Background
Status epilepticus (SE) is a serious neurological condition with significant acute mortality of 7–39 % and early treatment is of crucial importance [
1‐
6]. The management and treatment of patients presenting with SE is widely debated. The treatment ranges from benzodiazepines, different anti-epileptic drugs to coma induction [
7,
8]. Because of the clinical heterogeneity of the affected patients [
9] and the lack of established prognostic factors, the prediction of the clinical outcome and survival of SE remains difficult. Rossetti et al. therefore developed the “Status Epilepticus Severity Score” (STESS, Additional file
1: Table S1) in the purpose to predict in-hospital mortality [
10]. The score was designed to give the clinician an estimate of in-hospital mortality of each individual patient, based on four outcome predictors (“age”, “history of seizures”, “seizure type”, “extent of consciousness impairment”). With a maximum score of 6, Rossetti et al. found an optimal cut-off value at ≥3 with a sensitivity of 0.94 and specificity 0.60. Negative predictive value (NPV) was 0.97 and positive predictive value (PPV) was 0.39 [
11]. STESS is a clinically used score to predict outcome after SE and has been externally validated in a second study [
12]. In this confirmatory study, components “history of seizures” and “extent of consciousness impairment” but not “age” and “generalised convulsive seizures at SE onset” were significantly associated with higher odds for death. With a score of ≥4, the optimal cut-off for predicting in-hospital mortality was higher in this cohort [
12].
Leitinger et al. recently developed a new “Epidemiology-based Mortality Status Epilepticus Score” (EMSE) that initially included a combination of six clinical parameters: aetiology, age, comorbidity, EEG, duration and level of consciousness. The authors concluded that the combination of aetiology, age, level of consciousness, +/−EEG (EMSE-EACE/EMSE-EAC) was in many ways superior to predict in-hospital mortality than STESS (≥3 and ≥4) [
13]. However, a very recent study showed no significant difference between STESS and EMSE-EAC or EMSE-EACE [
14].
With SE with respect to mortality and functional status, the long-term outcome after discharge of patients is essentially unknown. Hauser and co-workers studied a cohort of paediatric and adult patients surviving SE at least for 30 days. They followed them until death or end-of-study and found a long-term mortality of 40 % [
15]. Ristic et al. reported a mortality rate of 22.2 % in a cohort of patients treated in a tertiary reference centre. Unfortunately, follow up data was available for only 32.8 % of the surviving patients [
16]. Apart from patients with progressive neurological diseases (typically brain tumours), it is often unknown why patients die several months after SE. If and how the consequences of prolonged SE, e.g. neuronal death due to excitotoxicity or alteration of neuronal networks, contribute to the high mortality is unknown [
9]. Given that SE treatment often includes treatment at intensive care units (ICU), which is associated with significant mortality [
17,
18], prognostic factors and scores allowing determining long-term survival after SE are of high importance.
This study therefore aimed at determining the accuracy of STESS on long-term survival based on a population of patients presenting with SE at admission or during hospital stay, treated in two academic centres in Southern Denmark.
Discussion
An important finding of this study is the high mortality after discharge. After an average follow-up of 30 months, 42 % of our patients died. Our mortality and the data published by Logroscino et al. appear to be in the same range despite of the differences in the patient populations. Logroscino et al. analysed 145 patients (including paediatric patients) that survived 30 days after diagnosis of SE and found a 10-year mortality of 43 % [
15]. These rates were substantially higher than the mortality rates of 22.2 % described by Ristic et al. [
16]. However, Ristic et al. reported incomplete follow-up data in more than 2/3 of the patients, which may explain this difference.
The high mortality also prompts the question if our cohort was biased. We assume that the study population included all patients that required intravenous 2nd line treatment as well as all patients with refractory (refractory to 2nd line treatment) and super-refractory SE (refractory to narcosis), because all these patients are treated in the neurological departments. However, it is likely that an unknown number of patients with prompt success of 1st line treatment with benzodiazepines (e.g. patients with SE due to alcohol withdrawal) were not included in this study due to incorrect use of ICD-10 codes in the emergency departments. However, this potential minor bias did not lead to a higher proportion of severely ill patients included in this study and does therefore not explain the high overall mortality after SE in our cohort. Our cohort comprised 40 % patients with refractory SE (defined by failure of 2nd line therapy), which is exactly the same proportion as reported in comparable studies [
10,
12,
13,
22]. Comparing the patient demographics and baseline characteristics to the first study made by the STESS inventors [
10] was neither indicative for a substantial selection bias. Our cohort had a lower proportion of acute symptomatic aetiology (38 % vs. 56 %) but included slightly more elderly patients (48 % vs. 35 % ≥65 years). The in-hospital mortality of our patients was actually lower (12 %) than in similar studies by Sutter et al. (18 %) or Rosetti et al. (21 %) [
10,
12], showing that selection bias does not explain the high mortality.
The analysis of the underlying aetiology and the analysis of patients with refractory SE only (Additional file
2: Figure S1) did neither provide an obvious explanation for the poor outcome of the patients. The same applies for an obvious flaw of our study, the very variable follow-up: it may even have masked a higher morbidity. In summary, we think that the high overall mortality of patients with SE is a matter of fact and not due to selection bias.
In the light of the very high mortality of patients with SE after discharge, the prediction of outcome beyond acute treatment becomes as important as in-hospital mortality. No previous studies have tested, if STESS (or other clinically relevant scores) predicts long-term survival. Our study confirmed the prognostic significance of the STESS for in-hospital mortality in this Danish cohort of patients [
10,
12]. STESS with a threshold of 4 reliably identified patients that survived the acute phase of SE, and predicted to some extend in-hospital mortality. We here complement current knowledge by showing for the first time that STESS also predicts overall mortality (though with a lower sensitivity and specificity) but is not significantly associated with mortality after discharge. The Kaplan-Meier-plot based on the optimal cut-off of ≥ 4 in the discharge analysis displays this significant difference in overall mortality (Fig.
2a).
All components of the STESS except “history of previous seizures” remained significantly associated with long-term survival and survival after discharge. This indicates “history of previous seizures” is solely relevant for the acute phase of SE, possibly because patients with acute symptomatic seizures (and no history of previous seizures) have higher odds of dying in the hospital. Of note, the differentiation between seizure types remained without prognostic relevance in all our analyses in line with the report by Sutter et al. [
12].
Among all components, “coma” yielded most prognostic information but only relevant for a few patients. Coma had higher odds for death (in-hospital mortality: 19.4 and overall mortality: 8.8) than STESS (in-hospital mortality: 17.3, overall mortality: 5.3) in all our analyses, suggesting that this factor may even warrant a higher score. Only 3 out of 19 patients presenting with “coma at onset” of SE were alive at end-of-follow up.
The other major factor with similar importance was “age above 65”, which gave 2 points in the STESS. The Kaplan-Meier curves of patients above and below 65 years (Fig.
2e) were similar to the Kaplan-Meier curves of patients with STESS ≥3 (or STESS ≥4, Fig.
2b). However, neither the high mortality of SE patients nor the plateau after approximately 3 years can be explained by age alone or by naturally occurring death of the patients. Assuming that natural occurring death in higher age would explain the difference alone, one would not expect a major difference 6 months after SE. However, this analysis (Additional file
1: Table S3) revealed similar results as the analysis at the end-of-study. Further, the Kaplan-Meier curves of patients with STESS ≥3 (or STESS ≥4) show a much more rapid decline than the curve of patients above and below 65, which further supports the idea that STESS bears more prognostic information than age alone.
It is tempting to speculate that neuronal damage after SE may be the factor that substantially contributes to overall outcome of patients with SE. In patients with acute neuronal damage (like stroke [
23]), age is a major prognostic factor and neuronal damage may therefore explain the high relevance of age as prognostic factor. However, this retrospective study with all its limitations (e.g. mortality as only outcome parameter, lack of detailed assessment of functional outcome, retrospective design, incomplete assessment of other prognostic factors, etc.) does not provide clear clues in support of this hypothesis and further studies are required to better understand the important contributors to long-term survival after SE beyond aetiology.