Evidence map›Paper›PMID 40117757›Full record

ArticleClinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology2025

Utility of the IFCN criteria for identifying interictal epileptiform discharges by experts: A decision hygiene approach to improve inter-rater reliability.

Doyle Yuan, Roohi Katyal, Irfan Sheikh, Ioannis Karakis, Selim Benbadis, Ushtar Amin, Kollencheri Puthenveettil Vinayan, Niravkumar Barot, Dan Weber, Adam Greenblatt and 3 more

Abstract read
In one paragraph

Article in Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Doyle YuanDepartment of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA. Electronic address: doyle.yuan@utsouthwestern.edu.
Roohi KatyalDepartment of Neurology, Louisiana State University Health Sciences Center, Shreveport, LA, USA.
Irfan SheikhDepartment of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Ioannis KarakisDepartment of Neurology, Emory University School of Medicine, Atlanta, GA, USA; University of Crete School of Medicine, Heraklion, Greece.
Selim BenbadisDepartment of Neurology, University of South Florida, Tampa, FL, USA.
Ushtar AminDepartment of Neurology, University of South Florida, Tampa, FL, USA.
Kollencheri Puthenveettil VinayanDepartment of Pediatric Neurology and Amrita Advanced Center for Epilepsy, Amrita Institute of Medical Sciences, Cochin, Kerala, India.
Niravkumar BarotDepartment of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Dan WeberDepartment of Neurology, Saint Louis University, Saint Louis, MO, USA.
Adam GreenblattDepartment of Neurology, Washington University in St. Louis, St. Louis, MO, USA.
Sándor BeniczkyAarhus University, Danish Epilepsy Center and Aarhus University Hospital, Denmark.
M Brandon WestoverDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Fábio A NascimentoDepartment of Neurology, Washington University in St. Louis, St. Louis, MO, USA.

Funding

Late-onset Unexplained Epilepsy as a Risk Factor for DementiaR01NS130119 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Alice D Lam · 2023 to 2026
$8.7M
Data-Driven Sleep Biomarkers of Brain Health, Heart Health, and MortalityR01HL161253 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI CLIFFORD, GARI DAVID, MIGNOT, EMMANUEL J · 2022 to 2025
$8.3M
Prospective Validation of Neurophysiologic Outcome Prediction in Acute Brain InjuryR01NS126282 · NINDS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI Aaron F Struck, Michael Brandon Westover · 2023 to 2026
$2.9M
Establishing a Brain Health Index from the Sleep ElectroencephalogramRF1NS120947 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI CASH, SYDNEY S, THOMAS, ROBERT JOSEPH · 2021 to 2021
$2.4M
Establishing a Brain Health IndexR01NS120947 · NINDS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI CASH, SYDNEY S, THOMAS, ROBERT JOSEPH · 2024 to 2025
$1.6M
NHLBI NIH HHS R01 HL161253NINDS NIH HHS R01 NS120947NINDS NIH HHS R01 NS126282NINDS NIH HHS R01 NS130119NINDS NIH HHS RF1 NS120947
6 · The paper itself

Abstract

objectiveTo determine if implementing the IFCN criteria to define interictal epileptiform discharges (IEDs) improves expert inter-rater reliability (IRR) and diagnostic performance.

methodsNine EEG experts rated the same 200 candidate IEDs (100 expert-consensus, 100 epilepsy monitoring unit [EMU]-validated) as epileptiform or not, in random order, in two rounds separated by at least 30 days. During the second round, raters additionally selected the applicable IFCN criteria for each candidate IED.

resultsOverall, there were no major differences in performance (AUC; 0.90 vs. 0.91) or IRR (AC1; 0.48 vs. 0.47) between both Parts; nor was there a major difference in calibration within the expert-consensus dataset (median absolute calibration index; 35.5 vs. 30.0). Similarly, there were no major differences in performance or IRR within either dataset. IRR was substantial within the EMU-validated dataset and only fair within the expert-consensus dataset. IRR was fair for criteria 2, 3, 5 and 6, and moderate for criteria 1 and 4.

conclusionsOur findings suggest that the IFCN criteria to define IEDs may not significantly improve IRR, performance, or overall calibration among experts. SIGNIFICANCE: Increasing expert IRR for each criterion may enhance the utility of the IFCN criteria in clinical practice.

Indexed as

ElectroencephalographyEpilepsyAdultFemaleHumansMaleObserver VariationReproducibility of ResultsDecision hygieneEEGIFCN criteriaInter-rater reliability

Identifiers

PMID40117757
PMCPMC12335889

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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.