Prediction of mortality using Chinese version of epidemiology-based mortality score in status epilepticus (EMSE)

Abstract

Objective To study the value of epidemiology-based mortality score, a novel scoring system, in in-hospital adult patients with status epilepticus (SE) for predicting mortality, and to compare it with the status epilepticus severity score (STESS). Methods The clinical and electroencephalography data of 54 adult patients with SE admitted from June 2013 to June 2016 were derived from a prospective SE database of Zhejiang Provincial Hospital of Traditional Chinese Medicine. The outcome was defined as in-hospital death or survival at discharge. When the receiver-operating characteristic (ROC) curves were made, the area under ROC (AUC) and the optimal cutoff value were calculated. Fisher’s linear discriminant function analysis was conducted with the outcome as dependent variable and the scores as independent variables. Results Among 54 patients with SE recruited into the study, 13 (24.10 %) died in the hospital. The ROC curve for prediction of in-hospital death based on the STESS had a AUC of 0.705 with an optimal cutoff value for discrimination (best match for both sensitivity (0.77) and specificity (0.56) to be ≥3 points. The AUC based on the EMSE was 0.800 with an optimal cutoff value for discrimination (best match for both sensitivity (0.92) and specificity (0.61) to be ≥79 points. Three elements added in combination with EMSE system (etiology-age-comorbidity, EMSE-EAC) predicted in-hospital mortality with the best match for both sensitivity (1.00) and specificity (0.56) as the optimal cutoff point was ≥32 points, and the AUC was 0.814. Four elements added in combination with EMSE system (etiology-age-comorbidity-EEG, EMSE-EACE) predicted in-hospital mortality with the best match for both sensitivity (0.77) and specificity (0.98) as the optimal cutoff point was ≥71 points with an AUC of 0.925. The AUC of EMSE-EACE was larger than that of both STESS and EMSE (Both P<0.01). Discriminant equations were found by Fisher linear discriminant analysis. The rates of accuracy of the equation for predicting patients’ prognosis were 44.44% (STESS), 62.96% (EMSE), 70.37% (EMSE-EAC) and 81.48% (EMSE-EACE) respectively, suggesting that the equations of EMSE, EMSE-EAC and EMSE-EACE have superior stability. Conclusions The EMSE is an effective clinical scoring system that focuses on individual mortality. EMSE-EACE is superior over both STESS and EMSE in the prediction of in-hospital death. Key words: Status epilepticus; Mortality; Outcome; Predictive value; Epidemiology-based mortality score in status epilepticus; Status epilepticus severity score; Receiver-operating characteristic curves; Discriminant analysis