Evidence map›Paper›PMID 41634856›Full record

ArticleActa epileptologica2026

Predictors of cognitive impairment in drug-resistant epilepsy: the role of interictal EEG abnormalities.

Saleh Baeesa, Fawzi Babtain, Ahmad Albeshri, Amal Alkhotani, Rakan Bokhari, Motaz Fadul, Mohammed Karami, Mazen Basheikh, Adnan Badahdah, Ahmed Bamaga and 8 more

Abstract read
In one paragraph

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

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

18 authors.

Saleh BaeesaDepartment of Neurosciences, King Faisal Specialist Hospital and Research Center, Jeddah, 21499, Saudi Arabia.
Fawzi BabtainDepartment of Neurosciences, King Faisal Specialist Hospital and Research Center, Jeddah, 21499, Saudi Arabia.
Ahmad AlbeshriDepartment of Neurosurgery, King Abdulaziz Medical City, National Guard Hospital, Jeddah, 21423, Saudi Arabia.
Amal AlkhotaniDepartment of Medicine, College of Medicine, Umm Al-Qura University, Makkah, 21955, Saudi Arabia.
Rakan BokhariDepartment of Surgery, Faculty of Medicine, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.
Motaz FadulDepartment of Pathology, Faculty of Medicine, King Abdulaziz University, Rabigh, 21911, Saudi Arabia.
Mohammed KaramiDepartment of Clinical Physiology, Faculty of Medicine, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.
Mazen BasheikhDepartment of Internal Medicine, Faculty of Medicine, University of Jeddah, Jeddah, 23218, Saudi Arabia.
Adnan BadahdahDepartment of Internal Medicine, Faculty of Medicine, University of Jeddah, Jeddah, 23218, Saudi Arabia.
Ahmed BamagaDepartment of Pediatrics, Faculty of Medicine, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.
Mohammed AlshuremDepartment of Neurology, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, 31441, Saudi Arabia.
Raed GasemaltayebDepartment of Internal Medicine, Faculty of Medicine, King Abdulaziz University, Rabigh, 21911, Saudi Arabia.
Wareef AlzahraniDepartment of Neurosurgery, King Abdulaziz Medical City, National Guard Hospital, Jeddah, 21423, Saudi Arabia.
Ahmed NajjarDepartment of General and Specialized Surgery, College of Medicine, Taibah University, Madinah, 42351, Saudi Arabia.
Yasser AlamriDepartment of Neurology, King Salman Bin Abdulaziz Medical City, Madinah, 42317, Saudi Arabia.
Humaira WaseemDepartment of Data Science, INTI International University, Nilai, 71800, Malaysia.
Amber HassanEuropean School of Molecular Medicine, University of Milan, Milan, 20122, Italy.
Maher KurdiDepartment of Pathology, Faculty of Medicine, King Abdulaziz University, Rabigh, 21911, Saudi Arabia. Ahkurdi@kau.edu.sa.ORCID http://orcid.org/0000-0002-8979-3849

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCognitive impairment (CI) affects approximately one-third of patients with drug-resistant epilepsy (DRE), underscoring the need for accessible predictors. Interictal electroencephalographic (EEG) abnormalities have been proposed as potential indicators of cognitive dysfunction; however, their independent diagnostic utility is unclear. This study aimed to investigate the association between interictal EEG patterns and CI in adults with DRE, with a specific focus on evaluating their incremental predictive value beyond established clinical predictors.

methodsIn this cross-sectional study of 90 adults with DRE were recruited over a six-month period. Participants were stratified into two groups based on their Montreal Cognitive Assessment (MoCA): those with cognitive impairment (Cases; n = 45; MoCA < 26) and those with preserved cognition (Controls; n = 45; MoCA ≥ 26). All participants underwent routine interictal scalp EEG, An EEG recording was classified as abnormal if epileptiform discharges or significant background slowing was identified. The relationships between cognitive status and various clinical variables-including age, monthly seizure frequency and epilepsy type were analyzed using multivariable logistic regression, with expressed as odds ratios alongside their 95% confidence intervals.

resultsThe frequency of monthly seizures was significantly higher in the CI group compared to the control group (9.6 ± 2.8 vs. 5.4 ± 2.1 seizures/month, P < 0.001). Interictal EEG abnormalities were also more prevalant in CI group (77.8% vs. 57.8%; OR = 2.56, 95% CI: 1.02-6.41, P = 0.041). However, in the adjusted multivariable model, only seizure frequency reained a signifcant independent association with CI (adjusted OR = 0.46, 95% CI: 0.32-0.65, P < 0.001), indicating that EEG abnormalities did not confer significant additional predictive power after accounting for seizure burden.

conclusionsSeizure burden emerged as the predominant predictor of CI with DRE, while interictal EEG abnormalities demonstrated a univariate correlation with cogntive status, this association was not independent in the adjusted analysis. EEG findings may still provide contextual or supportive clinical context, emphasize that a comprehensive approach integrating seizure management with cognitive assessments is warranted, rather than relying primarily on interictal EEG for cognitive risk stratification.

Indexed as

Cognitive impairmentDrug-resistant epilepsyInterictal electroencephalographMontreal Cognitive AssessmentPredictors

Identifiers

PMID41634856
PMCPMC12870934

What Socratic 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 Socratic graph.