Prognostic value of Salzburg nonconvulsive status epilepticus criteria: The SACE score.

OBJECTIVE: This study was undertaken to investigate the association between the Salzburg nonconvulsive status epilepticus (NCSE) criteria and in-hospital outcome, to determine the predictive accuracy of the Status Epilepticus Severity Score (STESS), modified STESS (mSTESS), Epidemiology-Based Mortality Score in Status Epilepticus (EMSE), and END-IT (encephalitis, NCSE, diazepam resistance, imaging features, and tracheal intubation) in NCSE patients, and to develop a new prognostic score specifically designed for NCSE patients. METHODS: Clinical and electroencephalographic (EEG) data of adult patients treated for NCSE from 2020 to 2023 were retrospectively assessed. Age, sex, modified Rankin Scale at admission, comorbidities, history of seizures, etiology, status epilepticus type, and outcome were collected from the patients' digital charts. EEG data were assessed and categorized applying the Salzburg NCSE criteria. In-hospital death was defined as the primary outcome. RESULTS: A total of 116 NCSE patients were included. Multivariable logistic regression revealed that Salzburg NCSE criterion A2 (ictal morphological, spatial, and temporal evolution) was associated with in-hospital survival. The best STESS cutoff was ≥4 (sensitivity = .62, specificity = .69, accuracy = 67%). mSTESS ≥ 5 reached a sensitivity of .68, a specificity of .57, and an overall accuracy of 60%, EMSE ≥ 64 a sensitivity of .82, a specificity of .39, and an overall accuracy of 52%, and END-IT ≥ 3 a sensitivity of .65, a specificity of .44, and an overall accuracy of 50%. Through a hypothesis-generating approach, we developed the SACE score, which integrates EEG features (criterion A2) with patient age (with a 75-year cutoff), history of seizures, and level of consciousness. With a cutoff of ≥3, it had a sensitivity of .77, a specificity of .74, and an overall accuracy of 76%, performing better than other prognostic scores. SIGNIFICANCE: We developed a new user-friendly scoring system, the SACE score, which integrates EEG features with other established outcome-related variables assessable in early stages, to assist neurologists and neurointensivists in making more tailored prognostic decisions for NCSE patients.

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.

Prognostic scores in status epilepticus-a critical appraisal.

Currently, there are 4 published scales evaluating status epilepticus (SE) prognosis: the Status Epilepticus Severity Score (STESS), the Epidemiology-based Mortality score in Status Epilepticus (EMSE), the modified STESS (mSTESS), and the Encephalitis Nonconvulsive Status Epilepticus Diazepam Resistence Imaging Tracheal Intubation (END-IT) score. The first prognostic score published for SE, the STESS, is a simple and practical scale that evaluates patient prognosis upon admission and is used widely to predict the outcome and stratify patients. Another scale, which was developed based on large epidemiologic studies, the EMSE, is more easily adapted to different regions around the world when assessing individual risk and stratifying patients in interventional studies. The mSTESS was created by adding the modified Rankin Scale (mRS) to the STESS, which decreases the ceiling effect and increases the mortality prediction capabilities of the STESS. The END-IT is the only prognostic scale assessing functional outcome and is comprehensively simple and satisfyingly accurate. Evaluating the limitations of each of these scales aids in the exploration and advancement of SE prognostic scales, thereby facilitating better clinical interventions and scientific research.

Endothelial Reprogramming in Atherosclerosis.

Atherosclerosis (AS) is a severe vascular disease that results in millions of cases of mortality each year. The development of atherosclerosis is associated with vascular structural lesions, characterized by the accumulation of immune cells, mesenchymal cells, lipids, and an extracellular matrix at the intimal resulting in the formation of an atheromatous plaque. AS involves complex interactions among various cell types, including macrophages, endothelial cells (ECs), and smooth muscle cells (SMCs). Endothelial dysfunction plays an essential role in the initiation and progression of AS. Endothelial dysfunction can encompass a constellation of various non-adaptive dynamic alterations of biology and function, termed "endothelial reprogramming". This phenomenon involves transitioning from a quiescent, anti-inflammatory state to a pro-inflammatory and proatherogenic state and alterations in endothelial cell identity, such as endothelial to mesenchymal transition (EndMT) and endothelial-to-immune cell-like transition (EndIT). Targeting these processes to restore endothelial balance and prevent cell identity shifts, alongside modulating epigenetic factors, can attenuate atherosclerosis progression. In the present review, we discuss the role of endothelial cells in AS and summarize studies in endothelial reprogramming associated with the pathogenesis of AS.

Development and validation of a nomogram to provide individualized predictions of functional outcomes in patients with convulsive status epilepticus at 3 months: The modified END-IT tool.

AIMS: The prediction of outcomes in convulsive status epilepticus (CSE) remains a constant challenge. The Encephalitis-Nonconvulsive Status Epilepticus-Diazepam Resistance-Image Abnormalities-Tracheal Intubation (END-IT) score was a useful tool for predicting the functional outcomes of CSE patients, excluding cerebral hypoxia patients. With further understanding of CSE, and in view of the deficiencies of END-IT itself, we consider it necessary to modify the prediction tool. METHODS: The prediction model was designed from a cohort of CSE patients from Xijing Hospital (China), between 2008 and 2020. The enrolled subjects were randomly divided into training cohort and validation cohort as a ratio of 2:1. The logistic regression analysis was performed to identify the predictors and construct the nomogram. The performance of the nomogram was assessed by calculating the concordance index, and creating calibration plots to check the consistency between the predicted probabilities of poor prognosis and the actual outcomes of CSE. RESULTS: The training cohort included 131 patients and validation cohort included 66 patients. Variables included in the nomogram were age, etiology of CSE, non-convulsive SE, mechanical ventilation, abnormal albumin level at CSE onset. The concordance index of the nomogram in the training and validation cohorts was 0.853 (95% CI, 0.787-0.920) and 0.806 (95% CI, 0.683-0.923), respectively. The calibration plots showed an adequate consistency between the reported and predicted unfavorable outcomes of patients with CSE at 3 months after discharge. CONCLUSIONS: A nomogram for predicting the individualized risks of poor functional outcomes in CSE was constructed and validated, which has been an important modification of END-IT score.

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.

Predicting the Functional Outcome of Adult Patients with Status Epilepticus.

Patients that survive status epilepticus (SE) may suffer from neurological and cognitive deficits that cause severe disabilities. An effective scoring system for functional outcome prediction may help the clinician in making treatment decisions for SE patients. Three scoring systems, namely the Status Epilepticus Severity Score (STESS), the Epidemiology-Based Mortality Score in Status Epilepticus (EMSE), and the Encephalitis-Nonconvulsive Status Epilepticus-Diazepam Resistance-Image Abnormalities-Tracheal Intubation (END-IT), have been developed in the past decade to predict the outcomes of patients with SE. Our study aimed at evaluating the effectiveness of these scores in predicting the function outcomes both at and after discharge in SE patients. We retrospectively reviewed the clinical data of 55 patients admitted to our neurological intensive care unit between January 2017 and December 2017. The clinical outcomes at discharge and at last follow-up were graded using the modified Rankin Scale. Our research indicated that STESS was the most sensitive and EMSE was the most specific predictive scoring method for SE outcome prediction. On the other hand, END-IT predicted functional outcomes in SE patients poorly. We concluded that STESS and EMSE can accurately predict the functional outcomes in SE patients both at discharge and the follow-up period.

Comparison of scoring tools for the prediction of in-hospital mortality in status epilepticus.

PURPOSE: Several scoring tools have been developed for the prognostication of outcome after status epilepticus (SE). In this study, we compared the performances of STESS (Status Epilepticus Severity Score), mSTESS (modified STESS), EMSE-EAL (Epidemiology-based Mortality Score in Status Epilepticus- Etiology, Age, Level of Consciousness) and END-IT (Encephalitis-NCSE-Diazepam resistance-Image abnormalities-Tracheal intubation) in predicting in-hospital mortality after SE. METHOD: Data collected retrospectively from a cohort of 287 patients with SE were used to calculate STESS, mSTESS, EMSE-EAL, and END-IT scores. The differences between the scores' performances were determined by means of area under the ROC curve (AUC) comparisons and McNemar testing. RESULTS: The in-hospital mortality rate was 11.8%. The AUC of STESS (0.628; 95% confidence interval (CI), 0.529-0.727) was similar to that of mSTESS (0.620; 95% CI, 0.510-0.731), EMSE-EAL (0.556; 95% CI, 0.446-0.665), and END-IT (0.659; 95% CI, 0.550-0.768; p > .05 for each comparison) in predicting in-hospital mortality. STESS with a cutoff of 3 was found to have lowest specificity and number of correctly classified episodes. EMSE-EAL with a cutoff at 40 had highest specificity and showed a trend towards more correctly classified episodes while sensitivity tended to be low. END-IT with a cutoff of 3 had the most balanced sensitivity-specificity ratio. CONCLUSIONS: EMSE-EAL is as easy to calculate as STESS and tended towards higher diagnostic accuracy. Adding information on premorbid functional status to STESS did not enhance outcome prediction. END-IT was not superior to other scores in prediction of in-hospital mortality despite including information of diagnostic work-up and response to initial treatment.

Predictive values of the Status Epilepticus in Pediatric Patients Severity Score and END-IT score for short-term prognosis of children with status epilepticus / 中华实用儿科临床杂志

Objective:To evaluate the predictive values of the Status Epilepticus in Pediatric Patients Severity Score (STEPSS) and END-IT score in the short-term prognosis of children with status epilepticus (SE).Methods:It was a retrospective study involving 103 children with SE who were admitted to the Qingdao Women and Children′s Hospital Affiliated to Qingdao University from January 1, 2012 to January 1, 2022.Glasgow Outcome Scale was used to evaluate the prognosis at discharge, and the children were divided into good prognosis group ( n=78) and poor prognosis group ( n=25). Risk factors for poor prognosis of SE in children were analyzed by Logistic regression.Receiver operating characteristic (ROC) curve was used to evaluate the prognostic values of STEPSS and END-IT score in children with SE. Results:Compared with those of the good prognosis group, significantly younger age [16 (9, 58) months vs.56 (21, 84) months, Z=-3.068, P=0.002], higher blood lactic acid levels [3.16 (2.43, 4.01) mmol/L vs.1.67 (1.32, 2.10) mmol/L, Z=-6.085, P<0.001], STEPSS scores [3.0(3.0, 4.0) points vs.1.0(1.0, 2.0) points, Z=-6.956, P<0.001], END-IT scores [3.0(1.5, 4.0) points vs.1.0(0, 1.0) points, Z=-5.502, P<0.001], proportion of developmental delay ( χ2=16.756, P<0.001), abnormal brain magnetic resonance imagine examination ( χ2=5.860, P=0.015), use of ventilator and multiple drugs (all P<0.001), and longer duration of anti-SE therapy time( Z=1.488, P=0.024) were detected in the poor prognosis group. Logistic regression analysis indicated that increased blood lactic acid ( OR=7.975, 95% CI: 2.705-23.518), increased drug types ( OR=14.562, 95% CI: 2.035-104.173), STEPSS scores( OR=8.914, 95% CI: 2.824-28.140) and END-IT scores ( OR=2.209, 95% CI: 1.046-4.667) were risk factors for the poor prognosis of SE in children.The area under the curve (AUC) of STEPSS in predicting the poor prognosis of SE in children was 0.939, with the cut-off value, sensitivity, specificity and Youden index of 2.5 points, 96.0%, 85.9% and 0.82, respectively.AUC of END-IT scores in predicting the poor prognosis of SE in children was 0.853, with the cut-off value, sensitivity, specificity and Youden index of 1.5 points, 76.0%, 75.6% and 0.52, respectively.AUC of STEPSS in predicting the poor prognosis of SE in children was significantly higher than that of END-IT scores ( U=36.91, P<0.05). The predictive value of STEPSS combined with END-IT was higher, and the sensitivity and negative predictive value of parallel test were 100.0%, while the specificity and positive predictive value of series test were 94.9% and 81.8%, respectively. Conclusions:STEPSS and END-IT scores may be used as predictors for the poor prognosis of SE in children.Their combination provides a better prediction.