Timo Leppänen

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Recent Grants

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Revolution of sleep diagnostics and personalized health care based on digital diagnostics and therapeutics with health data integration

Open Date: 2021-03-01

Close Date: 2025-02-01

Grant: Close

Deep learning and physiology based approach to derive and link obstructive sleep apnoea phenotypes ans symptomatology

Open Date: 2021-01-01

Close Date: 2023-12-01

Grant: Close

Novel Polysomnogram Derived Endotypes and Phenotypes of Sleep Apnea Provide New Insight to Explain Daytime Sleepiness and Lowered Daytime Vigilance

Open Date: 2020-04-01

Close Date: 2021-07-01

Grant: Close

Novel Polysomnogram Derived Endotypes and Phenotypes of Sleep Apnea Provide New Insight to Explain Daytime Sleepiness and Lowered Daytime Vigilance

Open Date: 2020-04-01

Close Date: 2024-12-01

Grant: Close

New Enhanced and Individualized Diagnostic Paradigm for Obstructive Sleep Apnea

Open Date: 2019-09-01

Close Date: 2022-08-01

Articles (11)

Summary Determining sleep stages accurately is an important part of the diagnostic process for numerous sleep disorders. However, as the sleep stage scoring is done manually following visual scoring rules there can be considerable variation in the sleep staging between different scorers. Thus, this study aimed to comprehensively evaluate the inter‐rater agreement in sleep staging. A total of 50 polysomnography recordings were manually scored by 10 independent scorers from seven different sleep centres. We used the 10 scorings to calculate a majority score by taking the sleep stage that was the most scored stage for each epoch. The overall agreement for sleep staging was κ = 0.71 and the mean agreement with the majority score was 0.86. The scorers were in perfect agreement in 48% of all scored epochs. The agreement was highest in rapid eye movement sleep ( κ = 0.86) and lowest in N1 sleep ( κ = 0.41). The agreement with the majority scoring varied between the scorers from 81% to 91%, with large variations between the scorers in sleep stage‐specific agreements. Scorers from the same sleep centres had the highest pairwise agreements at κ = 0.79, κ = 0.85, and κ = 0.78, while the lowest pairwise agreement between the scorers was κ = 0.58. We also found a moderate negative correlation between sleep staging agreement and the apnea–hypopnea index, as well as the rate of sleep stage transitions. In conclusion, although the overall agreement was high, several areas of low agreement were also found, mainly between non‐rapid eye movement stages.

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2023

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2023

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2022

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2021

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2021

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2021

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2021

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2021

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2021

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2021

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2021

Collaborators (5)

Diego R. Mazzotti, Ph.D.

Assistant Professor, Medical Informatics

University of Kansas Medical Center

UNITED STATES
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Samu Kainulainen

University of Eastern Finland

FINLAND
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Sami Nikkonen

Kuopio University Hospital

FINLAND
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Henri Korkalainen

-

FINLAND
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Tuomas Karhu

Kuopio University Hospital

FINLAND
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