleep and the fragmentation of respiratoryevents. When two errors were corrected, many differences in polysomnography parameters,including AHI and RDI, were eliminated.
Conclusion : It showed 80% coincidence of epoch in the sleep stage between the automatedscoring and manual scoring. However, there was no difference in AHI and RDI when the fragmentedrespiratory events of the automated scoring were adjusted. Therefore, automated scoringis considered to be useful if only a little modification could be made.
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KEYWORD
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Artificial intelligence, Economics, Obstructive sleep apneas, Polysomnographies, Sleep monitoring
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