Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts

Wood, GK; Babar, R; Ellul, MA; Thomas, RH; Van Den Tooren, H; Easton, A; Tharmaratnam, K; Burnside, G; Alam, AM; Castell, H; Boardman, S; Collie, C; Facer, B; Dunai, C; Defres, S; Granerod, J; Brown, DWG; Vincent, A; Marson, AG; Irani, SR; Solomon, T; Michael, BD

Journal article

Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts

Abstract:: 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.

Publication status:: Published

Peer review status:: Peer reviewed

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APA Style

Wood, G. K., Babar, R., Ellul, M. A., Thomas, R. H., Van Den Tooren, H., Easton, A., Tharmaratnam, K., Burnside, G., Alam, A. M., Castell, H., Boardman, S., Collie, C., Facer, B., Dunai, C., Defres, S., Granerod, J., Brown, D. W. G., Vincent, A., Marson, A. G., … Michael, B. D. (2022). Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts. BMJ Open Neurology, 4(2).

MLA Style

Wood, G. K., et al. “Acute Seizure Risk in Patients with Encephalitis: Development and Validation of Clinical Prediction Models from Two Independent Prospective Multicentre Cohorts.” BMJ Open Neurology, vol. 4, no. 2, BMJ Publishing Group, 2022.

Chicago Style

Wood, GK, R Babar, MA Ellul, RH Thomas, H Van Den Tooren, A Easton, K Tharmaratnam, et al. 2022. “Acute Seizure Risk in Patients with Encephalitis: Development and Validation of Clinical Prediction Models from Two Independent Prospective Multicentre Cohorts.” BMJ Open Neurology 4 (2).
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