Modeling Seizure Self-Prediction: An E-Diary Study

Details

• Alternative Title:
  Epilepsia
• Personal Author:
  Haut, Sheryl R. ; Hall, Charles B. ; Borkowski, Thomas ; Tennen, Howard ; Lipton, Richard B.
• Description:
  Purpose
  
  A subset of patients with epilepsy successfully self-predicted seizures in a paper diary study. We conducted an e-diary study to ensure that prediction precedes seizures, and to characterize the prodromal features and time windows that underlie self-prediction.
  
  Methods
  
  Subjects 18 or older with LRE and ≥3 seizures/month maintained an e-diary, reporting AM/PM data daily, including mood, premonitory symptoms, and all seizures. Self-prediction was rated by, “How likely are you to experience a seizure [time frame]”? Five choices ranged from almost certain (>95% chance) to very unlikely. Relative odds of seizure (OR) within time frames was examined using Poisson models with log normal random effects to adjust for multiple observations.
  
  Key Findings
  
  Nineteen subjects reported 244 eligible seizures. OR for prediction choices within 6hrs was as high as 9.31 (1.92,45.23) for “almost certain”. Prediction was most robust within 6hrs of diary entry, and remained significant up to 12hrs. For 9 best predictors, average sensitivity was 50%. Older age contributed to successful self-prediction, and self-prediction appeared to be driven by mood and premonitory symptoms. In multivariate modeling of seizure occurrence, self-prediction (2.84; 1.68,4.81), favorable change in mood (0.82; 0.67,0.99) and number of premonitory symptoms (1,11; 1.00,1.24) were significant.
  
  Significance
  
  Some persons with epilepsy can self-predict seizures. In these individuals, the odds of a seizure following a positive prediction are high. Predictions were robust, not attributable to recall bias, and were related to self awareness of mood and premonitory features. The 6-hour prediction window is suitable for the development of pre-emptive therapy.
  
  
• Subjects:
  Adolescent Adult Affect Article Child Diagnostic Self Evaluation Electroencephalography Electronic Diary Female Humans Localization-related Epilepsy Male Odds Ratio Premonitory Symptoms Seizure Diary Seizure Precipitants Seizure Prediction Seizures Self-prediction Time Factors Young Adult

  More +
• Source:
  Epilepsia. 54(11):1960-1967.
• Pubmed ID:
  24111898
• Pubmed Central ID:
  PMC3833277
• Document Type:
  Journal Article
• Funding:
  1R01DA031275-01A1/DA/NIDA NIH HHS/United States ; 5P60AA003510-33/AA/NIAAA NIH HHS/United States ; 5R01AA016599-03/AA/NIAAA NIH HHS/United States ; 5R01AA12827-07/AA/NIAAA NIH HHS/United States ; K23AG030857/AG/NIA NIH HHS/United States ; K23NS05140901A1/NS/NINDS NIH HHS/United States ; K23NS47256/NS/NINDS NIH HHS/United States ; P01 AG003949/AG/NIA NIH HHS/United States ; P01 AG027734/AG/NIA NIH HHS/United States ; P01 AG03949/AG/NIA NIH HHS/United States ; P30 CA13330-35/CA/NCI NIH HHS/United States ; R01 AG022092/AG/NIA NIH HHS/United States ; R01 AG034087/AG/NIA NIH HHS/United States ; R01 NS053998/NS/NINDS NIH HHS/United States ; R01AG022374-06A2/AG/NIA NIH HHS/United States ; R01AG025119/AG/NIA NIH HHS/United States ; R01AG034119/AG/NIA NIH HHS/United States ; R01AG12101/AG/NIA NIH HHS/United States ; R21 AG036935/AG/NIA NIH HHS/United States ; U01-OH10411/OH/NIOSH CDC HHS/United States ; U01-OH10412/OH/NIOSH CDC HHS/United States ; UL1-RR025750-01/RR/NCRR NIH HHS/United States
• Volume:
  54
• Issue:
  11
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:157faf1bcbf34cc3bf41d413ad1f88df12a735ec1f7060e37d697afe79403ef5
• Download URL:
  https://stacks.cdc.gov/view/cdc/29779/cdc_29779_DS1.pdf
• File Type:
  [PDF - 955.60 KB ]