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Published on: February 22, 2020
Prediction of functional outcome in patients with convulsive status epilepticus: the END-IT score
Qiong Gao1, Tang-peng Ou-Yang2, Xiao-long Sun3
1Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, PR China. gaoqq0513@163.com.
Background:
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.
Methods:
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.
Results:
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.
Conclusions:
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.
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