Evidence map›Paper›PMID 42227921›Full record

ArticleEpilepsia2026

High-frequency oscillations after acute hemorrhagic traumatic brain injury: insights into posttraumatic epilepsy development.

Kseniia Kriukova, Lin Li, Richard J Staba, Misque Boswell, Tuba Asifriyaz, Rachel Thomas, James J Gugger, Mohamad Shamas, Ramon Diaz-Arrastia, Manuel Buitrago Blanco and 4 more

Abstract readMulticenter Study
In one paragraph

Article in Epilepsia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Kseniia KriukovaDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0000-0001-6714-9780
Lin LiDepartment of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.ORCID https://orcid.org/0000-0002-9996-9377
Richard J StabaDepartment of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.ORCID https://orcid.org/0000-0003-2285-5627
Misque BoswellDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-6128-1964
Tuba AsifriyazDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0009-0008-0240-1840
Rachel ThomasDepartment of Neurology, Barrow Neurological Institute, Phoenix, Arizona, USA.ORCID https://orcid.org/0000-0002-8981-1568
James J GuggerDepartment of Neurology, School of Medicine and Dentistry, University of Rochester, Rochester, New York, USA.ORCID https://orcid.org/0000-0003-1113-2984
Mohamad ShamasDepartment of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.ORCID https://orcid.org/0000-0001-7564-0932
Ramon Diaz-ArrastiaDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0000-0001-6051-3594
Manuel Buitrago BlancoBrain Research Institute, University of California, Los Angeles, Los Angeles, California, USA.
Jerome EngelDepartment of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.ORCID https://orcid.org/0000-0001-6324-5716
Paul M VespaBrain Research Institute, University of California, Los Angeles, Los Angeles, California, USA.ORCID https://orcid.org/0000-0003-0936-9501
Dominique DuncanDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-6154-9262
EpiBios4Rx investigators

Funding

The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) Public Engagement CoreU54NS100064 · NINDS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ENGEL, JEROME NONE, GALANOPOULOU, ARISTEA S · 2017 to 2021
$21.7M
Translational Platform for Epilepsy Therapy and Biomarker DiscoveryR01NS127524 · NINDS · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI Denes V. Agoston, LISA D COLES · 2022 to 2026
$11.0M
SUPPORT FOR THE ROSE F KENNEDY IDDRC P50P50HD105352 · NICHD · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI SOPHIE MOLHOLM, Steven Upshaw Walkley · 2021 to 2026
$7.0M
In Vivo Studies of the Epileptic HippocampusRF1NS033310 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ENGEL, JEROME NONE, STABA, RICHARD · 2023 to 2023
$3.6M
Defining the Epileptogenic Network and Identifying Which Components Generate SeizuresR01NS106957 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Richard Staba · 2018 to 2026
$3.4M
Christina Louise George TrustNICHD NIH HHS P50 HD105352NINDS NIH HHS R01 NS106957NINDS NIH HHS R01 NS127524NINDS NIH HHS RF1 NS033310NINDS NIH HHS U54 NS100064
6 · The paper itself

Abstract

objectiveThe development of posttraumatic epilepsy after traumatic brain injury (TBI) is potentially identifiable by measuring biomarkers of epileptogenesis, namely pathological high-frequency oscillations (pHFOs). pHFOs are promising candidates, but it remains uncertain whether they can be detected early after TBI in clinical settings. This study was undertaken to determine the incidence and location of pHFOs as recorded from scalp and intracranial electroencephalography (EEG) during the first week after acute TBI and to determine the association of pHFOs with late posttraumatic seizures (PTS).

methodsWe analyzed continuous EEG from 35 TBI patients with acute hemorrhagic TBI (Glasgow Coma Scale = 3-13) enrolled in the multicenter EpiBioS4Rx cohort. Automated pHFO detection was followed by independent experts' verification. The rate of two types of pHFO ripples (70-250 Hz) and fast ripples (250-500 Hz) were computed using scalp and intracranial EEG. Firth logistic regression models estimated associations between pHFOs rates and late PTS occurrence.

results16 of 35 patients (45.7%) developed late PTS. Verified scalp ripples were observed in 17 patients (48.6%), whereas no fast ripples were confirmed on expert review. Ripple activity was most frequent over frontal regions (13/17, 76.5%, p = .049, 95% confidence interval [CI] = .50-.93) and similarly frequent in perihemorrhagic locations (13/17, 76.5%, p = .049, 95% CI = .50-.93). Among 10 patients with intracranial EEG, verified ripples occurred in five (50%), including two of two with pericontusional strip electrodes. SIGNIFICANCE: In critically ill patients with acute hemorrhagic TBI monitored in the intensive care unit, both scalp and intracranial EEG can detect pHFOs within the first week after injury, demonstrating the technical feasibility of capturing these signals in a real-world clinical setting. Verified pHFOs were most frequently observed over frontal and perihemorrhagic regions, consistent with early perilesional hyperexcitability. pHFOs appear to be mechanistically grounded markers of perilesional hyperexcitability. Standardized, high-sampling EEG studies with targeted pericontusional coverage are needed to establish prognostic performance for late PTS.

Indexed as

Brain Injuries, TraumaticBrain WavesEpilepsy, Post-TraumaticAdultAgedElectroencephalographyFemaleHumansMaleMiddle Agedepileptogenesishigh‐frequency oscillationsposttraumatic epilepsytraumatic brain injury

Identifiers

PMID42227921
PMCPMC13360913

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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.