Investigating the Impact of Epilepsy on Cognitive Function: A Narrative Review

Hoxhaj, Pranvera; Habiya, Sana K; Sayabugari, Rithika; Balaji, Roghan; Xavier, Roshni; Ahmad, Arghal; Khanam, Mousumi; Kachhadia, Meet Popatbhai; Patel, Tirath; Abdin, Zain U; Haider, Ali; Nazir, Zahra

doi:10.7759/cureus.41223

Cited by 4 publications

(2 citation statements)

References 79 publications

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“…A large number of seriously ill patients including those in the intensive care units (ICUs) are at risk of diverse neurological ailments that can adversely in uence their outcome and quality of life [2]. Seizures are serious threats to the neurological well-being and are associated with long term cognitive de cits if missed or mistaken [3]. Other patterns of abnormal brain activity including periodic discharges and rhythmic activities are associated with underlying neurological injuries and must be studied for interpretation [4].…”

Section: Introductionmentioning

confidence: 99%

Explainable classification of seizures and other patterns of harmful brain activity in critically ill patients

NAGANDLA

2024

Preprint

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Accurate detection and classification of seizures from electroencephalography (EEG) data can potentially enable timely interventions and treatments for neurological diseases. Currently, EEG recordings are exclusively reviewed by human experts, namely neurologists with specialized training. While indispensable, this time-consuming workflow represents a major bottleneck. Review of EEG records is laborious, time-consuming, expensive, prone to fatigue-induced errors, and suffers from inter-rater reliability even among expert reviewers. This paper introduces a new deep neural network (DNN) with interpretable layers for the classification of seizures and other pathologic brain activities such as periodic discharges, rhythmic delta waves and miscellaneous activities. The DNN architecture uses interpretable layers that allow clinicians to evaluate the model’s decision-making pipeline and build trust in the model and support clinical decision making. The combination of deep learning and interpretability layers is novel and addresses the limitations of existing methods. We demonstrate the usefulness of the proposed approach on a publicly available EEG dataset. Our method achieves state-of-the-art performance and provides classification decisions that are interpretable, useful for clinical experts. This paper contributes to the existing body of literature on EEG-based seizure detection and addresses the gap between DNN-based methods and clinical interpretability, leading to accurate and clinically meaningful predictions.

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Section: Introductionmentioning

confidence: 99%

Explainable classification of seizures and other patterns of harmful brain activity in critically ill patients

NAGANDLA

2024

Preprint

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“…7 Limited studies show that older adults with seizures and TBI often experience significant cognitive impairment. [8][9][10] The number of individuals in the US with ADRD is projected to reach 14 million by 2050. African American and Hispanic individuals are 2 and 1.5 times more likely to have ADRD, respectively, compared with non-Hispanic White (hereafter, White) individuals.…”

Section: Introductionmentioning

confidence: 99%

Traumatic Brain Injury, Seizures, and Cognitive Impairment Among Older Adults

Zhu,

Williams,

Beyene

et al. 2024

JAMA Netw Open

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ImportanceTraumatic brain injury (TBI), seizures, and dementia increase with age. There is a gap in understanding the associations of TBI, seizures, and medications such as antiseizure and antipsychotics with the progression of cognitive impairment across racial and ethnic groups.ObjectiveTo investigate the association of TBI and seizures with the risk of cognitive impairment among cognitively normal older adults and the role of medications in moderating the association.Design, Setting, and ParticipantsThis multicenter cohort study was a secondary analysis of the Uniform Data Set collected between June 1, 2005, and June 30, 2020, from the National Alzheimer’s Coordination Center. Statistical analysis was performed from February 1 to April 3, 2024. Data were collected from participants from 36 Alzheimer’s Disease Research Centers in the US who were 65 years or older at baseline, cognitively normal at baseline (Clinical Dementia Rating of 0 and no impairment based on a presumptive etiologic diagnosis of AD), and had complete information on race and ethnicity, age, sex, educational level, and apolipoprotein E genotype.ExposureHealth history of TBI, seizures, or both conditions.Main Outcomes and MeasuresProgression to cognitive impairment measured by a Clinical Dementia Rating greater than 0.ResultsAmong the cohort of 7180 older adults (median age, 74 years [range, 65-102 years]; 4729 women [65.9%]), 1036 were African American or Black (14.4%), 21 were American Indian or Alaska Native (0.3%), 143 were Asian (2.0%), 332 were Hispanic (4.6%), and 5648 were non-Hispanic White (78.7%); the median educational level was 16.0 years (range, 1.0-29.0 years). After adjustment for selection basis using propensity score weighting, seizure was associated with a 40% higher risk of cognitive impairment (hazard ratio [HR], 1.40; 95% CI, 1.19-1.65), TBI with a 25% higher risk of cognitive impairment (HR, 1.25; 95% CI, 1.17-1.34), and both seizure and TBI were associated with a 57% higher risk (HR, 1.57; 95% CI, 1.23-2.01). The interaction models indicated that Hispanic participants with TBI and seizures had a higher risk of cognitive impairment compared with other racial and ethnic groups. The use of antiseizure medications (HR, 1.23; 95% CI, 0.99-1.53), antidepressants (HR, 1.32; 95% CI, 1.17-1.50), and antipsychotics (HR, 2.15; 95% CI, 1.18-3.89) was associated with a higher risk of cognitive impairment, while anxiolytic, sedative, or hypnotic use (HR, 0.88; 95% CI, 0.83-0.94) was associated with a lower risk.Conclusions and RelevanceThis study highlights the importance of addressing TBI and seizures as risk factors for cognitive impairment among older adults. Addressing the broader social determinants of health and bridging the health divide across various racial and ethnic groups are essential for the comprehensive management and prevention of dementia.

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Static and dynamic changes in amplitude of Low-Frequency fluctuations in patients with Self-Limited epilepsy with centrotemporal Spikes (SeLECTS): A Resting-State fMRI study

Ameen Fateh,

Hassan,

et al. 2024

Journal of Clinical Neuroscience

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Investigating the Impact of Epilepsy on Cognitive Function: A Narrative Review

Cited by 4 publications

References 79 publications

Explainable classification of seizures and other patterns of harmful brain activity in critically ill patients

Explainable classification of seizures and other patterns of harmful brain activity in critically ill patients

Traumatic Brain Injury, Seizures, and Cognitive Impairment Among Older Adults

Static and dynamic changes in amplitude of Low-Frequency fluctuations in patients with Self-Limited epilepsy with centrotemporal Spikes (SeLECTS): A Resting-State fMRI study

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