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比较用于预测癫痫持续状态患者院内死亡率的评分工具。

Comparison of scoring tools for the prediction of in-hospital mortality in status epilepticus.

机构信息

Department of Neurology, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany.

出版信息

Seizure. 2018 Mar;56:92-97. doi: 10.1016/j.seizure.2018.01.024. Epub 2018 Feb 1.

Abstract

PURPOSE

Several scoring tools have been developed for the prognostication of outcome after status epilepticus (SE). In this study, we compared the performances of STESS (Status Epilepticus Severity Score), mSTESS (modified STESS), EMSE-EAL (Epidemiology-based Mortality Score in Status Epilepticus- Etiology, Age, Level of Consciousness) and END-IT (Encephalitis-NCSE-Diazepam resistance-Image abnormalities-Tracheal intubation) in predicting in-hospital mortality after SE.

METHOD

Data collected retrospectively from a cohort of 287 patients with SE were used to calculate STESS, mSTESS, EMSE-EAL, and END-IT scores. The differences between the scores' performances were determined by means of area under the ROC curve (AUC) comparisons and McNemar testing.

RESULTS

The in-hospital mortality rate was 11.8%. The AUC of STESS (0.628; 95% confidence interval (CI), 0.529-0.727) was similar to that of mSTESS (0.620; 95% CI, 0.510-0.731), EMSE-EAL (0.556; 95% CI, 0.446-0.665), and END-IT (0.659; 95% CI, 0.550-0.768; p > .05 for each comparison) in predicting in-hospital mortality. STESS with a cutoff of 3 was found to have lowest specificity and number of correctly classified episodes. EMSE-EAL with a cutoff at 40 had highest specificity and showed a trend towards more correctly classified episodes while sensitivity tended to be low. END-IT with a cutoff of 3 had the most balanced sensitivity-specificity ratio.

CONCLUSIONS

EMSE-EAL is as easy to calculate as STESS and tended towards higher diagnostic accuracy. Adding information on premorbid functional status to STESS did not enhance outcome prediction. END-IT was not superior to other scores in prediction of in-hospital mortality despite including information of diagnostic work-up and response to initial treatment.

摘要

目的

已经开发了几种评分工具来预测癫痫持续状态(SE)后的预后。在本研究中,我们比较了 STESS(癫痫持续状态严重程度评分)、mSTESS(改良 STESS)、EMSE-EAL(基于病因、年龄、意识水平的癫痫持续状态死亡率评分)和 END-IT(脑炎-NCSE-地西泮耐药-异常影像-气管插管)在预测 SE 后院内死亡率的表现。

方法

使用回顾性收集的 287 例 SE 患者的数据计算 STESS、mSTESS、EMSE-EAL 和 END-IT 评分。通过 ROC 曲线下面积(AUC)比较和 McNemar 检验确定评分表现的差异。

结果

院内死亡率为 11.8%。STESS 的 AUC(0.628;95%置信区间[CI],0.529-0.727)与 mSTESS(0.620;95%CI,0.510-0.731)、EMSE-EAL(0.556;95%CI,0.446-0.665)和 END-IT(0.659;95%CI,0.550-0.768)相似,在预测院内死亡率方面(每种比较的 p 值均大于 0.05)。发现 STESS 的截断值为 3 时具有最低的特异性和正确分类的发作次数。EMSE-EAL 的截断值为 40 时具有最高的特异性,且具有更多正确分类的发作趋势,而敏感性往往较低。END-IT 的截断值为 3 时具有最平衡的敏感性-特异性比。

结论

EMSE-EAL 与 STESS 一样易于计算,且倾向于更高的诊断准确性。向 STESS 添加发病前功能状态的信息并未增强预后预测。尽管 END-IT 包括诊断评估和初始治疗反应的信息,但在预测院内死亡率方面并不优于其他评分。

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