Abstracts

Rationale: Physiological variation in secretion of estrogen and progesterone during the menstrual cycle can influence the occurrence of seizures in some women with epilepsy and can lead to a pattern of seizure exacerbation around specific days of the menstrual cycle, e.g around menstruation and ovulation in ovulatory women. ¹ We developed the Seizure Cycle mobile application (app) which has a built-in algorithm to predict the date of next ovulation and menstruation based on certain variables entered by the participants. If there is a consistent pattern between their menstrual cycle and seizure exacerbation, the app can reliably predict the next increase in seizure frequency.

Methods: The feasibility study for the seizure cycle app will include 20 Adult female patients under the age of 45 with a history of epilepsy and regular menstrual cycle. Once consented, the participants downloaded app and entered seizure data including date, time, duration, and seizure triggers. They also entered menstrual cycle information such as first and last day of menses. Based on the information entered by patients, the app predicts date of next ovulation and menstruation. The app will be used by patients for six months with data being collected by the investigators monthly.

Results: At the time of this submission, only one enrolled participant had completed six months of use of the app. Twenty-two seizures were logged during this period. Of those, nine seizures (41%) occurred either during the perimenstrual (C1) or peri-ovulatory (C2) of the menstrual cycle. Fifty-five percent of these seizures recorded fell under C1 peri-menstrual pattern and 44% under the C2 peri-ovulatory pattern described by Herzog et al. Based on this current data, patient does not meet the criteria for catamenial epilepsy (consistent doubling of seizure frequency during C1, C2, or C3 phase).¹ But despite the limited data, one could hypothesize that continued use of the app for a longer duration may be beneficial in predicting catamenial seizure exacerbations in a larger cohort of female subjects.

References
1. Herzog AG, Klein P, Rand BJ. Three Patterns of Catamenial Epilepsy. Epilepsia. 1997;38:1082–1088.

Conclusions: This limited pilot data from one patient shows the feasibility of the mobile application Seizure Cycle in detecting catamenial seizure patterns and predicting seizure exacerbation associated with menstrual cycle in some female patients.

Funding: Please list any funding that was received in support of this abstract.: The application was developed with the support of national center for advancing translational sciences of the NIH under award number UL1TR001876.