Literature review and protocol for a prospective multicentre cohort study on multimodal prediction of seizure recurrence after unprovoked first seizure.

INTRODUCTION: Epilepsy is a common neurological disorder characterised by recurrent seizures. Almost half of patients who have an unprovoked first seizure (UFS) have additional seizures and develop epilepsy. No current predictive models exist to determine who has a higher risk of recurrence to guide treatment. Emerging evidence suggests alterations in cognition, mood and brain connectivity exist in the population with UFS. Baseline evaluations of these factors following a UFS will enable the development of the first multimodal biomarker-based predictive model of seizure recurrence in adults with UFS. METHODS AND ANALYSIS: 200 patients and 75 matched healthy controls (aged 18-65) from the Kingston and Halifax First Seizure Clinics will undergo neuropsychological assessments, structural and functional MRI, and electroencephalography. Seizure recurrence will be assessed prospectively. Regular follow-ups will occur at 3, 6, 9 and 12 months to monitor recurrence. Comparisons will be made between patients with UFS and healthy control groups, as well as between patients with and without seizure recurrence at follow-up. A multimodal machine-learning model will be trained to predict seizure recurrence at 12 months. ETHICS AND DISSEMINATION: This study was approved by the Health Sciences and Affiliated Teaching Hospitals Research Ethics Board at Queen's University (DMED-2681-22) and the Nova Scotia Research Ethics Board (1028519). It is supported by the Canadian Institutes of Health Research (PJT-183906). Findings will be presented at national and international conferences, published in peer-reviewed journals and presented to the public via patient support organisation newsletters and talks. TRIAL REGISTRATION NUMBER: NCT05724719.

Cognitive dysfunction at epilepsy onset as a marker for seizure recurrence.

BACKGROUND: Cognitive dysfunction has been correlated with seizure control in chronic epilepsy and in newly diagnosed epilepsy, which potentially makes it a good marker for predicting disease course and seizure control. However, there is a lack of prospective studies examining the role of cognitive dysfunction in predicting seizure recurrence at the earliest stages of the disease, such as following the first unprovoked seizure (UFS) or new onset epilepsy (NOE). METHODS: Thirty three adult participants (FS=18, NOE=15) from the Halifax First Seizure Clinic (HFSC) completed a cognitive screening assessment at baseline (typically 3 months following diagnosis); seizure-recurrence was evaluated one year after the initial HFSC visit. RESULTS: Cognitive impairment, defined as at least one z-score in the impaired range (≤-1.5) relative to published test norms, was documented in 76% of the patients with seizure recurrence at follow-up and in 55% without seizure recurrence. Speed/executive functions and Memory were the most frequently affected domains, with impaired performance noted in 35% and 29% of the entire sample, respectively. Although the seizure recurrence vs. non-recurrence groups did not differ significantly on likelihood of impairment in any specific cognitive domains, a regression model of seizure recurrence that included years of education, baseline mood and anxiety scores, normal vs. abnormal baseline MRI, and impaired (vs. unimpaired) function in six cognitive domains was significant overall (Χ2 (10) = 24.04, p =.007*, R2N =.77). The regression model was no longer significant with the cognitive variables removed. CONCLUSIONS: Subtle cognitive dysfunction, especially in the domains of executive functions and memory are prevalent in individuals at the earliest stages of epilepsy. In addition to abnormal MRI and EEG findings at baseline, which are far less prevalent in FS and NOE, cognitive factors show promise in helping predict seizure recurrence in these populations.