Identification of seizure clusters using free text notes in an electronic seizure diary.

SIGNIFICANCE: Online seizure diaries offer a wealth of information regarding real world experience of patients living with epilepsy. Free text notes (FTN) written by patients reflect concerns and priorities of patients and provide supplemental information to structured diary data. OBJECTIVE: This project evaluated feasibility using an automated lexical analysis to identify FTN relevant to seizure clusters (SCs). METHODS: Data were extracted from EpiDiary™, a free electronic epilepsy diary with 42,799 unique users, generating 1,096,168 entries and 247,232 FTN. Both structured data as well as FTN were analyzed for presence of SC. A pilot study was conducted to validate an automated lexical analysis algorithm to identify SC in FTN in a sample of 98 diaries. The lexical analysis was then applied to the entire dataset. Outcomes included cluster prevalence and frequency, as well as the types of triggers commonly reported. RESULTS: At least one FTN was found among 13,987 (32.68%) individual diaries. An automated lexical analysis algorithm identified 5797 of FTN as SC. There were 2423 unique patients with SC that were not identified by structured data alone and were identified using lexical analysis of FTN only. Seizure clusters were identified in n = 10,331 (24.1%) of diary users through both structured data and FTN. The median number of SCs days per year was 13.7, (interquartile rank (IQR): 3.2-54.7). The median number of seizures in a cluster day was 3 (IQR 2-4). The most common missed medication linked to patients with SC was levetiracetam (n = 576, 29%) followed by lamotrigine (n = 495, 24%), topiramate (n = 208, 10.5%), carbamazepine (n = 190, 9.6%), and lacosamide (n = 170, 8.6%). These percentages generally reflected prevalence of medication use in this population. The use of rescue medications was documented in 3306 of structured entries and 4305 in FTN. CONCLUSION: This exploratory study demonstrates a novel approach applying lexical analysis to previously untapped FTN in a large electronic seizure diary database. Free text notes captured information about SC not available from the structured diary data. Diary FTN contain information of high importance to people with epilepsy, written in their own words.

Medication adherence in women with epilepsy who are planning pregnancy.

OBJECTIVE: This study examines medication adherence among women with epilepsy via use of an electronic diary, as part of a prospective multicenter observational study designed to evaluate fertility in women with epilepsy (WWE) versus age-matched controls. METHODS: WWE and healthy age-matched controls, seeking pregnancy, were given an iPod Touch using a customized mobile application (the WEPOD App) for daily data tracking. Eighty-six WWE tracked seizures and antiepileptic drugs (AEDs). Tracking of nonepilepsy medications was optional. Diary data were counted from enrollment date until date of delivery, or up to 12 months if pregnancy was not achieved. Each day that subjects reported missing one or more AED was counted as nonadherence. Because adherence can only be determined in women who track consistently, we elected to include adherence data only for women who tracked >80% of days in the study. RESULTS: Approximately 75% of WWE tracked >80% of days and were included in medication adherence data analysis. In this group, medication adherence rate was 97.71%; 44% of women admitted to missing an AED on at least 1 day. Among the subgroup of WWE who recorded nonepilepsy medications, AED adherence rate was 98.56%, versus 93.91% for non-AEDs. SIGNIFICANCE: The 75% compliance rate with an electronic diary suggests that it may be useful to track medication adherence in future studies and in the clinical setting. In those who tracked, the observed medication adherence rate was considerably higher than the 75% adherence rate seen in previous epilepsy studies. This might be explained in part by selection bias, but may also result from properties of the diary itself (daily reminders, real time feedback given to the provider). Women reported a higher rate of adherence to AEDs than to other prescribed medications and supplements, suggesting that perceived importance of medications likely influences medication adherence, and warrants future study.

Use of an online epilepsy diary to characterize repetitive seizures.

SIGNIFICANCE: Little is known about patterns of seizures that occur multiple times a day, sometimes called clusters or serial seizures. OBJECTIVE: The online diary, My Epilepsy Diary (MED), provided self-reported data from community-based patients to describe the characteristics of clusters. METHODS: We used MED data to define a population of 5098 community outpatients, including 1177 who specified time of multiple seizures in a 24-hour period. Outcomes included cluster prevalence and frequency, distribution of interseizure time intervals, as well as the types of triggers commonly reported. RESULTS: One-fourth of days with any seizures included clusters for these patients. Most days with clusters included 2 seizures, with >5 events occurring in only 10% of days. One-third of seizures occurred within 3h of the initial event and two-thirds within 6h. When more than 2 seizures occurred, the time to the next seizure decreased from an average of over 2h (to the 3rd event) to a quarter-hour (from the 4th to the 5th event). CONCLUSION: My Epilepsy Diary data have provided the first overview of cluster seizures in a large community-based population. Treatments with less than 3-hour duration of action would be bioavailable at the time of only one-third of subsequent seizures. Although limited by the self-reported and observational nature of the diary data, some general patterns emerge and can help to focus questions for future studies.

An online diary for tracking epilepsy.

My Epilepsy Diary is a free Web-based application on the public website epilepsy.com, available for patients to track epilepsy and to aid clinicians with data-based, individualized management. The first aim of this descriptive study was to outline electronic diary functions. Second, the study retrospectively profiled a large cohort of 2010 calendar year diary users including demographics, seizure types, temporal distribution of seizures, triggers, and use and side effects of antiepileptic drugs (AEDs). A total of 1944 users provided demographic information and 1877 recorded seizure data. Most (64%) users were women. Average age was 29.9±16.0 years. A total of 70,990 seizure entries and 15,630 AED entries were logged. Events were apportioned as 79% seizures and 21% seizure clusters. Specific AEDs were detailed in 7331 entries: monotherapy was used in 18% and polytherapy in 82%. Mood-related side effects were most commonly reported in 19% of 1027 users.