Evidence map›Paper›PMID 40958425›Full record

ArticleBrain and behavior2025

How Neurologists Combine Clinical Signs and Subjective Factors to Diagnose Epileptic and Functional Seizures: Insights From Seizure Video Analysis.

Subramanian Muthusamy, Udaya Seneviratne, Henry Ma, Thanh G Phan

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Article in Brain and behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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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

4 authors.

Subramanian MuthusamySchool of Clinical Sciences at Monash Health, Department of Medicine, Monash University, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0002-1975-9362
Udaya SeneviratneSchool of Clinical Sciences at Monash Health, Department of Medicine, Monash University, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0003-0182-9702
Henry MaSchool of Clinical Sciences at Monash Health, Department of Medicine, Monash University, Melbourne, Victoria, Australia.
Thanh G PhanSchool of Clinical Sciences at Monash Health, Department of Medicine, Monash University, Melbourne, Victoria, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEvaluating seizure semiology is crucial for distinguishing functional seizures (FS) from epileptic seizures (ES). This study examines how neurologists integrate clinical signs, observations, and subjective factors in making this distinction.

methodsNeurologists at Monash Health assessed unlabeled seizure videos on a web-based platform, providing free-text descriptions, selecting observed clinical signs, offering diagnoses, and rating their certainty (0-100). Non-negative matrix factorization (NMF) clustered clinical signs, and thematic analysis was performed on free-text responses. Logistic regression evaluated how single signs, sign combinations, and rater consensus influenced diagnostic alignment. Model performance was assessed using area under the receiver operating characteristic curve (AUC).

resultsNMF identified two sign clusters: one associated with FS (eye closure, asynchronous limb jerking, headshaking, pelvic thrusting) and another with ES (eyes open, head version, tonic/dystonic posturing, automatisms, synchronous limb jerking). Diagnostic alignment was influenced by clinical sign combinations (OR = 1.37, 95% CI = 1.15-1.64, p < 0.001) and rater consensus (OR = 1.40, 95% CI = 1.15-1.77, p = 0.002). Models incorporating these factors incrementally improved performance, with the final model achieving an AUC of 0.88 (95% CI: 0.84-0.92, McFadden's R

conclusionNeurologists rely on distinct clinical sign patterns and subjective factors to differentiate FS from ES. Understanding these decision-making processes can improve diagnostic workflows and training programs.

Indexed as

EpilepsyNeurologistsSeizuresAdultDiagnosis, DifferentialFemaleHumansMaleMiddle AgedVideo Recordingdiagnosisepileptic seizurefunctional seizure

Identifiers

PMID40958425
PMCPMC12441005

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