Evidence map›Paper›PMID 40749302›Full record

SynthesisSchizophrenia research2025

The role of the electroencephalogram (EEG) in determining the aetiology of psychosis: a systematic review and meta-analysis of diagnostic test accuracy.

Jack B Fanshawe, Rosie Lawrence, Dory A Ghanem, Lucy Pauli, Rebecca Whincup, Emma Salter, Brendan F Sargent, Lauren Evans, Iman Jasani, Dominic Oliver and 7 more

Abstract readSystematic ReviewMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Schizophrenia research, 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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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

17 authors.

Jack B FanshaweDepartment of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK. Electronic address: jack.fanshawe@conted.ox.ac.uk.
Rosie LawrenceDivision of Psychiatry, University College London, London, UK.
Dory A GhanemMedical School, University College London, London, UK.
Lucy PauliSheffield Health and Social Care NHS Foundation Trust, UK.
Rebecca WhincupLeicestershire Partnership NHS Trust, Leicester, UK.
Emma SalterOxford Health NHS Foundation Trust, Oxford, UK.
Brendan F SargentDepartment of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK.
Lauren EvansDivision of Psychiatry, University College London, London, UK.
Iman JasaniSouth London and Maudsley NHS Trust, London, UK.
Dominic OliverDepartment of Psychiatry, University of Oxford, Oxford, UK.
Joseph HutchinsonDepartment of Clinical Neurophysiology, The National Hospital for Neurology and Neurosurgery, London, UK.
Steven WhiteDepartment of Clinical Neurophysiology, The National Hospital for Neurology and Neurosurgery, London, UK.
Ben CarterDepartment of Biostatistics and Health Informatics, King's College London, London, UK.
Anthony S DavidDivision of Psychiatry, University College London, London, UK.
Glyn LewisDivision of Psychiatry, University College London, London, UK.
Michael S ZandiNational Hospital for Neurology and Neurosurgery, London, UK; Queen Square Institute of Neurology, University College London, London, UK.
Jonathan P RogersDivision of Psychiatry, University College London, London, UK; Department of Neuropsychiatry, National Hospital for Neurology and Neurosurgery, London, UK.

Funding

Wellcome Trust 220659
6 · The paper itself

Abstract

backgroundPsychosis is a transdiagnostic condition which can manifest as part of many disorders including those of primary psychiatric origin, or secondary to a medical condition. This study aims to systematically review and quantify the diagnostic accuracy of electroencephalography (EEG) in identifying people with psychosis secondary to a medical condition.

methodsA comprehensive search strategy was implemented across multiple databases. Inclusion criteria specified observational human studies with a minimum of 20 participants experiencing psychosis who underwent EEG. The reference standard was the final clinical diagnosis. Two reviewers independently assessed article inclusion using predefined eligibility criteria. Data were extracted by two blinded reviewers. A bivariate meta-analysis was conducted to model the correlation between sensitivity and specificity.

findingsThe search strategy yielded 8688 results, of which 38 were eligible. The main diagnostic test accuracy meta-analysis found that the sensitivity (i.e., the proportion of patients with secondary psychosis who had an abnormal EEG) was 0·71 (95 % CI 0·61-0·80) and the specificity (i.e., the proportion of patients with primary psychosis who had a normal EEG) was 0·67 (95 % CI 0·58-0·74). The area under the receiver operating characteristics curve was 0·67, corresponding to poor discrimination. The pattern for each of the specific EEG abnormalities was a low-moderate sensitivity and high specificity.

interpretationEEG demonstrates poor discrimination in identifying a secondary psychosis. Specific EEG abnormalities exhibit potential diagnostic value, encouraging more detailed reporting standards. While EEG alone does not definitively distinguish psychosis aetiology, its integration with clinical assessment may enhance diagnostic precision.

Indexed as

ElectroencephalographyPsychotic DisordersHumansSensitivity and SpecificityEEGMeta-analysisPsychosisSchizophreniaSystematic review

Identifiers

PMID40749302
PMCPMC7618760

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