Evidence map›Paper›PMID 32384221›Full record

ArticleJournal of neuroimaging : official journal of the American Society of Neuroimaging2020

Epilepsy Lesion Localization is not Predicted by Developmental Venous Anomaly Location or its FDG-PET Metabolic Activity.

Jillian W Lazor, Joel M Stein, James Eric Schmitt, Kathryn A Davis, Seyed Ali Nabavizadeh

Open access · greenAbstract read
In one paragraph

Article in Journal of neuroimaging : official journal of the American Society of Neuroimaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 46% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
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

5 authors at 1 institution in 1 country.

Jillian W LazorDepartment of Neuroradiology, The Hospital of the University of Pennsylvania, Philadelphia, PA.ORCID 0000-0002-7966-9377
Joel M SteinDepartment of Neuroradiology, The Hospital of the University of Pennsylvania, Philadelphia, PA.
James Eric SchmittDepartment of Neuroradiology, The Hospital of the University of Pennsylvania, Philadelphia, PA.
Kathryn A DavisDepartment of Neurology, The Hospital of the University of Pennsylvania, Philadelphia, PA.
Seyed Ali NabavizadehDepartment of Neuroradiology, The Hospital of the University of Pennsylvania, Philadelphia, PA.
Hospital of the University of Pennsylvania · US

Funding

Localizing epileptic networks using novel 7T MRI glutamate imagingK23NS092973 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DAVIS, KATHRYN ADAMIAK · 2016 to 2020
$980k
NINDS NIH HHS K23 NS092973
6 · The paper itself

Abstract

background and purposeThis study's purpose is to correlate location and metabolic activity of developmental venous anomalies (DVAs) in epilepsy patients to the seizure focus as determined by ictal/interictal encephaloelectrogram (EEG).

methodsA retrospective search was performed for epilepsy patients with DVAs who underwent brain

resultsTwenty-eight DVAs in 25 patients were included. Twelve DVAs demonstrated regional metabolic abnormality on

conclusionsIn this sample, there is no significant correlation between location of DVA and seizure focus, and hypometabolism within the DVA territory is not predictive of EEG/DVA co-localization. As use of

Indexed as

AdultBrainElectroencephalographyEpilepsyFemaleFluorodeoxyglucose F18HumansMagnetic Resonance ImagingMaleMiddle AgedPositron-Emission TomographyRetrospective StudiesFluorodeoxyglucose F18Developmental venous anomalyepilepsyFDG-PETseizure

Identifiers

PMID32384221
PMCPMC8162990
OpenAlexW3022607889

What OpenQuestion holds

Textmetadata
LicenceTDM
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.