Predictive performances of STESS and EMSE in a Norwegian adult status epilepticus cohort
| Autor: | Line Bédos Ulvin, Kjell Heuser, Ketil Berg Olsen, Erik Taubøll |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
medicine.medical_specialty
Status epilepticus Norwegian Comorbidity Risk Assessment Sensitivity and Specificity Severity of Illness Index Cohort Studies 03 medical and health sciences 0302 clinical medicine Level of consciousness Status Epilepticus Risk Factors Internal medicine Epidemiology Medicine Humans Hospital Mortality Receiver operating characteristic business.industry Norway Area under the curve General Medicine Prognosis language.human_language Neurology Cohort Etiology language Neurology (clinical) medicine.symptom business 030217 neurology & neurosurgery |
| Zdroj: | Seizure. 70 |
| ISSN: | 1532-2688 |
| Popis: | "Status Epilepticus Severity Score" (STESS) and "Epidemiology-based Mortality Score in Status Epilepticus" (EMSE) are two clinical scoring systems aiming to predict mortality in status epilepticus (SE). The objective of this study was to compare their predictive performances in a cohort of 151 SE-patients from Oslo University Hospital in the period 2001-2017.Variables used to calculate STESS (age, previous seizures, worst SE-semiology, level of consciousness) and two different versions of EMSE, EMSE-EAC (etiology, age, comorbidities) and EMSE-EACE (etiology, age, comorbidities, EEG-pattern), as well as outcome were collected retrospectively. Receiver Operating Characteristic (ROC)-analyses, determination of best cut-off values, sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) were performed. In addition, Precision-Recall curves (PRC) were produced, plotting PPV as a function of Se.Thirteen patients (9%) died during their hospital stay. STESS did not accurately predict mortality, with a ROC-curve showing an area under the curve (AUC) of 0.625(95%CI = 0.472-0.783), p = 0.15. EMSE-EAC performed better with an AUC of 0.714(95%CI = 0.552-0.873), p = 0.01 and a best cut-off value of 37. Se was 69.2%, Sp 72.1%, PPV 19% and NPV 96.2%. EMSE-EACE performed best with an AUC of 0.855(95%CI = 0.736-0.976), p 0.0005 and a best cut-off value of 79. Se was 77.8%, Sp 87.8%, PPV 36.8% and NPV 97.7%. The PRC showed areas under the PRC of 0.23 for EMSE-EAC and 0.46 for EMSE-EACE.EMSE-EAC and EMSE-EACE performed better than STESS and may be useful in identifying the patients at risk of death in SE. PRC may give a more relevant visual representation of predictive utility than ROC-curves in situations of imbalanced datasets. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect