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Risk factors for comorbid epilepsy in patients with psychogenic non-epileptic seizures. Dataset of a large cohort study
Psychogenic non-epileptic seizures (PNES) are the main differential diagnosis of pharmacorresistant epilepsy. Achieving the certainty in the diagnosis of PNES may be challenging, especially in the 10-22% of cases in which PNES and epilepsy co-exist. This difficulty hampers the management of these pa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9489491/ https://www.ncbi.nlm.nih.gov/pubmed/36160062 http://dx.doi.org/10.1016/j.dib.2022.108568 |
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author | Massot-Tarrús, Andreu Yu, Yeyao Joe AlKhateeb, Mashael Mirsattari, Seyed M. |
author_facet | Massot-Tarrús, Andreu Yu, Yeyao Joe AlKhateeb, Mashael Mirsattari, Seyed M. |
author_sort | Massot-Tarrús, Andreu |
collection | PubMed |
description | Psychogenic non-epileptic seizures (PNES) are the main differential diagnosis of pharmacorresistant epilepsy. Achieving the certainty in the diagnosis of PNES may be challenging, especially in the 10-22% of cases in which PNES and epilepsy co-exist. This difficulty hampers the management of these patients. Unfortunately, published series with this combined pathology are scarce and small in size. This article presents the dataset of our article “Factors associated with comorbid epilepsy in patients with psychogenic non-epileptic seizures: a large cohort study” (Massot-Tarrús et al. 2022). It is composed by a detailed demographic and clinical data of 271 consecutive patients diagnosed with PNES in our epilepsy monitoring unit (EMU) between May 2001 and February 2011, and followed until September 2016. Based on the clinical, neuroimaging and vEEG findings, 47 of these patients were diagnosed with definite comorbid epilepsy, and 30 with possible or probable comorbid epilepsy. All data was collected retrospectively from chart review. The cohort is depicted by means of demographic variables; age at PNES onset; years with PNES; frequency of PNES; duration of longest PNES seizure; self-reported history of minor head trauma (not associated with an increased risk of epilepsy) immediately preceding the first PNES; history of substance abuse; past or present history of active suicidal ideation; neuropsychological evaluation with the Minnesota Multiphasic Personality Inventory test; number and nature of risk factors for epilepsy; co-morbid degenerative brain disease or other neurological or psychiatric medical conditions; semiology of the seizures and triggers; EEG findings; type of epilepsy; number of past EMU admissions and epilepsy clinic visits and re-referrals; number of Anti-Seizure Medications (ASM) at EMU admission and discharge; and the outcome of the spells and ASM after the EMU discharge. Those ASM prescribed for reasons other than the treatment of the seizures (e.g., psychiatric disorders, migraine, pain syndromes, etc.) were not counted. The presented baseline data can be used in studies evaluating the characteristics of patients with PNES and comorbid epilepsy, and in the creation of algorithms to identify them. It could facilitate the prioritization of this subgroup of patients for prolonged video-EEG monitorization to confirm the co-existence of both types of seizures and treat them accordingly. |
format | Online Article Text |
id | pubmed-9489491 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-94894912022-09-22 Risk factors for comorbid epilepsy in patients with psychogenic non-epileptic seizures. Dataset of a large cohort study Massot-Tarrús, Andreu Yu, Yeyao Joe AlKhateeb, Mashael Mirsattari, Seyed M. Data Brief Data Article Psychogenic non-epileptic seizures (PNES) are the main differential diagnosis of pharmacorresistant epilepsy. Achieving the certainty in the diagnosis of PNES may be challenging, especially in the 10-22% of cases in which PNES and epilepsy co-exist. This difficulty hampers the management of these patients. Unfortunately, published series with this combined pathology are scarce and small in size. This article presents the dataset of our article “Factors associated with comorbid epilepsy in patients with psychogenic non-epileptic seizures: a large cohort study” (Massot-Tarrús et al. 2022). It is composed by a detailed demographic and clinical data of 271 consecutive patients diagnosed with PNES in our epilepsy monitoring unit (EMU) between May 2001 and February 2011, and followed until September 2016. Based on the clinical, neuroimaging and vEEG findings, 47 of these patients were diagnosed with definite comorbid epilepsy, and 30 with possible or probable comorbid epilepsy. All data was collected retrospectively from chart review. The cohort is depicted by means of demographic variables; age at PNES onset; years with PNES; frequency of PNES; duration of longest PNES seizure; self-reported history of minor head trauma (not associated with an increased risk of epilepsy) immediately preceding the first PNES; history of substance abuse; past or present history of active suicidal ideation; neuropsychological evaluation with the Minnesota Multiphasic Personality Inventory test; number and nature of risk factors for epilepsy; co-morbid degenerative brain disease or other neurological or psychiatric medical conditions; semiology of the seizures and triggers; EEG findings; type of epilepsy; number of past EMU admissions and epilepsy clinic visits and re-referrals; number of Anti-Seizure Medications (ASM) at EMU admission and discharge; and the outcome of the spells and ASM after the EMU discharge. Those ASM prescribed for reasons other than the treatment of the seizures (e.g., psychiatric disorders, migraine, pain syndromes, etc.) were not counted. The presented baseline data can be used in studies evaluating the characteristics of patients with PNES and comorbid epilepsy, and in the creation of algorithms to identify them. It could facilitate the prioritization of this subgroup of patients for prolonged video-EEG monitorization to confirm the co-existence of both types of seizures and treat them accordingly. Elsevier 2022-09-03 /pmc/articles/PMC9489491/ /pubmed/36160062 http://dx.doi.org/10.1016/j.dib.2022.108568 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Massot-Tarrús, Andreu Yu, Yeyao Joe AlKhateeb, Mashael Mirsattari, Seyed M. Risk factors for comorbid epilepsy in patients with psychogenic non-epileptic seizures. Dataset of a large cohort study |
title | Risk factors for comorbid epilepsy in patients with psychogenic non-epileptic seizures. Dataset of a large cohort study |
title_full | Risk factors for comorbid epilepsy in patients with psychogenic non-epileptic seizures. Dataset of a large cohort study |
title_fullStr | Risk factors for comorbid epilepsy in patients with psychogenic non-epileptic seizures. Dataset of a large cohort study |
title_full_unstemmed | Risk factors for comorbid epilepsy in patients with psychogenic non-epileptic seizures. Dataset of a large cohort study |
title_short | Risk factors for comorbid epilepsy in patients with psychogenic non-epileptic seizures. Dataset of a large cohort study |
title_sort | risk factors for comorbid epilepsy in patients with psychogenic non-epileptic seizures. dataset of a large cohort study |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9489491/ https://www.ncbi.nlm.nih.gov/pubmed/36160062 http://dx.doi.org/10.1016/j.dib.2022.108568 |
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