Prediction of functional outcome in patients with convulsive status epilepticus: the END-IT score

• Published in: Critical care (London, England) Vol. 20; no. 45; p. 46
• Main Authors: Gao, Qiong, Ou-Yang, Tang-peng, Sun, Xiao-long, Yang, Feng, Wu, Chen, Kang, Tao, Kang, Xiao-gang, Jiang, Wen
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 25.02.2016; BioMed Central
• Subjects: Activities of daily living; Adolescent; Adult; Care and treatment; China; Complications and side effects; Critical care; Female; Forecasting - methods; Humans; Male; Middle Aged; Patient Outcome Assessment; Patient outcomes; Prognosis; Prospective Studies; Retrospective Studies; Severity of Illness Index; Status epilepticus; Status Epilepticus - mortality; Survival Analysis; Treatment Outcome; China
• ISSN: 1364-8535; 1466-609X; 1364-8535; 1366-609X
• DOI: 10.1186/s13054-016-1221-9

Prediction of the functional outcome for patients with convulsive status epilepticus (CSE) has been a challenge. The aim of this study was to characterize the prognostic factors and functional outcomes of patients after CSE in order to develop a practicable scoring system for outcome prediction. We performed a retrospective explorative analysis on consecutive patients diagnosed with CSE between March, 2008 and November, 2014 in a tertiary academic medical center in northwest China. The modified Rankin Scale (mRS) was used to measure the functional outcome at three months post discharge. A total of 132 CSE patients was included, with a median age of 25.5 years and 60.6% were male. Three months post discharge, an unfavorable outcome with mRS of 3-6 was seen in 62 (47.0%) patients, 25 (18.9%) of whom died. Logistic regression analysis revealed that encephalitis (p = 0.029), nonconvulsive SE (p = 0.018), diazepam resistance (p = 0.005), image abnormalities (unilateral lesions, p = 0.027; bilateral lesions or diffuse cerebral edema, p < 0.001) and tracheal intubation (p = 0.032) were significant independent predictors for unfavorable outcomes. Based on the coefficients in the model, these predictors were assigned a value of 1 point each, with the exception of the image, creating a 6-point scoring system, which we refer to as END-IT, for the outcome prediction of CSE. The area under the receiver operating characteristic curve for the END-IT score was 0.833 and using a cut-off point of 3 produced the highest sum sensitivity (83.9%) and specificity (68.6%). Compared with status epilepticus severity score (STESS) and Epidemiology-based Mortality score in SE (EMSE), END-IT score showed better discriminative power and predictive accuracy for the outcome prediction. We developed an END-IT score with a strong discriminative power for predicting the functional outcome of CSE patients. External prospective validation in different cohorts is needed for END-IT score.