Evidence map›Paper›PMID 42369468›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Association between Interictal Spike Rate and Seizure Frequency in a Large Epilepsy Cohort.

Erin C Conrad, Ellie Chang, Kevin Xie, Carlos A Aguila, Juri Kim, Haoer Shi, William Ks Ojemann, Jin Jing, M Brandon Westover, Saurabh R Sinha and 4 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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.

Erin C ConradDepartment of Neurology, University of Pennsylvania.ORCID 0000-0001-8910-1817
Ellie ChangDepartment of Bioengineering, University of Pennsylvania.
Kevin XieDepartment of Neurology, University of Pennsylvania.
Carlos A AguilaDepartment of Bioengineering, University of Pennsylvania.
Juri KimDepartment of Bioengineering, University of Pennsylvania.
Haoer ShiDepartment of Bioengineering, University of Pennsylvania.
William Ks OjemannDepartment of Bioengineering, University of Pennsylvania.
Jin JingDepartment of Neurology, Beth Israel Deaconess Medical Center.
M Brandon WestoverDepartment of Neurology, Beth Israel Deaconess Medical Center.
Saurabh R SinhaDepartment of Neurology, University of Pennsylvania.
Brian LittDepartment of Neurology, University of Pennsylvania.
Kathryn A DavisDepartment of Neurology, University of Pennsylvania.
Quy CaoDepartment of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia.
Colin A EllisDepartment of Neurology, University of Pennsylvania.

Funding

Late-onset Unexplained Epilepsy as a Risk Factor for DementiaR01NS130119 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Alice D Lam · 2023 to 2026
$8.7M
Data-Driven Sleep Biomarkers of Brain Health, Heart Health, and MortalityR01HL161253 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI CLIFFORD, GARI DAVID, MIGNOT, EMMANUEL J · 2022 to 2025
$8.3M
Comparative Safety of Seizure Prophylaxis within the Medicare ProgramR01AG073410 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Lidia Maria Veras Rocha de Moura · 2021 to 2026
$4.1M
Low Neurophysiologic Resistance to Anesthetics as a Marker of Preclinical/Prodromal Alzheimer's Disease and Neurovascular Pathology, Delirium risk and InattentionR01AG073598 · NIA · STANFORD UNIVERSITY · PI Miles Berger · 2022 to 2026
$3.8M
Integrative Motor Activity Biomarker for the Risk of Alzheimer's RiskRF1AG064312 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI HU, KUN · 2019 to 2019
$3.6M
Prospective Validation of Neurophysiologic Outcome Prediction in Acute Brain InjuryR01NS126282 · NINDS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI Aaron F Struck, Michael Brandon Westover · 2023 to 2026
$2.9M
Establishing a Brain Health Index from the Sleep ElectroencephalogramRF1NS120947 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI CASH, SYDNEY S, THOMAS, ROBERT JOSEPH · 2021 to 2021
$2.4M
Comparative Effectiveness of EEG-Guided Anti-Seizure Treatment in Acute Brain InjuryR01NS131347 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Sahar F Zafar · 2024 to 2026
$1.9M
Quantitative interictal networks to localize seizure generatorsK23NS121401 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Erin Conrad · 2022 to 2026
$1.2M
Polygenic risk in familial epilepsyK23NS121520 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI ELLIS, COLIN · 2021 to 2025
$1.1M
Quantitative scalp and intracranial EEG in surgical planningR01NS148413 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Erin Conrad · 2026 to 2026
$646k
NHLBI NIH HHS R01 HL161253NIA NIH HHS R01 AG073410NIA NIH HHS R01 AG073598NIA NIH HHS RF1 AG064312NINDS NIH HHS K23 NS121401NINDS NIH HHS K23 NS121520NINDS NIH HHS R01 NS126282NINDS NIH HHS R01 NS130119NINDS NIH HHS R01 NS131347NINDS NIH HHS R01 NS148413NINDS NIH HHS RF1 NS120947
6 · The paper itself

Abstract

Background and Objectives: Tracking and predicting seizure frequency in patients with epilepsy is important for prognostication and therapy management. Interictal spikes have been proposed as a biomarker of seizure burden, but their association with seizure frequency has not been well quantified across epilepsy subtypes. Our objective was to measure the association between spike rate and seizure frequency and how this varies by epilepsy subtype. Methods: We studied 3,614 consecutive routine outpatient EEGs from 3,245 patients with epilepsy followed for a median of 2.8 years. A validated automated detector (SpikeNet2) estimated spike frequency. Validated large language models performed natural language processing on outpatient clinic notes to extract seizure frequency and epilepsy subtype. We measured Spearman correlation between spike frequency (spikes/hour) and seizure frequency (seizures/month) for all patients with epilepsy and for patients with generalized epilepsy, temporal lobe epilepsy, and frontal lobe epilepsy. Results: Overall, spike frequency was modestly associated with seizure frequency (N = 3,245, ρ = 0.11 [95% CI 0.07-0.14], p < 0.001). Significant positive associations were observed in generalized epilepsy (N = 625, ρ = 0.23 [0.15-0.30], Bonferroni-adjusted p < 0.001) and temporal lobe epilepsy (N = 834, ρ = 0.12 [0.05-0.19], p = 0.0013), but not in frontal lobe epilepsy (N = 263, ρ = 0.11 [-0.02-0.24], p = 0.22). A mixed-effects model revealed a stronger spike-seizure association for clinic visits close in time to EEGs (OR=0.983 [0.967-0.999], p = 0.03), suggesting that spike rate may be a time-varying biomarker of seizure frequency. Discussion: In this large outpatient cohort, higher interictal spike rates on routine EEG were associated with higher seizure frequencies, with the strongest relationship observed in generalized epilepsy. These associations support interictal spike rate as a quantitative EEG marker of seizure burden. Spike rate may have clinical utility for risk stratification at diagnosis and for monitoring longitudinal changes in seizure burden in response to therapy.

Identifiers

PMID42369468
PMCPMC13308318

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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.