Evidence map›Paper›PMID 34704026›Full record

ArticleBrain communications2021

Interictal high frequency background activity as a biomarker of epileptogenic tissue.

Truman Stovall, Brian Hunt, Simon Glynn, William C Stacey, Stephen V Gliske

Abstract read
In one paragraph

Article in Brain communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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.

Truman StovallDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
Brian HuntDepartment of Neurology, University of Michigan, Ann Arbor, MI, USA.
Simon GlynnDepartment of Neurology, University of Michigan, Ann Arbor, MI, USA.
William C StaceyDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.ORCID https://orcid.org/0000-0002-8359-8057
Stephen V GliskeDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.ORCID https://orcid.org/0000-0002-2259-2612

Funding

Characterizing High Frequency Oscillations as an epilepsy biomarker with Big Data toolsR01NS094399 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI STACEY, WILLIAM CHARLES · 2015 to 2025
$4.1M
Epileptic biomarkers and big data: identifying brain regions to resect in patients with refractory epilepsyK01ES026839 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GLISKE, STEPHEN V · 2015 to 2019
$734k
Doris Duke Charitable Foundation 2015096NIEHS NIH HHS K01 ES026839NINDS NIH HHS R01 NS094399
6 · The paper itself

Abstract

High frequency oscillations (HFOs) are very brief events that are a well-established biomarker of the epileptogenic zone (EZ) but are rare and comprise only a tiny fraction of the total recorded EEG. We hypothesize that the interictal high frequency 'background' data, which has received little attention but represents the majority of the EEG record, also may contain additional, novel information for identifying the EZ. We analysed intracranial EEG (30-500 Hz frequency range) acquired from 24 patients who underwent resective surgery. We computed 38 quantitative features based on all usable, interictal data (63-307 h per subject), excluding all detected HFOs. We assessed association between each feature and the seizure onset zone (SOZ) and resected volume (RV) using logistic regression. A pathology score per channel was also created via principle component analysis and logistic regression, using hold-out-one-patient cross-validation to avoid in-sample training. Association of the pathology score with the SOZ and RV was quantified using an asymmetry measure. Many features were associated with the SOZ: 23/38 features had odds ratios >1.3 or <0.7 and 17/38 had odds ratios different than zero with high significance (

Indexed as

EEGhigh frequency activity

Identifiers

PMID34704026
PMCPMC8417455

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.