Prognostic scores in status epilepticus-a critical appraisal

External validation of newly modified status epilepticus severity score for predicting mortality in patients with status epilepticus in a regional hospital in Taiwan

PURPOSE

To evaluate and compare the performance of the status epilepticus severity score (STESS), modified STESS (mSTESS), and the newly modified STESS (nSTESS) in predicting mortality in patients with status epilepticus (SE) at a regional hospital in Taiwan.

METHODS

Data were collected from 81 patients with SE, aged over 18 years at a regional medical hospital in Tainan from January 2012 to December 2022. SE were treated following the standard treatment protocol. Exclusion criteria included missing data, lack of adherence to the treatment protocol, and transfer to tertiary medical centers. Outcome measures included differences in characteristics between survivor and non-survivor groups, the accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of STESS, nSTESS, mSTESS. Receiver operating characteristic (ROC) curve and area under curve (AUC) of scales were generated. Calibration with Hosmer-Lemeshow test was built as well.

RESULTS

The study found significant differences in seizure types (p = 0.015) and undergoing intubation (p = 0.017) between survivor and non-survivor groups. No significant differences were observed in age, gender, underlying diseases, or the category of antiseizure medications (ASMs) usage. The ROC curve for STESS, nSTESS and mSTESS showed similar predictive values of around 0.75, indicating moderate performance of prediction. The Hosmer-Lemeshow test showed no significant difference between real-world predictions and these three clinical scales. In the aspect of accuracy, sensitivity and specificity, nSTESS has similar overall accuracy as in STESS and mSTESS.

CONCLUSION

This external validation study demonstrates the moderate performance of nSTESS in predicting mortality in SE patients at a regional hospital in Taiwan. These outcomes underscore the practical utility of these scales in clinical practice, with nSTESS demonstrating accuracy on par with the others. Further validation in larger, multicenter cohorts and other healthcare settings is necessary to fully confirm its predictive value.

The value of serum albumin concentration in predicting functional outcome of status epilepticus: An observational study

OBJECTIVE

Status epilepticus (SE) is a common neurological emergency with unsatisfying prognoses, and accurate prediction of functional outcome is beneficial in clinical decision-making. The relationship between serum albumin concentration and outcome of SE patients has yet to be unveiled.

METHODS

Clinical profiles of SE patients admitted to Xiangya Hospital, Central South University, from April 2017 to November 2020, were analyzed retrospectively. Outcomes of SE patients at discharge were divided into two groups based on the modified Rankin Scale (mRS): favorable outcome (mRS: 0-3) and unfavorable outcome (mRS: 4-6).

RESULTS

Fifty-one patients were enrolled. Unfavorable functional outcome at discharge was reported in 60.8% (31/51). Serum albumin concentration at admission and the Encephalitis-NCSE-Diazepam resistance-Image abnormalities-Tracheal intubation (END-IT) score remained independent predictors for functional outcome of SE patients. A lower albumin concentration at admission and higher END-IT score indicated a higher chance of unfavorable outcome for SE patients. The cut-off value of serum albumin to predict unfavorable outcome was 35.2 g/L, with a sensitivity of 67.7% and specificity of 85.0%, and an area under the receiver operating characteristic curve (ROC) of .738 (95% CI: .600-.876, p = .004). The preferable END-IT score with optimal sensitivity (74.2%) and specificity (60%) was 2 and the area under the ROC was .742, with 95% CI of .608-.876 (p = .004).

SIGNIFICANCE

Serum albumin concentration at admission and the END-IT score are two independent predictive factors for short-term outcome of SE patients, moreover, the serum albumin concentration is not inferior to the END-IT score in indicating functional outcome at discharge.

Imaging of status epilepticus: Making the invisible visible. A prospective study on 206 patients

BACKGROUND

Peri-ictal MRI abnormalities (PMA) frequently affect the cerebral cortex, hippocampus, pulvinar of the thalamus, corpus callosum, and cerebellum. In this prospective study, we aimed to characterize the spectrum of PMA in a large cohort of patients with status epilepticus.

METHODS

We prospectively recruited 206 patients with SE and an acute MRI. The MRI protocol included diffusion weighted imaging (DWI), fluid-attenuated inversion recovery (FLAIR), arterial spin labeling (ASL), and T1-weighted imaging pre-and post-contrast application. Peri-ictal MRI abnormalities were stratified as either neocortical or non-neocortical. Amygdala, hippocampus, cerebellum, and corpus callosum were regarded as non-neocortical structures.

RESULTS

Peri-ictal MRI abnormalities were observed in 93/206 (45%) of patients in at least one MRI sequence. Diffusion restriction was observed in 56/206 (27%) of patients, which was mainly unilateral in 42/56 (75%) affecting neocortical structures in 25/56 (45%), non-neocortical structures in 20/56 (36%) and both areas in 11/56 (19%) of patients. Cortical DWI lesions were located mostly in frontal lobes 15/25 (60%); non-neocortical diffusion restriction affected either the pulvinar of the thalamus or hippocampus 29/31 (95%). Alterations in FLAIR were observed in 37/203 (18%) of patients. They were mainly unilateral 24/37 (65%); neocortical 18/37 (49%), non-neocortical 16/37 (43%), or affecting both neocortical and non-neocortical structures 3/37 (8%). In ASL, 51/140 (37%) of patients had ictal hyperperfusion. Hyperperfused areas were located mainly in the neocortex 45/51 (88%) and were unilateral 43/51 (84%). In 39/66 (59%) of patients, PMA were reversible in one week. In 27/66 (41%), the PMA persisted and a second follow-up MRI was performed three weeks later in 24/27 (89%) patients. In 19/24 (79%) PMA were resolved.

CONCLUSIONS

Almost half of the patients with SE had peri-ictal MRI abnormalities. The most prevalent PMA was ictal hyperperfusion followed by diffusion restriction and FLAIR abnormalities. Neocortex was most frequently affected especially the frontal lobes. The majority of PMAs were unilateral. This paper was presented at the 8th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures held in September 2022.

Retrospective External Validation of the Status Epilepticus Severity Score (STESS) to Predict In-hospital Mortality in Adults with Nonhypoxic Status Epilepticus: A Machine Learning Analysis

BACKGROUND

The objective of this study was to validate the value of the Status Epilepticus Severity Score (STESS) in the prediction of the risk of in-hospital mortality in patients with nonhypoxic status epilepticus (SE) using a machine learning analysis.

METHODS

We included consecutive patients with nonhypoxic SE (aged ≥ 16 years) admitted from 2013 to 2021 at the Modena Academic Hospital. A decision tree analysis was performed using in-hospital mortality as a dependent variable and the STESS predictors as input variables. We evaluated the accuracy of STESS in predicting in-hospital mortality using the area under the receiver operating characteristic curve (AUROC) with 95% confidence interval (CI).

RESULTS

Among 629 patients with SE, the in-hospital mortality rate was 23.4% (147 of 629). The median STESS in the entire cohort was 2.9 (SD 1.6); it was lower in surviving compared with deceased patients (2.7, SD 1.5 versus 3.9, SD 1.6; p < 0.001). Of deceased patients, 82.3% (121 of 147) had scores of 3-6, whereas 17.7% (26 of 147) had scores of 0-2 (p < 0.001). STESS was accurate in predicting mortality, with an AUROC of 0.688 (95% CI 0.641-0.734) only slightly reduced after bootstrap resampling. The most significant predictor was the seizure type, followed by age and level of consciousness at SE onset. Nonconvulsive SE in coma and age ≥ 65 years predicted a higher risk of mortality, whereas generalized convulsive SE and age < 65 years were associated with a lower risk of death. The decision tree analysis using STESS variables correctly classified 90% of survivors and 34% of nonsurvivors after the SE, with an overall risk of error of 23.1%.

CONCLUSIONS

This validation study using a machine learning system showed that STESS is a valuable prognostic tool. The score appears particularly accurate and effective in identifying patients who are alive at discharge (high negative predictive value), whereas it has a lower predictive value for in-hospital mortality.

Machine learning validation through decision tree analysis of the Epidemiology-Based Mortality Score in Status Epilepticus

OBJECTIVE

This study was undertaken to validate the accuracy of the Epidemiology-Based Mortality Score in Status Epilepticus (EMSE) in predicting the risk of death at 30 days in a large cohort of patients with status epilepticus (SE) using a machine learning system.

METHODS

We included consecutive patients with SE admitted from 2013 to 2021 at Modena Academic Hospital. A decision tree analysis was performed using the 30-day mortality as a dependent variable and the EMSE predictors as input variables. We evaluated the accuracy of EMSE in predicting 30-day mortality using the area under the receiver operating characteristic curve (AUC ROC), with 95% confidence interval (CI). We performed a subgroup analysis on nonhypoxic SE.

RESULTS

A total of 698 patients with SE were included, with a 30-day mortality of 28.9% (202/698). The mean EMSE value in the entire population was 57.1 (SD = 36.3); it was lower in surviving compared to deceased patients (47.1, SD = 31.7 vs. 81.9, SD = 34.8; p < .001). The EMSE was accurate in predicting 30-day mortality, with an AUC ROC of .782 (95% CI = .747-.816). Etiology was the most relevant predictor, followed by age, electroencephalogram (EEG), and EMSE comorbidity group B. The decision tree analysis using EMSE variables correctly predicted the risk of mortality in 77.9% of cases; the prediction was accurate in 85.7% of surviving and in 58.9% of deceased patients within 30 days after SE. In nonhypoxic SE, the most relevant predictor was age, followed by EEG, and EMSE comorbidity group B; the prediction was correct in 78.9% of all cases (89.6% in survivors and 46.1% in nonsurvivors).

SIGNIFICANCE

This validation study using a machine learning analysis shows that the EMSE is a valuable prognostic tool, and appears particularly accurate and effective in identifying patients with 30-day survival, whereas its performance in predicting 30-day mortality is lower and needs to be further improved.

Development and Validation of a Nomogram Based on the Epidemiology-Based Mortality Score in Status Epilepticus (EMSE) Parameters to Predict 30-day Mortality in Status Epilepticus

BACKGROUND

To develop a nomogram using the parameters of the Epidemiology-Based Mortality Score in Status Epilepticus (EMSE) and to evaluate its accuracy compared with the EMSE alone in the prediction of 30-day mortality in patients with status epilepticus (SE).

METHODS

We included a cohort of patients with SE aged ≥ 21 years admitted from 2013 to 2021. Regression coefficients from the multivariable logistic regression model were used to generate a nomogram predicting the risk of 30-day mortality. Discrimination of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUCROC) with 95% confidence interval. Internal validation was performed by bootstrap resampling.

RESULTS

Among 698 patients with SE, the 30-day mortality rate was 28.9% (202 of 698). On the multivariable analysis, all EMSE parameters (except for the comorbidity group including metastatic solid tumor or AIDS) were associated with a significantly higher risk of 30-day mortality and were included in the nomogram. The discriminatory capability of the nomogram with bootstrap resampling (5000 resamples) had an AUCROC of 0.830 (95% confidence interval 0.798-0.862). Conversely, the AUCROC of the EMSE was 0.777 (95% confidence interval 0.742-0.813). Thus, the probability that a patient who died within 30 days from SE had a higher score than a patient who survived was 83%, indicating good discriminatory power of the nomogram. Conversely, the risk predicted using the EMSE alone was 77%. The nomogram was well calibrated.

CONCLUSIONS

A nomogram based on EMSE parameters appears superior to the EMSE in predicting the risk of 30-day mortality after SE. The discrimination and calibration of the nomogram shows a better predictive accuracy than the EMSE alone.

Clinico-biological markers for the prognosis of status epilepticus in adults

Prediction of mortality, functional outcome and recovery after status epilepticus (SE) is a challenge. Biological and clinical markers have been proposed to reflect the brain injury or to monitor critical ill patients' severity. The aim of this study was to characterize short-term and long-term prognostic factors for SE patients hospitalized in intensive care unit. Patient's outcome was assessed using the modified Rankin Scale at discharge and after 6-12 months. We first assessed the univariate prognosis significance of 51 clinical, demographic or biochemical markers. Next, we built multivariate clinico-biological models by combining most important factors. Statistical models' performances were compared to those of two previous published scales STESS and mSTESS. Eighty-one patients were enrolled. Thirty-five patients showed a steady state while 46 patients clinically worsened at discharge: 14 died, 14 had persistent disability at 6-12 months and 18 recovered. Logistic regression analysis revealed that clinical markers (SE refractoriness, SE duration, de novo SE) were significant independent predictors of worsening while lipids markers and progranulin better predicted mortality. The association of clinico-biological variables allowed to accurately predict worsening at discharge (AUC > 0.72), mortality at discharge (AUC 0.83) and recovery at long-term (AUC 0.89). Previous scales provided lower prediction for worsening (AUC 0.63, STESS; 0.53, mSTESS) and mortality (AUC 0.56, STESS; 0.62, mSTESS) (p < 0.001). We proposed new clinico-biological models with a strong discrimination power for prediction of short- and long-term outcome of hospitalized status epilepticus patients. Their implementation in electronic devices may enhance their clinical liability.

Status Epilepticus Mortality Risk Factors and a Correlation Survey with the Newly Modified STESS

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.

Clinical findings, etiological factors, and prognosis markers in status epilepticus: a university hospital experience

OBJECTIVE

To determine the factors affecting mortality and disability in status epilepticus (SE) and to evaluate the prediction ability of the Status Epilepticus Severity Score (STESS) for disability and mortality.

MATERIALS AND METHOD

The demographic and clinical characteristics, prognosis and prognosis predictors of 72 patients who were diagnosed with SE between 2013 and 2018 were retrospectively evaluated. The STESS was used to predict prognosis, and the modified Rankin scale (mRS) was used to determine the disability at discharge.

RESULTS

The study population had a mean age of 45.4 ± 20.7, and it was found that mortality was 22.2% and acute symptomatic etiology played a 54.1% role in etiology. Advanced age, refractory SE or super-refractory SE, acute symptomatic etiology, and a history of epilepsy were related to mortality, symptomatic etiology (acute, progressive, remote), a history of hospitalization and epilepsy in intensive care or in other departments other than the neurology department were associated with disability. The sensitivity of STESS in predicting mortality was 100%, specificity was 69%, accuracy was 76.4%, positive predictive value (PPV) was 48.5%, and the negative predictive value (NPV) was 100%. The sensitivity of STESS in predicting mobilization during discharge was 55.6% with a 63.9% specificity and 59.7% accuracy, PPV was 60.6%, and NPV was 59%.

CONCLUSION

It was observed that STESS strongly predicts a good prognosis; however, it was not found to be useful in predicting motor disability during discharge. Thus, new studies should be conducted to predict and evaluate mobility in SE patients at discharge.

Predictors of in-hospital mortality in epilepsy and epileptic seizures in the elderly populace - A cross sectional study from rural India

AIM

This study was aimed to analyze the predictors of in-hospital mortality in epilepsy and epileptic seizures in the elderly population of the rural regions of North India.

METHODS

250 hospitalized elderly (≥60 years of age) were evaluated for predictors of in- hospital mortality who presented with epilepsy or epileptic seizures during the study period from July 2017 to September 2019.

RESULTS

The mean age of the study population was 67.2 ± 7.7 years, among them, 49.2 % (123) cases were of convulsive status epilepticus (CSE), 37.6 % (94) cases were of acute symptomatic seizures and 13.2 % (33) cases were of epilepsy. The most common etiology was a stroke in 58 % of cases. In -hospital mortality was 21.6 % and the variables significantly related with mortality on multivariate analysis were: cases with age more than 70 years (odds ratio(OR) = 2.76, 95 % confidence interval (CI) = 1.24-6.12; p = 0.013), cases with new onset CSE (NOCSE) (OR = 15.24, 95 % CI = 3.13-73.92; p = 0.001), duration of hospital stay more than ≥5 days (OR = 2.27, 95 % CI = 1.03-4.99; p = 0.042).

CONCLUSIONS

The predictors of in-hospital mortality in the elderly were related to age more than 70 years, NOCSE, longer duration of hospital stay.

Prediction of in-hospital mortality in status epilepticus: Evaluation of four scoring tools in younger and older adult patients

OBJECTIVE

The goal of this study was to evaluate the predictive capacity of four scoring tools: the Status Epilepticus Severity Score (STESS), the Encephalitis-NCSE-Diazepam resistance-Image abnormalities-Tracheal intubation (END-IT) score, and two variable combinations of the Epidemiology-based Mortality Score in Status Epilepticus (EMSE) in younger and older adult patients with status epilepticus (SE).

METHODS

We present a retrospective hospital-based analysis with a focus on adult patients with SE at three tertiary care hospitals in the Zhejiang province of China. Data were collected from January 2013 to December 2018. The patients were divided into two groups: younger adult patients (18-64 years old) and older adult patients (≥65 years old). Clinical outcomes (dead or alive) were assessed at hospital discharge. The four scoring tools were used to predict in-hospital mortality in both younger and older adult patients.

RESULTS

The mortality rate in older adult patients (25.4%) was higher than in younger adult patients (12.9%). Compared with the elderly, the younger adult patients had a higher proportion of encephalitis, while acute cerebrovascular disease and Charlson Complications Index (CCI) were lower. For the younger adult patients, END-IT had the largest area under the curve (AUC) of 0.843 (95% CI, 0.772-0.899), which was higher than the EMSE-EAL value of 0.687 (95% CI, 0.603-0.763, p < 0.05) and EMSE-EAC of 0.646 (95% CI, 0.561-0.725, p < 0.05). For the older adult patients, EMSE-EAL had the largest AUC of 0.843 (95% CI, 0.738-0.919), which was significantly higher than STESS with an AUC of 0.676 (95% CI, 0.554-0.782, p < 0.05). Moreover, the AUC of EMSE-EAL in the elderly was larger than in younger adult patients. The cutoffs in younger adult patients were STESS ≥ 4 (sensitivity 0.444, specificity 0.951), END-IT ≥ 3 (sensitivity 0.833, specificity 0.672), EMSE-EAL ≥ 31 (sensitivity 0.778, specificity 0.566), and EMSE-EAC ≥ 33 (sensitivity 0.833, specificity 0.492). However, the cutoffs in older adult patients were STESS ≥ 5 (sensitivity 0.500, specificity 0.925), END-IT ≥ 2 (sensitivity 0.944, specificity 0.547), EMSE-EAL ≥ 30 (sensitivity 0.944, specificity 0.623), and EMSE-EAC ≥ 31 (sensitivity 0.944, specificity 0.415).

CONCLUSION

Our results indicated that the STESS, END-IT, EMSE-EAC, and EMSE-EAL scores have excellent capacity to predict in-hospital mortality in both younger and older adult patients with SE. Our study supports the use of END-IT in patients under 65 years of age and suggests that EMSE-EAL is the most suitable scoring tool for patients over 65.

Development of a novel outcome prediction score (PEDSS) for pediatric convulsive status epilepticus: A longitudinal observational study

OBJECTIVE

The objectives of this study were to evaluate ENDIT score and develop a novel outcome prediction score for outcome of pediatric convulsive status epilepticus (CSE) at the hospital and 3 months postdischarge.

METHODS

Children and adolescents aged 1 month to 14 years, presenting with CSE to a tertiary care teaching center in North India from January 2017 to March 2019, were screened for enrollment. In-hospital and 3-month postdischarge outcome were defined as poor if Pediatric Cerebral Performance Category Scale (PCPCS) score dropped by ≥2 levels.

RESULTS

Overall, 61 patients were enrolled for final analysis after applying exclusion and inclusion criteria. The area under the receiver operating characteristic (ROC) curve for ENDIT score in predicting mortality and differentiating good from poor outcome at the hospital and at 3 months postdischarge was 0.74 (95% confidence interval [CI] = 0.58-0.89), 0.7 (95% CI = 0.57-0.83), and 0.72 (95% CI = 0.6-0.82), respectively. Based on predictors in the present cohort that were significantly different between good and poor outcome cases at the hospital and 3 months postdischarge, a new six-point score named PEDSS (pre-status epilepticus PCPCS, background electroencephalographic abnormalities, drug refractoriness, semiology, and critical sickness) was developed. The area under ROC curves for PEDSS score in predicting mortality and differentiating good from poor outcome at the hospital and at 3 months postdischarge were 0.93 (95% CI = 0.87-0.99), 0.8 (95% CI = 0.7-0.9), and 0.89 (95% CI = 0.8-0.96), respectively. The best cutoff PEDSS scores for predicting mortality and poor outcome at the hospital and at 3 months postdischarge were ≥4, ≥3, and ≥3, respectively.

SIGNIFICANCE

The PEDSS score has high predictive accuracy for mortality and differentiating good from poor outcome at the hospital and 3 months postdischarge in pediatric CSE. Future studies should be planned to validate it in various geographical and health care settings and in adults.

Improving the ability to predict hospital mortality among adults by combining two status epilepticus outcome scoring tools

OBJECTIVE

The goal of this study was to compare the predictive ability of the Status Epilepticus Severity Score (STESS), the Encephalitis-nonconvulsive status epilepticus (NCSE)-Diazepam resistance-Image abnormalities-Tracheal intubation (END-IT), and the combination of these two scoring tools to predict mortality among inhospital patients with status epilepticus (SE).

METHODS

A retrospective analysis was conducted of adult patients with SE who were admitted to the neurology department, the emergency department, and the intensive care unit from January 2013 to December 2017. The patients were divided into two groups: survivors and nonsurvivors. The STESS data were obtained when the patient arrived at the hospital, and the END-IT data were collected 24 h after patients were initially treated in the hospital. The ability of the scoring tools to predict death in patients with SE, alone or in combination, was evaluated.

RESULTS

A total of 123 patients with SE were included in the study, of which 22 died, for a mortality rate of 17.9%. The STESS and END-IT scores of nonsurvivors were both significantly higher than those of survivors (median STESS 4 vs. 2, p = 0.003; median END-IT 3 vs. 1, p < 0.001). The area under the receiver operating characteristic curve (AUC) was 0.698 for the STESS and 0.852 for the END-IT, and the cutoff values were 4 and 3, respectively. The AUC of the END-IT with the optimal cutoff value was larger than that of the STESS (p = 0.024). The sensitivity and specificity of combining the STESS and END-IT by the serial method (STESS ≥ 4∩END-IT ≥ 3) were 0.50 and 0.95, respectively, and the specificity was significantly higher than the STESS or END-IT (both p's < 0.001). The sensitivity and specificity of combining the STESS and END-IT by the parallel method (STESS ≥ 4⋃END-IT ≥ 3) were 0.91 and 0.53, respectively, and the sensitivity was higher than the STESS was (p = 0.016).

CONCLUSION

Our results indicated that the combined score of the STESS and END-IT systems was a better predictor of survival of patients with SE than the scores of either the STESS system or the END-IT system alone and that combining the scores may be considered to be a new method for early identification of patients for both good and bad outcomes.

Management of prolonged epileptic seizures and status epilepticus in palliative care patients

Prolonged seizures and status epilepticus (SE) are relevant problems in palliative care. Timely recognition and effective early treatment with first- and second-line antiepileptic drugs (AEDs) may prevent unnecessary hospitalizations. Seizures should be recognized and addressed like any other symptom that causes discomfort or reduces quality of life. Use of alternative AED administration routes (buccal, intranasal, or subcutaneous) may offer possibilities for effective and individualized AED therapy, even during the last days of life. In hospice or home care, however, also intravenous treatment is possible via vascular access devices for long-term use. Aggressive unlimited intensive care unit (ICU) treatment of refractory SE in palliative patients is mostly not indicated. At worst, intensive care can be futile and possibly harmful: death in the ICU is often preceded by long and aggressive treatments. Metastatic cancer, old age, high severity of acute illness, overall frailty, poor functional status before hospital admission, and the presence of severe comorbidities all increase the probability of poor outcome of intensive care. When several of these factors are present, consideration of withholding intensive care may be in the patient's best interests. Anticipated outcomes influence patients' preferences. A majority of patients with a limited life expectancy because of an incurable disease would not want aggressive treatment, if the anticipated outcome was survival but with severe functional impairment. Doctors' perceptions about their patients' wishes are often incorrect, and therefore, advance care planning including seizure management should be done early in the course of the disease. This article is part of the Special Issue "Proceedings of the 7th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures".