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Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts
OBJECTIVE: In patients with encephalitis, the development of acute symptomatic seizures is highly variable, but when present is associated with a worse outcome. We aimed to determine the factors associated with seizures in encephalitis and develop a clinical prediction model. METHODS: We analysed 20...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9445799/ https://www.ncbi.nlm.nih.gov/pubmed/36110928 http://dx.doi.org/10.1136/bmjno-2022-000323 |
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author | Wood, Greta K Babar, Roshan Ellul, Mark A Thomas, Rhys Huw Van Den Tooren, Harriet Easton, Ava Tharmaratnam, Kukatharmini Burnside, Girvan Alam, Ali M Castell, Hannah Boardman, Sarah Collie, Ceryce Facer, Bethany Dunai, Cordelia Defres, Sylviane Granerod, Julia Brown, David W G Vincent, Angela Marson, Anthony Guy Irani, Sarosh R Solomon, Tom Michael, Benedict D |
author_facet | Wood, Greta K Babar, Roshan Ellul, Mark A Thomas, Rhys Huw Van Den Tooren, Harriet Easton, Ava Tharmaratnam, Kukatharmini Burnside, Girvan Alam, Ali M Castell, Hannah Boardman, Sarah Collie, Ceryce Facer, Bethany Dunai, Cordelia Defres, Sylviane Granerod, Julia Brown, David W G Vincent, Angela Marson, Anthony Guy Irani, Sarosh R Solomon, Tom Michael, Benedict D |
author_sort | Wood, Greta K |
collection | PubMed |
description | OBJECTIVE: In patients with encephalitis, the development of acute symptomatic seizures is highly variable, but when present is associated with a worse outcome. We aimed to determine the factors associated with seizures in encephalitis and develop a clinical prediction model. METHODS: We analysed 203 patients from 24 English hospitals (2005–2008) (Cohort 1). Outcome measures were seizures prior to and during admission, inpatient seizures and status epilepticus. A binary logistic regression risk model was converted to a clinical score and independently validated on an additional 233 patients from 31 UK hospitals (2013–2016) (Cohort 2). RESULTS: In Cohort 1, 121 (60%) patients had a seizure including 103 (51%) with inpatient seizures. Admission Glasgow Coma Scale (GCS) ≤8/15 was predictive of subsequent inpatient seizures (OR (95% CI) 5.55 (2.10 to 14.64), p<0.001), including in those without a history of prior seizures at presentation (OR 6.57 (95% CI 1.37 to 31.5), p=0.025). A clinical model of overall seizure risk identified admission GCS along with aetiology (autoantibody-associated OR 11.99 (95% CI 2.09 to 68.86) and Herpes simplex virus 3.58 (95% CI 1.06 to 12.12)) (area under receiver operating characteristics curve (AUROC) =0.75 (95% CI 0.701 to 0.848), p<0.001). The same model was externally validated in Cohort 2 (AUROC=0.744 (95% CI 0.677 to 0.811), p<0.001). A clinical scoring system for stratifying inpatient seizure risk by decile demonstrated good discrimination using variables available on admission; age, GCS and fever (AUROC=0.716 (95% CI 0.634 to 0.798), p<0.001) and once probable aetiology established (AUROC=0.761 (95% CI 0.6840.839), p<0.001). CONCLUSION: Age, GCS, fever and aetiology can effectively stratify acute seizure risk in patients with encephalitis. These findings can support the development of targeted interventions and aid clinical trial design for antiseizure medication prophylaxis. |
format | Online Article Text |
id | pubmed-9445799 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-94457992022-09-14 Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts Wood, Greta K Babar, Roshan Ellul, Mark A Thomas, Rhys Huw Van Den Tooren, Harriet Easton, Ava Tharmaratnam, Kukatharmini Burnside, Girvan Alam, Ali M Castell, Hannah Boardman, Sarah Collie, Ceryce Facer, Bethany Dunai, Cordelia Defres, Sylviane Granerod, Julia Brown, David W G Vincent, Angela Marson, Anthony Guy Irani, Sarosh R Solomon, Tom Michael, Benedict D BMJ Neurol Open Original Research OBJECTIVE: In patients with encephalitis, the development of acute symptomatic seizures is highly variable, but when present is associated with a worse outcome. We aimed to determine the factors associated with seizures in encephalitis and develop a clinical prediction model. METHODS: We analysed 203 patients from 24 English hospitals (2005–2008) (Cohort 1). Outcome measures were seizures prior to and during admission, inpatient seizures and status epilepticus. A binary logistic regression risk model was converted to a clinical score and independently validated on an additional 233 patients from 31 UK hospitals (2013–2016) (Cohort 2). RESULTS: In Cohort 1, 121 (60%) patients had a seizure including 103 (51%) with inpatient seizures. Admission Glasgow Coma Scale (GCS) ≤8/15 was predictive of subsequent inpatient seizures (OR (95% CI) 5.55 (2.10 to 14.64), p<0.001), including in those without a history of prior seizures at presentation (OR 6.57 (95% CI 1.37 to 31.5), p=0.025). A clinical model of overall seizure risk identified admission GCS along with aetiology (autoantibody-associated OR 11.99 (95% CI 2.09 to 68.86) and Herpes simplex virus 3.58 (95% CI 1.06 to 12.12)) (area under receiver operating characteristics curve (AUROC) =0.75 (95% CI 0.701 to 0.848), p<0.001). The same model was externally validated in Cohort 2 (AUROC=0.744 (95% CI 0.677 to 0.811), p<0.001). A clinical scoring system for stratifying inpatient seizure risk by decile demonstrated good discrimination using variables available on admission; age, GCS and fever (AUROC=0.716 (95% CI 0.634 to 0.798), p<0.001) and once probable aetiology established (AUROC=0.761 (95% CI 0.6840.839), p<0.001). CONCLUSION: Age, GCS, fever and aetiology can effectively stratify acute seizure risk in patients with encephalitis. These findings can support the development of targeted interventions and aid clinical trial design for antiseizure medication prophylaxis. BMJ Publishing Group 2022-09-05 /pmc/articles/PMC9445799/ /pubmed/36110928 http://dx.doi.org/10.1136/bmjno-2022-000323 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Research Wood, Greta K Babar, Roshan Ellul, Mark A Thomas, Rhys Huw Van Den Tooren, Harriet Easton, Ava Tharmaratnam, Kukatharmini Burnside, Girvan Alam, Ali M Castell, Hannah Boardman, Sarah Collie, Ceryce Facer, Bethany Dunai, Cordelia Defres, Sylviane Granerod, Julia Brown, David W G Vincent, Angela Marson, Anthony Guy Irani, Sarosh R Solomon, Tom Michael, Benedict D Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts |
title | Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts |
title_full | Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts |
title_fullStr | Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts |
title_full_unstemmed | Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts |
title_short | Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts |
title_sort | acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9445799/ https://www.ncbi.nlm.nih.gov/pubmed/36110928 http://dx.doi.org/10.1136/bmjno-2022-000323 |
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