Comparison of the status epilepticus severity score and the epidemiology-based mortality score in predicting 30-day mortality and status epilepticus cessation.
Epilepsy Behav
; 147: 109388, 2023 Oct.
Article
em En
| MEDLINE
| ID: mdl-37625347
ABSTRACT
OBJECTIVE:
To evaluate the role of the Status Epilepticus Severity Score (STESS) and the Epidemiology-based Mortality score (EMSE) in predicting 30-day mortality and SE (Status epilepticus) cessation, and their prognostic performance in subgroups of patients with specific characteristics.METHODS:
We reviewed consecutive episodes of SE occurring in patients aged ≥14 years at Baggiovara Civil Hospital (Modena, Italy) from 2013 to 2021. We evaluated the predictive accuracy of EMSE and STESS for 30-day mortality and SE cessation through stepwise regression binary logistic models adjusted for possible univariate clinical confounders.RESULTS:
Seven hundred and eleven patients were enrolled. The mean value of STESS was 3.2 (SD 1.7) and of EMSE was 80.1 (SD 52.6). Within 30 days of the onset of SE, 28.4% of patients (202/711) died. EMSE had higher discriminatory ability for 30-day mortality compared with STESS (AUROC 0.799; 95% CI 0.765-0.832 versus 0.727; 95% CI 0.686-0.766, respectively; p = 0.014). SE cessation within 1 h for convulsive SE and within 12 h for nonconvulsive SE was achieved in 35.3% (251/711) of patients. No significant difference was found between EMSE and STESS in discriminatory ability for SE cessation (AUROC 0.516; 95% CI 0.488-0.561 and 0.518; 95% CI 0.473-0.563, respectively; p = 0.929). EMSE was superior to STESS in predicting 30-day mortality in patients with specific characteristics. No difference between the two scores was found in predicting SE cessation in subgroups of patients with specific characteristics.CONCLUSIONS:
EMSE seems superior to STESS in predicting 30-day mortality, particularly in specific patient categories. Conversely, there is no difference in the ability of these scores in predicting SE cessation, which is overall rather low.
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Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
/
Screening_studies
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article