TY - JOUR
T1 - Seizure self-prediction in a randomized controlled trial of stress management
AU - Privitera, Michael
AU - Haut, Sheryl R.
AU - Lipton, Richard B.
AU - McGinley, James S.
AU - Cornes, Susannah
N1 - Funding Information:
S.R. Haut serves on the editorial board of Epilepsy and Behavior; received unrestricted grant support from the Charles L. Shor Foundation for Epilepsy Research; serves/served as consultant for Acorda, Upsher Smith, Siga, Neurelis, and Xeris; and received compensation for expert testimony for a legal proceeding (Pesce vs NYPD). R.B. Lipton is the Edwin S. Lowe Professor of Neurology at the Albert Einstein College of Medicine in New York; receives research support from the NIH: 2PO1 AG003949 (Program Director), 5U10 NS077308 (PI), 1RO1 AG042595 (Investigator), RO1 NS082432 (Investigator), K23 NS09610 (Mentor), K23AG049466 (Mentor); receives support from the Migraine Research Foundation and the National Headache Foundation;servesontheeditorialboardofNeurology® and as senior advisor to Headache; has reviewed for the NIA and NINDS; holds stock options in eNeura Therapeutics; serves as consultant, advisory board member, or has received honoraria from American Academy of Neurology, Alder, Allergan,
Funding Information:
This study was supported by unrestricted grants from the Charles L. Shor Foundation for Epilepsy Research and Epilepsy Foundation.
Funding Information:
American Headache Society, Amgen, Autonomic Technologies, Avanir, Biohaven, Biovision, Boston Scientific, Colucid, Dr. Reddy’s, Electrocore, Eli Lilly, eNeura Therapeutics, GlaxoSmithKline, Merck, Pernix, Pfizer, Supernus, Teva, Trigemina, Vector, and Vedanta; and receives royalties from Wolff’s Headache, 8th edition, Oxford Press University, 2009, Wiley, and Informa. S. Cornes reports no disclosures relevant to the manuscript. M. Privitera receives research funding from NIH 2U01NS038455-11A1, Epilepsy Foundation, GW Pharmaceuticals, UCB, and Sage; received unrestricted grant support from the Charles L. Shor Foundation for Epilepsy Research; and serves as a consultant for Astellas and Sun. J.S. McGinley is an employee of Vector Psychometric Group, LLC. Go to Neurology.org/N for full disclosures.
Publisher Copyright:
© American Academy of Neurology.
PY - 2019/11/26
Y1 - 2019/11/26
N2 - ObjectiveUsing electronic diaries as part of a randomized controlled trial of stress reduction for epilepsy, we evaluated factors associated with successful seizure self-prediction.MethodsAdults with medication-resistant focal epilepsy were recruited from 3 centers and randomized to treatment with progressive muscle relaxation or control focused attention. An 8-week baseline was followed by 12 weeks of double-blind treatment. Twice daily, participants rated the likelihood of a seizure in the next 24 hours on a 5-point scale from very unlikely to almost certain, along with mood, premonitory symptoms, stress ratings, and seizure counts. We analyzed the association of mood, premonitory symptoms, stress, and circadian influences on seizure self-prediction.ResultsSixty-four participants completed the trial (3,126 seizures). Diary entry adherence was >82%. Participant self-prediction was associated with seizure occurrence at 6, 12, and 24 hours (p < 0.0001). Odds ratio (OR) of seizure prediction increased systematically with participants' prediction of seizure likelihood (p < 0.0001, all levels of prediction and all time intervals). For the 12-hour prediction window, median specificity for seizure prediction was 0.94 and negative predictive value 0.94; median sensitivity was 0.10 and positive predictive value 0.13. A subset of 13 participants (20% of sample) met criteria for good predictors (median OR for seizure prediction 5.25). Mood, stress, premonitory symptoms, seizure time, and randomized group were not associated with seizure occurrence.ConclusionIn this prospective study, participants' prediction of a high probability of seizure was significantly associated with subsequent seizure occurrence within 24 hours. Future studies should focus on understanding factors that drive self-prediction.Clinicaltrials.gov identifierNCT01444183.
AB - ObjectiveUsing electronic diaries as part of a randomized controlled trial of stress reduction for epilepsy, we evaluated factors associated with successful seizure self-prediction.MethodsAdults with medication-resistant focal epilepsy were recruited from 3 centers and randomized to treatment with progressive muscle relaxation or control focused attention. An 8-week baseline was followed by 12 weeks of double-blind treatment. Twice daily, participants rated the likelihood of a seizure in the next 24 hours on a 5-point scale from very unlikely to almost certain, along with mood, premonitory symptoms, stress ratings, and seizure counts. We analyzed the association of mood, premonitory symptoms, stress, and circadian influences on seizure self-prediction.ResultsSixty-four participants completed the trial (3,126 seizures). Diary entry adherence was >82%. Participant self-prediction was associated with seizure occurrence at 6, 12, and 24 hours (p < 0.0001). Odds ratio (OR) of seizure prediction increased systematically with participants' prediction of seizure likelihood (p < 0.0001, all levels of prediction and all time intervals). For the 12-hour prediction window, median specificity for seizure prediction was 0.94 and negative predictive value 0.94; median sensitivity was 0.10 and positive predictive value 0.13. A subset of 13 participants (20% of sample) met criteria for good predictors (median OR for seizure prediction 5.25). Mood, stress, premonitory symptoms, seizure time, and randomized group were not associated with seizure occurrence.ConclusionIn this prospective study, participants' prediction of a high probability of seizure was significantly associated with subsequent seizure occurrence within 24 hours. Future studies should focus on understanding factors that drive self-prediction.Clinicaltrials.gov identifierNCT01444183.
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U2 - 10.1212/WNL.0000000000008539
DO - 10.1212/WNL.0000000000008539
M3 - Article
C2 - 31645468
AN - SCOPUS:85075812722
VL - 93
SP - E2021-E2031
JO - Neurology
JF - Neurology
SN - 0028-3878
IS - 22
ER -