Clinic for Intensive Care Medicine, University Hospital Basel, Basel, Switzerland.
Department of Neurology, University Hospital Basel, Basel, Switzerland.
Epilepsia. 2019 Jan;60(1):42-52. doi: 10.1111/epi.14603. Epub 2018 Nov 22.
Early identification of patients who are at risk of prolonged status epilepticus (SE) and patients with high chances of full recovery despite prolonged SE may urge clinicians to intensify treatment rather than to withdraw care. We aimed to develop prediction models based on readily available clinical parameters to predict prolonged SE at seizure onset and to identify patients with high chances for full recovery.
From 2005 to 2016, all adult SE patients treated at the University Hospital Basel, a Swiss medical care center, were included. Multivariable Poisson regression was performed to identify predictors of prolonged SE (defined as SE for >12, >24, and >48 hours) and return to baseline from prolonged SE. The area under the receiver-operating characteristic curves (AUROC) for prediction models was calculated.
Of 467 patients, the median age was 66.7 years and mortality was 12%. Relative risk (RR) for death was 1.06 (P < 0.0001) with every SE day. In multivariable analysis, nonconvulsive SE with coma, SE severity score ≥3, and acute brain lesions at SE onset independently predicted prolonged SE with an AUROC of 0.68 for >12, 0.67 for >24, and 0.72 for >48 hours of SE. Absence of nonconvulsive SE with coma and a decreasing Charlson comorbidity index were independent predictors for return to baseline in prolonged SE with an AUROC of 0.82 and 0.76 following cross-validation. Both associations remained significant despite adjustments for determinants of adverse outcome, such as anesthetics and vasopressors (nonconvulsive SE with coma RR = 0.24, 95% confidence interval [CI] 0.07-0.86; comorbidity index RR = 0.87, 95% CI 0.76-0.99).
Although our data indicate that identification of prolonged SE at seizure onset is unreliable, timely recognition of patients with high chances of good outcome despite prolonged SE is promising on the basis of comorbidities, type of SE, and level of consciousness. Further external validation of this prediction model is needed.
早期识别有癫痫持续状态（SE）延长风险的患者和尽管 SE 延长但有很大机会完全恢复的患者，可能促使临床医生加强治疗而不是停止治疗。我们旨在基于易于获得的临床参数建立预测模型，以预测发作时的 SE 延长，并识别有完全恢复高几率的患者。
从 2005 年至 2016 年，纳入瑞士医疗中心巴塞尔大学医院治疗的所有成年 SE 患者。使用多变量泊松回归来确定 SE 延长（定义为 SE 持续时间>12、>24 和>48 小时）和从 SE 延长中恢复到基线的预测因子。计算预测模型的受试者工作特征曲线下面积（AUROC）。
在 467 名患者中，中位年龄为 66.7 岁，死亡率为 12%。SE 每持续一天，死亡的相对风险（RR）为 1.06（P<0.0001）。多变量分析显示，非惊厥性 SE 伴昏迷、SE 严重程度评分≥3 和 SE 发作时的急性脑病变是 SE 延长的独立预测因素，AUROC 分别为>12 小时的 0.68、>24 小时的 0.67 和>48 小时的 0.72。无非惊厥性 SE 伴昏迷和逐渐降低的 Charlson 合并症指数是 SE 延长后恢复到基线的独立预测因素，经交叉验证的 AUROC 分别为 0.82 和 0.76。尽管调整了麻醉剂和加压素等不良预后决定因素，这些关联仍然具有统计学意义（非惊厥性 SE 伴昏迷 RR=0.24，95%置信区间 [CI] 0.07-0.86；合并症指数 RR=0.87，95% CI 0.76-0.99）。
尽管我们的数据表明在发作时识别 SE 延长是不可靠的，但根据合并症、SE 类型和意识水平，及时识别有很大机会获得良好结局的患者是有希望的。需要进一步对该预测模型进行外部验证。
