Evidence map›Paper›PMID 32589284›Full record

ArticleEpilepsia2020

Interictal intracranial electroencephalography for predicting surgical success: The importance of space and time.

Yujiang Wang, Nishant Sinha, Gabrielle M Schroeder, Sriharsha Ramaraju, Andrew W McEvoy, Anna Miserocchi, Jane de Tisi, Fahmida A Chowdhury, Beate Diehl, John S Duncan and 1 more

Abstract read
In one paragraph

Article in Epilepsia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
–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

35 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  15. Interictal intracranial EEG asymmetry lateralizes temporal lobe epilepsy.medRxiv : the preprint server for health sciences · 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

11 authors.

Yujiang WangCNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.ORCID 0000-0002-4847-6273
Nishant SinhaCNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Gabrielle M SchroederCNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Sriharsha RamarajuCNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Andrew W McEvoyInstitute of Neurology, University College London, London, UK.
Anna MiserocchiInstitute of Neurology, University College London, London, UK.
Jane de TisiInstitute of Neurology, University College London, London, UK.
Fahmida A ChowdhuryInstitute of Neurology, University College London, London, UK.
Beate DiehlInstitute of Neurology, University College London, London, UK.ORCID 0000-0002-6896-854X
John S DuncanInstitute of Neurology, University College London, London, UK.ORCID 0000-0002-1373-0681
Peter N TaylorCNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.ORCID 0000-0003-2144-9838

Funding

SUDEP Translational Research Alliance (SUTRA): Autonomic and Imaging Biomarkers of SUDEP; SUTRA 3 of 7U01NS090407 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI DIEHL, BEATE, HARPER, RONALD MARVEN · 2014 to 2018
$7.3M
NINDS NIH HHS U01 NS090407Wellcome Trust 208940Wellcome Trust 208940/Z/17/ZWellcome Trust 210109Wellcome Trust 210109/Z/18/Z
6 · The paper itself

Abstract

objectivePredicting postoperative seizure freedom using functional correlation networks derived from interictal intracranial electroencephalography (EEG) has shown some success. However, there are important challenges to consider: (1) electrodes physically closer to each other naturally tend to be more correlated, causing a spatial bias; (2) implantation location and number of electrodes differ between patients, making cross-subject comparisons difficult; and (3) functional correlation networks can vary over time but are currently assumed to be static.

methodsIn this study, we address these three challenges using intracranial EEG data from 55 patients with intractable focal epilepsy. Patients additionally underwent preoperative magnetic resonance imaging (MRI), intraoperative computed tomography, and postoperative MRI, allowing accurate localization of electrodes and delineation of the removed tissue.

resultsWe show that normalizing for spatial proximity between nearby electrodes improves prediction of postsurgery seizure outcomes. Moreover, patients with more extensive electrode coverage were more likely to have their outcome predicted correctly (area under the receiver operating characteristic curve > 0.9, P « 0.05) but not necessarily more likely to have a better outcome. Finally, our predictions are robust regardless of the time segment analyzed. SIGNIFICANCE: Future studies should account for the spatial proximity of electrodes in functional network construction to improve prediction of postsurgical seizure outcomes. Greater coverage of both removed and spared tissue allows for predictions with higher accuracy.

Indexed as

Electrodes, ImplantedDrug Resistant EpilepsyElectroencephalographyHumansMagnetic Resonance ImagingNerve NetPredictive Value of TestsRetrospective StudiesTime FactorsTreatment Outcomecortical localizationEEGepilepsy surgeryepileptogenic zoneintracranial electrodes

Identifiers

PMID32589284
PMCPMC7611164

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LicenceCC BY
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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.