Status Epilepticus Mortality Risk Factors and a Correlation Survey with the Newly Modified STESS
2021
Background: Status epilepticus (SE) is a neurological emergency and is usually associated with significant morbidity and mortality rates. Several clinical scales have been proposed to predict the clinical outcome of such incidents, including the Status Epilepticus Severity Score (STESS), the modified STESS (mSTESS), and the Encephalitis-Nonconvulsive Status Epilepticus-Diazepam Resistance-Image Abnormalities-Tracheal intubation (END-IT). Nevertheless, there is still a need for a more practical and precise predictive scale. Methods: This is a retrospective cohort study which examines data from patients with SE in our Department of Neurology between 2009 and 2020. Based on the outcome of each case, the patients were divided into survivor and non-survivor groups. We analyzed the independent factors and adjusted the STESS to achieve a better prediction of prognosis. The predictive accuracy of our new STESS scale was then compared with that of the mSTESS and the END-IT. Results: Data on a total of 59 patients were collected, with 6 of them classified as non-survivors. The effects of the variables of age, sex, underlying disease(s), and type(s) of antiepileptic drug (AED) use showed no significant differences between the survivor and non-survivor groups. Importantly, the number of AEDs used in the first week and the use of thiobarbiturates predicted non-survival. We adjusted the STESS to create the newly modified STESS (nSTESS), which showed a better predictive capacity than the STESS, the mSTESS, and the END-IT. Conclusions: Our adjustment of the STESS with the addition of the factors “number of AEDs within the first week” and “use of thiobarbiturates”, could have a positive impact on the prediction of mortality rates compared with currently used scales. This nSTESS could potentially be useful in clinical practices, for the early prediction of outcomes for patients with SE.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
18
References
0
Citations
NaN
KQI