Evidence map›Paper›PMID 34725412›Full record

ArticleScientific reports2021

Accuracy of high-frequency oscillations recorded intraoperatively for classification of epileptogenic regions.

Shennan A Weiss, Richard J Staba, Ashwini Sharan, Chengyuan Wu, Daniel Rubinstein, Sandhitsu Das, Zachary Waldman, Iren Orosz, Gregory Worrell, Jerome Engel and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 9% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
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  4. Normative atlases of high-frequency oscillation and spike rates under Sevoflurane anesthesia.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2024
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  11. Sevoflurane-induced high-frequency oscillations, effective connectivity and intraoperative classification of epileptic brain areas.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2023
    Article
  12. Article
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  14. Review
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 at 5 institutions in 1 country.

Shennan A WeissDepartment of Neurology, State University of New York Downstate, Brooklyn, NY, 11203, USA.
Richard J StabaDepartment of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.
Ashwini SharanDepartment of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, 19107, USA.
Chengyuan WuDepartment of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, 19107, USA.
Daniel RubinsteinDepartment of Neurology and Neuroscience, Thomas Jefferson University, 901 Walnut St. Suite 400, Philadelphia, PA, 19107, USA.
Sandhitsu DasPenn Image Computing & Science Lab, University of Pennsylvania, Philadelphia, PA, 19143, USA.
Zachary WaldmanDepartment of Neurology and Neuroscience, Thomas Jefferson University, 901 Walnut St. Suite 400, Philadelphia, PA, 19107, USA.
Iren OroszDepartment of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.
Gregory WorrellDepartment of Neurology, Mayo Systems Electrophysiology Laboratory (MSEL), Rochester, USA.
Jerome EngelDepartment of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.
Michael R SperlingDepartment of Neurology and Neuroscience, Thomas Jefferson University, 901 Walnut St. Suite 400, Philadelphia, PA, 19107, USA. Michael.sperling@jefferson.edu.
Thomas Jefferson University · USUniversity of California, Los Angeles · USMayo Clinic in Florida · USSUNY Downstate Health Sciences University · USUniversity of Pennsylvania · US

Funding

IN VIVO STUDIES OF THE EPILEPTIC HIPPOCAMPUSR01NS033310 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI JEROME NONE ENGEL, Richard Staba · 1994 to 2026
$7.5M
Defining the Epileptogenic Network and Identifying Which Components Generate SeizuresR01NS106957 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Richard Staba · 2018 to 2026
$3.4M
Reducing or obviating the need for chronic intracranial electroencephalogram telemetry for epilepsy surgery patients by utilizing inter-ictal HFO rates: A study of diagnostic accuracyK23NS094633 · NINDS · THOMAS JEFFERSON UNIVERSITY · PI WEISS, SHENNAN A · 2017 to 2018
$335k
NINDS NIH HHS K23 NS094633NINDS NIH HHS R01 NS033310NINDS NIH HHS R01 NS106957NINDS NIH HHS R01 NS106958
6 · The paper itself

Abstract

To see whether acute intraoperative recordings using stereo EEG (SEEG) electrodes can replace prolonged interictal intracranial EEG (iEEG) recording, making the process more efficient and safer, 10 min of iEEG were recorded following electrode implantation in 16 anesthetized patients, and 1-2 days later during non-rapid eye movement (REM) sleep. Ripples on oscillations (RonO, 80-250 Hz), ripples on spikes (RonS), sharp-spikes, fast RonO (fRonO, 250-600 Hz), and fast RonS (fRonS) were semi-automatically detected. HFO power and frequency were compared between the conditions using a generalized linear mixed-effects model. HFO rates were compared using a two-way repeated measures ANOVA with anesthesia type and SOZ as factors. A receiver-operating characteristic (ROC) curve analysis quantified seizure onset zone (SOZ) classification accuracy, and the scalar product was used to assess spatial reliability. Resection of contacts with the highest rate of events was compared with outcome. During sleep, all HFOs, except fRonO, were larger in amplitude compared to intraoperatively (p < 0.01). HFO frequency was also affected (p < 0.01). Anesthesia selection affected HFO and sharp-spike rates. In both conditions combined, sharp-spikes and all HFO subtypes were increased in the SOZ (p < 0.01). However, the increases were larger during the sleep recordings (p < 0.05). The area under the ROC curves for SOZ classification were significantly smaller for intraoperative sharp-spikes, fRonO, and fRonS rates (p < 0.05). HFOs and spikes were only significantly spatially reliable for a subset of the patients (p < 0.05). A failure to resect fRonO areas in the sleep recordings trended the most sensitive and accurate for predicting failure. In summary, HFO morphology is altered by anesthesia. Intraoperative SEEG recordings exhibit increased rates of HFOs in the SOZ, but their spatial distribution can differ from sleep recordings. Recording these biomarkers during non-REM sleep offers a more accurate delineation of the SOZ and possibly the epileptogenic zone.

Indexed as

ElectrocorticographyElectrodesEpilepsyFemaleHumansIntraoperative Neurophysiological MonitoringMaleSeizuresSleep

Identifiers

PMID34725412
PMCPMC8560764
OpenAlexW3210038526

What OpenQuestion holds

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Registered trials

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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.