Evidence map›Paper›PMID 36140594›Full record

ReviewDiagnostics (Basel, Switzerland)2022

Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review.

Andrea Perrottelli, Giulia Maria Giordano, Francesco Brando, Luigi Giuliani, Pasquale Pezzella, Armida Mucci, Silvana Galderisi

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

23 citing papers in PubMed.

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  20. Advances in the Diagnosis and Management of Psychosis.Diagnostics (Basel, Switzerland) · 2023
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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

7 authors.

Andrea PerrottelliDepartment of Psychiatry, University of Campania "Luigi Vanvitelli", Largo Madonna delle Grazie 1, 80138 Naples, Italy.ORCID 0000-0001-7771-1845
Giulia Maria GiordanoDepartment of Psychiatry, University of Campania "Luigi Vanvitelli", Largo Madonna delle Grazie 1, 80138 Naples, Italy.
Francesco BrandoDepartment of Psychiatry, University of Campania "Luigi Vanvitelli", Largo Madonna delle Grazie 1, 80138 Naples, Italy.
Luigi GiulianiDepartment of Psychiatry, University of Campania "Luigi Vanvitelli", Largo Madonna delle Grazie 1, 80138 Naples, Italy.
Pasquale PezzellaDepartment of Psychiatry, University of Campania "Luigi Vanvitelli", Largo Madonna delle Grazie 1, 80138 Naples, Italy.ORCID 0000-0002-8442-5385
Armida MucciDepartment of Psychiatry, University of Campania "Luigi Vanvitelli", Largo Madonna delle Grazie 1, 80138 Naples, Italy.ORCID 0000-0002-6195-9456
Silvana GalderisiDepartment of Psychiatry, University of Campania "Luigi Vanvitelli", Largo Madonna delle Grazie 1, 80138 Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cognitive dysfunctions represent a core feature of schizophrenia-spectrum disorders due to their presence throughout different illness stages and their impact on functioning. Abnormalities in electrophysiology (EEG) measures are highly related to these impairments, but the use of EEG indices in clinical practice is still limited. A systematic review of articles using Pubmed, Scopus and PsychINFO was undertaken in November 2021 to provide an overview of the relationships between EEG indices and cognitive impairment in schizophrenia-spectrum disorders. Out of 2433 screened records, 135 studies were included in a qualitative review. Although the results were heterogeneous, some significant correlations were identified. In particular, abnormalities in alpha, theta and gamma activity, as well as in MMN and P300, were associated with impairments in cognitive domains such as attention, working memory, visual and verbal learning and executive functioning during at-risk mental states, early and chronic stages of schizophrenia-spectrum disorders. The review suggests that machine learning approaches together with a careful selection of validated EEG and cognitive indices and characterization of clinical phenotypes might contribute to increase the use of EEG-based measures in clinical settings.

Indexed as

biomarkerscognitionelectroencephalogram (EEG)schizophrenia

Identifiers

PMID36140594
PMCPMC9498272

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.