Evaluation of STESS, mRSTESS, and EMSE to Predict High Disability and Mortality at Hospital Discharge in Ecuadorian Patients with Status Epilepticus.

BACKGROUND

Adequate identification of the severity of status epilepticus (SE) contributes to individualized treatment. The scales most widely used for this purpose are: Status Epilepticus Severity Score (STESS), Epidemiology-Based Mortality Score in Status Epilepticus (EMSE) and modified Rankin Scale STESS (mRSTESS). The aim of this study was to evaluate the performance of the STESS, EMSE and mRSTESS scales to predict high disability and hospital mortality at discharge (HD/HM).

METHODS

A prospective study was conducted in which total of 41 patients were registered from November 2015 to January 2018 at Eugenio Espejo Hospital. Clinical variables such as age, sex, clinical status at the beginning of the SE, initial symptom of SE, as well as the STESS, mRSTESS and EMSE variant scales were studied at the time of the diagnosis of SE.

RESULTS

A total of 41 patients were evaluated, of which 8 (19.5%) had HD at hospital discharge and died 13 (31.7%) during their care. The area under the receiver operating characteristic curve to predict HD/HM was 0.71 (95% CI (confidence interval) 0.55-0.87), 0.81 (95% CI 0.67-0.94), 0.89 (95% CI 0.79-0.99), 0.90 (95% CI 0.80-1.0), 0.89 (95% CI 0.78-0.99) for the STESS, mRSTESS, EMSE-EAC (etiology, age, comorbidities), EMSE-EACEG (etiology, age, comorbidities, electroencephalography) and EMSE-ECLEG (etiology, age, level of consciousness at pre-treatment, electroencephalography), variants of EMSE, respectively. The binary logistic regression demonstrated how the following cut-off points were determined: STESS OR (odd ratio) 4.80 (p = 0.02), mRSTESS OR 7.89 (p = 0.00), EMSE-EAC OR 22.16 (p = 0.00), EMSE-ECLEG OR 18.00 (p = 0.00), EMSE-EACEG OR 14 (p = 0.00).

CONCLUSIONS

All of the evaluated scales (STESS, mRSTESS, and EMSE) were shown to be useful in predicting HD/HM. EMSE was observed to be the most effective of the scales, with relative similarities among the variants.