ArticleJournal of clinical neurophysiology : official publication of the American Electroencephalographic Society2019
Interrater and Intrarater Agreement in Neonatal Electroencephalogram Background Scoring.
Article in Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Unveiling variability: A systematic review of reproducibility in visual EEG analysis, with focus on seizures.Epileptic disorders : international epilepsy journal with videotape · 2024Pooled it
- Observational
- Detection of neurologic changes in critically ill infants using deep learning on video data: a retrospective single center cohort study.EClinicalMedicine · 2024Article
- Accurate prediction of neurologic changes in critically ill infants using pose AI.medRxiv : the preprint server for health sciences · 2024Article
- Comparison of Machine and Human Expert Evaluation of Capsulorrhexis Creation Performance Through Analysis of Surgical Video Recordings.Clinical ophthalmology (Auckland, N.Z.) · 2024Article
- [A preliminary study on a new method for evaluating brain maturation in preterm infants].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2023Article
- Neuromonitoring in neonatal critical care part I: neonatal encephalopathy and neonates with possible seizures.Pediatric research · 2023Review
- [A novel method for electroencephalography background analysis in neonates with hypoxic-ischemic encephalopathy].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2023Article
- Article
- Intelligent wearable allows out-of-the-lab tracking of developing motor abilities in infants.Communications medicine · 2022Article
- Building an Open Source Classifier for the Neonatal EEG Background: A Systematic Feature-Based Approach From Expert Scoring to Clinical Visualization.Frontiers in human neuroscience · 2021Article
- Perspectives from the Society for Pediatric Research. Neonatal encephalopathy clinical trials: developing the future.Pediatric research · 2021Review
- Reliability and accuracy of EEG interpretation for estimating age in preterm infants.Annals of clinical and translational neurology · 2020Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
purposeMany neonates undergo electroencephalogram (EEG) monitoring to identify and manage acute symptomatic seizures. Information about brain function contained in the EEG background data may also help predict neurobehavioral outcomes. For EEG background features to be useful as prognostic indicators, the interpretation of these features must be standardized across electroencephalographers. We aimed at determining the interrater and intrarater agreement among electroencephalographers interpreting neonatal EEG background patterns.
methodsFive neonatal electroencephalographers reviewed 5-to-7.5-minute epochs of EEG from full-term neonates who underwent continuous conventional EEG monitoring. The EEG assessment tool used to classify background patterns was based on the American Clinical Neurophysiology Society's guideline for neonatal EEG terminology. Interrater and intrarater agreement were measured using Kappa coefficients.
resultsInterrater agreement was consistently highest for voltage (binary: substantial, kappa = 0.783; categorical: moderate, kappa = 0.562), seizure presence (fair-substantial; kappa = 0.375-0.697), continuity (moderate; kappa = 0.481), burst voltage (moderate; kappa = 0.574), suppressed background presence (moderate-substantial; kappa = 0.493-0.643), delta activity presence (fair-moderate; kappa = 0.369-0.432), theta activity presence (fair-moderate; kappa = 0.347-0.600), presence of graphoelements (fair; kappa = 0.381), and overall impression (binary: moderate, kappa = 0.495; categorical: fair-moderate, kappa = 0.347, 0.465). Agreement was poor or inconsistent for all other patterns. Intrarater agreement was variable, with highest average agreement for voltage (binary: substantial, kappa = 0.75; categorical: substantial, kappa = 0.714) and highest consistent agreement for continuity (moderate-substantial; kappa = 0.43-0.67) and overall impression (moderate-substantial; kappa = 0.42-0.68).
conclusionsThis study demonstrates substantial variability in neonatal EEG background interpretation across electroencephalographers, indicating a need for educational and technological strategies aimed at improving performance.
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