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Characteristics of large patient‐reported outcomes: Where can one million seizures get us?

OBJECTIVE: To analyze data from Seizure Tracker, a large electronic seizure diary, including comparison of seizure characteristics among different etiologies, temporal patterns in seizure fluctuations, and specific triggers. METHODS: Zero‐inflated negative binomial mixed‐effects models were used to...

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Autores principales: Ferastraoaru, Victor, Goldenholz, Daniel M., Chiang, Sharon, Moss, Robert, Theodore, William H., Haut, Sheryl R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6119749/
https://www.ncbi.nlm.nih.gov/pubmed/30187007
http://dx.doi.org/10.1002/epi4.12237
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author Ferastraoaru, Victor
Goldenholz, Daniel M.
Chiang, Sharon
Moss, Robert
Theodore, William H.
Haut, Sheryl R.
author_facet Ferastraoaru, Victor
Goldenholz, Daniel M.
Chiang, Sharon
Moss, Robert
Theodore, William H.
Haut, Sheryl R.
author_sort Ferastraoaru, Victor
collection PubMed
description OBJECTIVE: To analyze data from Seizure Tracker, a large electronic seizure diary, including comparison of seizure characteristics among different etiologies, temporal patterns in seizure fluctuations, and specific triggers. METHODS: Zero‐inflated negative binomial mixed‐effects models were used to evaluate temporal patterns of seizure events (during the day or week), as well as group differences in monthly seizure frequency between children and adults and between etiologies. The association of long seizures with seizure triggers was evaluated using a mixed‐effects logistic model with subject as the random effect. Incidence rate ratios (IRRs) and odds ratios were reported for analyses involving zero‐inflated negative binomial and logistic mixed‐effects models, respectively. RESULTS: A total of 1,037,909 seizures were logged by 10,186 subjects (56.7% children) from December 2007 to January 2016. Children had more frequent seizures than adults did (median monthly seizure frequency 3.5 vs. 2.7, IRR 1.26; p < 0.001). Seizures demonstrated a circadian pattern (higher frequency between 07:00 a.m. and 10:00 a.m. and lower overnight), and seizures were reported differentially across the week (seizure rates higher Monday through Friday than Saturday or Sunday). Longer seizures (>5 or >30 min) had a higher proportion of the following triggers when compared with shorter seizures: “Overtired or irregular sleep,” “Bright or flashing lights,” and “Emotional stress” (p < 0.004). SIGNIFICANCE: This study explored a large cohort of patients with self‐reported seizures; strengths and limitations of large seizure diary databases are discussed. The findings in this study are consistent with those of prior work in smaller validated cohorts, suggesting that patient‐recorded databases are a valuable resource for epilepsy research, capable of both replication of results and generation of novel hypotheses.
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spelling pubmed-61197492018-09-05 Characteristics of large patient‐reported outcomes: Where can one million seizures get us? Ferastraoaru, Victor Goldenholz, Daniel M. Chiang, Sharon Moss, Robert Theodore, William H. Haut, Sheryl R. Epilepsia Open Full‐length Original Research OBJECTIVE: To analyze data from Seizure Tracker, a large electronic seizure diary, including comparison of seizure characteristics among different etiologies, temporal patterns in seizure fluctuations, and specific triggers. METHODS: Zero‐inflated negative binomial mixed‐effects models were used to evaluate temporal patterns of seizure events (during the day or week), as well as group differences in monthly seizure frequency between children and adults and between etiologies. The association of long seizures with seizure triggers was evaluated using a mixed‐effects logistic model with subject as the random effect. Incidence rate ratios (IRRs) and odds ratios were reported for analyses involving zero‐inflated negative binomial and logistic mixed‐effects models, respectively. RESULTS: A total of 1,037,909 seizures were logged by 10,186 subjects (56.7% children) from December 2007 to January 2016. Children had more frequent seizures than adults did (median monthly seizure frequency 3.5 vs. 2.7, IRR 1.26; p < 0.001). Seizures demonstrated a circadian pattern (higher frequency between 07:00 a.m. and 10:00 a.m. and lower overnight), and seizures were reported differentially across the week (seizure rates higher Monday through Friday than Saturday or Sunday). Longer seizures (>5 or >30 min) had a higher proportion of the following triggers when compared with shorter seizures: “Overtired or irregular sleep,” “Bright or flashing lights,” and “Emotional stress” (p < 0.004). SIGNIFICANCE: This study explored a large cohort of patients with self‐reported seizures; strengths and limitations of large seizure diary databases are discussed. The findings in this study are consistent with those of prior work in smaller validated cohorts, suggesting that patient‐recorded databases are a valuable resource for epilepsy research, capable of both replication of results and generation of novel hypotheses. John Wiley and Sons Inc. 2018-07-04 /pmc/articles/PMC6119749/ /pubmed/30187007 http://dx.doi.org/10.1002/epi4.12237 Text en © 2018 The Authors. Epilepsia Open published by Wiley Periodicals Inc. on behalf of International League Against Epilepsy. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Full‐length Original Research
Ferastraoaru, Victor
Goldenholz, Daniel M.
Chiang, Sharon
Moss, Robert
Theodore, William H.
Haut, Sheryl R.
Characteristics of large patient‐reported outcomes: Where can one million seizures get us?
title Characteristics of large patient‐reported outcomes: Where can one million seizures get us?
title_full Characteristics of large patient‐reported outcomes: Where can one million seizures get us?
title_fullStr Characteristics of large patient‐reported outcomes: Where can one million seizures get us?
title_full_unstemmed Characteristics of large patient‐reported outcomes: Where can one million seizures get us?
title_short Characteristics of large patient‐reported outcomes: Where can one million seizures get us?
title_sort characteristics of large patient‐reported outcomes: where can one million seizures get us?
topic Full‐length Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6119749/
https://www.ncbi.nlm.nih.gov/pubmed/30187007
http://dx.doi.org/10.1002/epi4.12237
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