ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2016
Minimizing Interrater Variability in Staging Sleep by Use of Computer-Derived Features.
Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 26 citations in OpenAlex.
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- A Clinical Decision Support System for Sleep Staging Tasks With Explanations From Artificial Intelligence: User-Centered Design and Evaluation Study.Journal of medical Internet research · 2022Article
- Computer-assisted analysis of polysomnographic recordings improves inter-scorer associated agreement and scoring times.PloS one · 2022Article
- Maturational trajectories of non-rapid eye movement slow wave activity and odds ratio product in a population-based sample of youth.Sleep medicine · 2021Article
- Interrater sleep stage scoring reliability between manual scoring from two European sleep centers and automatic scoring performed by the artificial intelligence-based Stanford-STAGES algorithm.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2021Article
- Automatic analysis of single-channel sleep EEG in a large spectrum of sleep disorders.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2021Article
- Noninvasive three-state sleep-wake staging in mice using electric field sensors.Journal of neuroscience methods · 2020Article
- Artificial intelligence in sleep medicine: background and implications for clinicians.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2020Article
- Reliability of the American Academy of Sleep Medicine Rules for Assessing Sleep Depth in Clinical Practice.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2018Article
- Large-Scale Automated Sleep Staging.Sleep · 2017Article
- The Accuracy, Night-to-Night Variability, and Stability of Frontopolar Sleep Electroencephalography Biomarkers.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2017Article
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2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
STUDY
objectivesInter-scorer variability in sleep staging of polysomnograms (PSGs) results primarily from difficulty in determining whether: (1) an electroencephalogram pattern of wakefulness spans > 15 sec in transitional epochs, (2) spindles or K complexes are present, and (3) duration of delta waves exceeds 6 sec in a 30-sec epoch. We hypothesized that providing digitally derived information about these variables to PSG scorers may reduce inter-scorer variability.
methodsFifty-six PSGs were scored (five-stage) by two experienced technologists, (first manual, M1). Months later, the technologists edited their own scoring (second manual, M2). PSGs were then scored with an automatic system and the same two technologists and an additional experienced technologist edited them, epoch-by-epoch (Edited-Auto). This resulted in seven manual scores for each PSG. The two M2 scores were then independently modified using digitally obtained values for sleep depth and delta duration and digitally identified spindles and K complexes.
resultsPercent agreement between scorers in M2 was 78.9 ± 9.0% before modification and 96.5 ± 2.6% after. Errors of this approach were defined as a change in a manual score to a stage that was not assigned by any scorer during the seven manual scoring sessions. Total errors averaged 7.1 ± 3.7% and 6.9 ± 3.8% of epochs for scorers 1 and 2, respectively, and there was excellent agreement between the modified score and the initial manual score of each technologist.
conclusionsProviding digitally obtained information about sleep depth, delta duration, spindles and K complexes during manual scoring can greatly reduce interrater variability in sleep staging by eliminating the guesswork in scoring epochs with equivocal features.
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