Prediction of functional outcome in patients with convulsive status epilepticus: the END-IT score.
Prediction of functional outcome in patients with convulsive status epilepticus: the END-IT score.
复制标题
惊厥性癫痫持续状态患者功能结果的预测：END-IT 评分
DOI：
10.1186/s13054-016-1221-9
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发表时间：
2016-02-25
期刊：
影响因子：
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通讯作者：
Jiang W
中科院分区：
文献类型：
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作者：
Gao Q;Ou-Yang TP;Sun XL;Yang F;Wu C;Kang T;Kang XG;Jiang W
背景：预测惊厥性癫痫持续状态（CSE）患者的功能结局一直是一个挑战。本研究的目的是描述CSE后患者的预后因素和功能结果，以便开发一种实用的评分系统来预测结果。方法对2008年3月至2014年11月在西北某三级学术医疗中心连续诊断为CSE的患者进行回顾性探索性分析。采用改良Rankin量表（mRS）测量出院后3个月的功能结局。结果共纳入132例CSE患者，中位年龄25.5岁，男性占60.6%。出院后3个月，62例（47.0%）患者出现不良预后，mRS为3-6，其中25例（18.9%）死亡。Logistic回归分析显示，脑炎（p= 0.029）、非惊厥性SE （p= 0.018）、地西泮耐药性（p= 0.005）、图像异常（单侧病变，p= 0.027；双侧病变或弥漫性脑水肿，p< 0.001）和气管插管（p= 0.032）是不良结局的显著独立预测因素。根据模型中的系数，这些预测因子被赋予1分的值，除了图像，创建一个6分的评分系统，我们称之为END-IT，用于CSE的结果预测。END-IT评分的受试者工作特征曲线下面积为0.833，使用截断点3产生最高的总灵敏度（83.9%）和特异性（68.6%）。与癫痫持续状态严重程度评分（ess）和SE中基于流行病学的死亡率评分（EMSE）相比，END-IT评分在预测预后方面具有更好的判别能力和预测准确性。结论：我们开发了一种END-IT评分，对预测CSE患者的功能结局具有很强的判别能力。END-IT评分需要在不同队列中进行外部前瞻性验证。
BackgroundPrediction 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.MethodsWe 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.ResultsA 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.ConclusionsWe 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.