Seizure occurrence: Precipitants and prediction

Research output: Contribution to journalArticle

145 Citations (Scopus)

Abstract

OBJECTIVE: To explore the relationship of seizure occurrence with candidate seizure precipitants in a prospective diary study, and to determine the relationship of precipitants to seizure self-prediction. METHODS: Eligible subjects were 18 or older, had localization-related epilepsy, at least one seizure within 12 months, and were able to maintain a daily diary. Information collected included the occurrence, time and characteristics of all seizures, hours of sleep, medication compliance, stress, anxiety, alcohol use, menstruation, and seizure self-prediction. Each night, subjects reported their estimate of the likelihood of a seizure the next day (self-prediction). Logit-normal models with a random subject-specific intercept were used to estimate an OR for the association of precipitants with seizure occurrence. RESULTS: Seventy-one subjects returned 15,179 complete diary days. For each hour of increased sleep on the preceding night, the relative odds of a seizure the following day decreased (OR 0.91, 95% CI 0.82, 0.99). One-unit increments of stress and anxiety (on a 10-point scale) were associated with an increased risk of seizure the following day (OR 1.06, 95% CI 1.01, 1.12 and OR 1.07; 95% CI 1.02, 1.12). With self-prediction included in the model, self-prediction (OR 3.7; 95% CI 1.8, 7.2) and hours of sleep for the night prior to the seizure (OR 0.90; 95% CI 0.82, 0.99) remained significant. CONCLUSION: Lack of sleep and higher self-reported stress and anxiety levels were associated with seizure occurrence. In a model that included self-prediction, less sleep, and self-prediction had significant effects, whereas stress and anxiety did not. The psychological and biologic mechanisms which link stress and anxiety to self-prediction of seizures requires further exploration. Ultimately, seizure prediction based on precipitants, premonitory features, and self-prediction may provide a foundation for preemptive treatment.

Original languageEnglish (US)
Pages (from-to)1905-1910
Number of pages6
JournalNeurology
Volume69
Issue number20
DOIs
StatePublished - Nov 2007

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Seizures
Sleep
Anxiety
Menstruation
Medication Adherence
Partial Epilepsy
Logistic Models
Odds Ratio
Alcohols
Prospective Studies
Psychology

ASJC Scopus subject areas

  • Neuroscience(all)

Cite this

Seizure occurrence : Precipitants and prediction. / Haut, Sheryl R.; Hall, Charles B.; Masur, Jonathan; Lipton, Richard B.

In: Neurology, Vol. 69, No. 20, 11.2007, p. 1905-1910.

Research output: Contribution to journalArticle

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abstract = "OBJECTIVE: To explore the relationship of seizure occurrence with candidate seizure precipitants in a prospective diary study, and to determine the relationship of precipitants to seizure self-prediction. METHODS: Eligible subjects were 18 or older, had localization-related epilepsy, at least one seizure within 12 months, and were able to maintain a daily diary. Information collected included the occurrence, time and characteristics of all seizures, hours of sleep, medication compliance, stress, anxiety, alcohol use, menstruation, and seizure self-prediction. Each night, subjects reported their estimate of the likelihood of a seizure the next day (self-prediction). Logit-normal models with a random subject-specific intercept were used to estimate an OR for the association of precipitants with seizure occurrence. RESULTS: Seventy-one subjects returned 15,179 complete diary days. For each hour of increased sleep on the preceding night, the relative odds of a seizure the following day decreased (OR 0.91, 95{\%} CI 0.82, 0.99). One-unit increments of stress and anxiety (on a 10-point scale) were associated with an increased risk of seizure the following day (OR 1.06, 95{\%} CI 1.01, 1.12 and OR 1.07; 95{\%} CI 1.02, 1.12). With self-prediction included in the model, self-prediction (OR 3.7; 95{\%} CI 1.8, 7.2) and hours of sleep for the night prior to the seizure (OR 0.90; 95{\%} CI 0.82, 0.99) remained significant. CONCLUSION: Lack of sleep and higher self-reported stress and anxiety levels were associated with seizure occurrence. In a model that included self-prediction, less sleep, and self-prediction had significant effects, whereas stress and anxiety did not. The psychological and biologic mechanisms which link stress and anxiety to self-prediction of seizures requires further exploration. Ultimately, seizure prediction based on precipitants, premonitory features, and self-prediction may provide a foundation for preemptive treatment.",
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