Epilepsy & behavior : E&B · 2022
Prevalence, risk factors, and prognosis of drug-resistant epilepsy in autoimmune encephalitis.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Wesselingh Robb, Broadley James, Buzzard Katherine, Tarlinton David, Seneviratne Udaya, Kyndt Chris, Stankovich Jim, Sanfilippo Paul, Nesbitt Cassie, D'Souza Wendyl, Macdonell Richard, Butzkueven Helmut, O'Brien Terence J, Monif Mastura
Аннотация
OBJECTIVE: To evaluate the prevalence and biomarkers of drug-resistant epilepsy (DRE) in patients with autoimmune encephalitis (AIE).
METHODS: Sixty-nine patients with AIE were recruited retrospectively and electroencephalographies (EEGs) were reviewed using a standard reporting proforma. Associations between EEG biomarkers and DRE development at 12 months were examined using logistic regression modeling and were utilized to create a DRE risk score.
RESULTS: Sixteen percent of patients with AIE developed DRE at 12-month follow-up. The presence of status epilepticus (SE) (OR 11.50, 95% CI [2.81, 51.86], p-value <0.001), temporal lobe focality (OR 9.90, 95% CI [2.60, 50.71], p-value 0.001) and periodic discharges (OR 19.12, 95% CI [3.79, 191.10], p-value 0.001) on the admission EEG were associated with the development of DRE at 12 months. These variables were utilized to create a clinically applicable risk score for the prediction of DRE development.
CONCLUSIONS: Drug-resistant epilepsy is an infrequent complication of AIE. Electroencephalography changes during the acute illness can predict the risk of DRE at 12 months post-acute AIE.
SIGNIFICANCE: The identified EEG biomarkers provide the basis to generate a clinically applicable prediction tool which could be used to inform treatment, prognosis, and select patients for acute treatment trials.
METHODS: Sixty-nine patients with AIE were recruited retrospectively and electroencephalographies (EEGs) were reviewed using a standard reporting proforma. Associations between EEG biomarkers and DRE development at 12 months were examined using logistic regression modeling and were utilized to create a DRE risk score.
RESULTS: Sixteen percent of patients with AIE developed DRE at 12-month follow-up. The presence of status epilepticus (SE) (OR 11.50, 95% CI [2.81, 51.86], p-value <0.001), temporal lobe focality (OR 9.90, 95% CI [2.60, 50.71], p-value 0.001) and periodic discharges (OR 19.12, 95% CI [3.79, 191.10], p-value 0.001) on the admission EEG were associated with the development of DRE at 12 months. These variables were utilized to create a clinically applicable risk score for the prediction of DRE development.
CONCLUSIONS: Drug-resistant epilepsy is an infrequent complication of AIE. Electroencephalography changes during the acute illness can predict the risk of DRE at 12 months post-acute AIE.
SIGNIFICANCE: The identified EEG biomarkers provide the basis to generate a clinically applicable prediction tool which could be used to inform treatment, prognosis, and select patients for acute treatment trials.