Evidence map›Paper›PMID 37811900›Full record

ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2024

Polysomnography scoring-related training and quantitative assessment for improving interscorer agreement.

Ying-Siou Liao, Meng-Chun Wu, Cheng-Xue Li, Wen-Kuei Lin, Cheng-Yu Lin, Sheng-Fu Liang

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Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ying-Siou LiaoDepartment of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan.
Meng-Chun WuDepartment of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan.
Cheng-Xue LiDepartment of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan.
Wen-Kuei LinSleep Medicine Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Cheng-Yu LinSleep Medicine Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Sheng-Fu LiangDepartment of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

objectivesTo efficiently improve the scoring competency of scorers with varying levels of experience across regions in Taiwan, we developed a training program with a cloud-based polysomnography scoring platform to evaluate and improve interscorer agreement.

methodsA total of 70 scorers from 34 sleep centers in Taiwan (job tenure: 0.5-39.0 years) completed a scoring test. All scorers scored a 742-epoch (30 s/epoch) overnight polysomnography recording of a patient with a moderate apnea-hypopnea index. Subsequently, 8 scoring experts delivered 8 interactive online lectures (each lasting 30 minutes). The training program included identifying scoring weaknesses, highlighting the latest scoring rules, and providing physicians' perspectives. Afterward, the scorers completed the second scoring test on the same participant. Changes in agreement from the first to second scoring test were identified. Sleep staging, sleep parameters, and respiratory events were considered for evaluating scoring agreement.

resultsThe scorers' agreement in overall sleep stage scoring significantly increased from 74.6 to 82.3% (median score). The proportion of scorers with an agreement of ≥ 80% increased from 20.0% (14/70) to 58.6% (41/70) after the online training program. In addition, the scorers' agreement in overall respiratory-event scoring increased to 88.8% (median score) after training. The scorers with a job tenure of 2.0-4.9 years exhibited the highest level of improvement in overall sleep staging (their median agreement increased from 72.8 to 84.9%;

conclusionsOur interactive online training program efficiently targeted the scorers' scoring weaknesses identified in the first scoring test, leading to substantial improvements in scoring proficiency. CITATION: Liao Y-S, Wu M-C, Li C-X, Lin W-K, Lin C-Y, Liang S-F. Polysomnography scoring-related training and quantitative assessment for improving interscorer agreement.

Indexed as

SleepSleep Apnea SyndromesHumansObserver VariationPolysomnographyReproducibility of ResultsSleep Stagesagreementassessmentcloud-based platformcompetencyenhancementonline tutorialovernight polysomnographyremote assistant training

Identifiers

PMID37811900
PMCPMC10835767

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.