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BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) in the cerebellum has a poor short-term prognosis, whereas data on the long-term case fatality and recurrent vascular events are sparse. Herewith, we aimed to assess the long-term case fatality and recurrence rate of vascular events after a first cerebellar ICH. METHODS: In this international cohort study, we included patients from 10 hospitals (the United States and Europe from 1997 to 2017) aged ≥18 years with a first spontaneous cerebellar ICH who were discharged alive. Data on long-term case fatality and recurrence of vascular events (recurrent ICH [supratentoria or infratentorial], ischemic stroke, myocardial infarction, or major vascular surgery) were collected for survival analysis and absolute event rate calculation. RESULTS: We included 405 patients with cerebellar ICH (mean age [SD], 72 [13] years, 49% female). The median survival time was 67 months (interquartile range, 23-100 months), with a cumulative survival rate of 34% at 10-year follow-up (median follow-up time per center ranged: 15-80 months). In the 347 patients with data on vascular events 92 events occurred in 78 patients, after initial cerebellar ICH: 31 (8.9%) patients had a recurrent ICH (absolute event rate, 1.8 per 100 patient-years [95% CI, 1.2-2.6]), 39 (11%) had an ischemic stroke (absolute event rate, 2.3 [95% CI, 1.6-3.2]), 13 (3.7%) had a myocardial infarction (absolute event rate, 0.8 [95% CI, 0.4-1.3]), and 5 (1.4%) underwent major vascular surgery (absolute event rate, 0.3 [95% CI, 0.1-0.7]). The median time to a first vascular event during follow-up was 27 months (interquartile range, 8.7-50 months), with a cumulative hazard of 47% at 10 years. CONCLUSIONS: The long-term prognosis of patients who survive a first spontaneous cerebellar ICH is poor and comparable to that of patients who survive a first supratentorial ICH. Further identification of patients at high risk of vascular events following the initial cerebellar ICH is needed. Including patients with cerebellar ICH in randomized controlled trials on secondary prevention of patients with ICH is warranted.
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BACKGROUND: Social determinants of health (SDOH) have been linked to neurocritical care outcomes. We sought to examine the extent to which SDOH explain differences in decisions regarding life-sustaining therapy, a key outcome determinant. We specifically investigated the association of a patient's home geography, individual-level SDOH, and neighborhood-level SDOH with subsequent early limitation of life-sustaining therapy (eLLST) and early withdrawal of life-sustaining therapy (eWLST), adjusting for admission severity. METHODS: We developed unique methods within the Bridge to Artificial Intelligence for Clinical Care (Bridge2AI for Clinical Care) Collaborative Hospital Repository Uniting Standards for Equitable Artificial Intelligence (CHoRUS) program to extract individual-level SDOH from electronic health records and neighborhood-level SDOH from privacy-preserving geomapping. We piloted these methods to a 7 years retrospective cohort of consecutive neuroscience intensive care unit admissions (2016-2022) at two large academic medical centers within an eastern Massachusetts health care system, examining associations between home census tract and subsequent occurrence of eLLST and eWLST. We matched contextual neighborhood-level SDOH information to each census tract using public data sets, quantifying Social Vulnerability Index overall scores and subscores. We examined the association of individual-level SDOH and neighborhood-level SDOH with subsequent eLLST and eWLST through geographic, logistic, and machine learning models, adjusting for admission severity using admission Glasgow Coma Scale scores and disorders of consciousness grades. RESULTS: Among 20,660 neuroscience intensive care unit admissions (18,780 unique patients), eLLST and eWLST varied geographically and were independently associated with individual-level SDOH and neighborhood-level SDOH across diagnoses. Individual-level SDOH factors (age, marital status, and race) were strongly associated with eLLST, predicting eLLST more strongly than admission severity. Individual-level SDOH were more strongly predictive of eLLST than neighborhood-level SDOH. CONCLUSIONS: Across diagnoses, eLLST varied by home geography and was predicted by individual-level SDOH and neighborhood-level SDOH more so than by admission severity. Structured shared decision-making tools may therefore represent tools for health equity. Additionally, these findings provide a major warning: prognostic and artificial intelligence models seeking to predict outcomes such as mortality or emergence from disorders of consciousness may be encoded with self-fulfilling biases of geography and demographics.
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Despite the persistently high prevalence of neurocognitive impairment in HIV-positive patients, routine HIV care in many resource-limited settings does not include neuropsychological assessment. The objective of this study was to examine the utility of a brief computerized battery for identifying neurocognitive impairment in a busy HIV clinic in Uganda. Specifically, we compared performance on a gold standard neuropsychological exam to that on the CogState Brief Battery. In this cross-sectional study, 181 HIV-positive patients completed both assessment batteries in a randomized order. The primary outcome measures were neurocognitive impairment on the standard exam defined by the global deficit score and cumulative performance on the CogState Brief Battery. Sixty-nine participants (38 %) were classified as impaired on the standard neuropsychological exam, and participants who were classified as impaired performed significantly worse on CogState compared to those who were unimpaired (p < 0.001). CogState had adequate specificity but low sensitivity, suggesting that it may not be a clinically useful screening tool to identify patients who likely have neurocognitive impairment in Uganda. This study supports the feasibility of using a computerized battery for assessing neurocognitive impairment in HIV-positive patients in resource-limited settings, but additional research is needed to identify screening tools with higher sensitivity for use in HIV clinics.
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Disfunción Cognitiva/diagnóstico , Infecciones por VIH/diagnóstico , Pruebas Neuropsicológicas , Adulto , Disfunción Cognitiva/complicaciones , Disfunción Cognitiva/fisiopatología , Disfunción Cognitiva/psicología , Estudios Transversales , Países en Desarrollo , Femenino , Infecciones por VIH/complicaciones , Infecciones por VIH/fisiopatología , Infecciones por VIH/psicología , Humanos , Masculino , Prevalencia , Sensibilidad y Especificidad , Índice de Severidad de la Enfermedad , UgandaRESUMEN
INTRODUCTION: Malnutrition is common in stroke patients and has been associated with poor functional outcomes and increased mortality after stroke. Previous research on nutrition status and post-intracerebral hemorrhage (ICH) outcomes, however, is limited and conflicting. PATIENTS AND METHODS: Monocenter study of patients with spontaneous deep or lobar ICH from a longitudinal cohort enrolling consecutive patients between 1994 and 2022. Nutrition status was assessed using admission body mass index (BMI), albumin, total bilirubin, cholesterol, c-reactive protein, hemoglobin a1c, high-density lipoprotein, hemoglobin, low-density lipoprotein, mean corpuscular volume, alanine transaminase, and triglycerides. Main outcome was favorable discharge outcome (mRS 0-2). Multivariable logistic regression was conducted with adjustment for baseline differences. RESULTS: Among 2170 patients, 1152 had deep and 1018 had lobar ICH. Overweight BMI was associated with higher odds of favorable discharge outcome in all (aOR = 3.01, 95% CI 1.59-5.69, p = 0.001) and lobar (aOR = 3.26, 95% CI 1.32-8.08, p = 0.011) ICH after adjustment for baseline differences. This association did not reach statistical significance in deep (aOR = 2.77, 95% CI 0.99-7.72, p = 0.052) ICH. No lab values were associated with functional outcome in all, deep, or lobar ICH after adjustment. DISCUSSION AND CONCLUSION: Overweight BMI was associated with favorable discharge status after ICH. These findings could inform future studies to determine whether overweight BMI has a protective effect in ICH patients.
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Background: Educational attainment is a critical social determinant of health that impacts the risk and severity of incident ischaemic stroke, but less is known of its impact on intracerebral haemorrhage (ICH). The objective of this study is to determine whether educational attainment is associated with ICH severity and short-term prognosis. Methods: Subjects were enrolled in a prospectively ascertained cohort with primary ICH from 1994 to 2020 at Massachusetts General Hospital. Educational attainment, medical history of ICH risk factors, ICH volume and ICH score were obtained on admission. The primary outcomes were ICH volume and the ICH score. Results: Of 2539 eligible patients eligible, the median age of the sample was 74 (IQR 64-82) and 2159 (85%) had high school-only education. 1655 (65%) presented with an ICH volume less than or equal to 30 mL and 1744 (69%) presented with an ICH score less than 3. In multivariable logistic regression analyses controlling for age, income, employment history and prestroke diagnoses of hypertension and coronary artery disease, patients with high school-only education were more likely to have an ICH volume greater than 30 mL compared with college diplomates (OR 1.58, 95% CI 1.24 to 2.08) and more likely to have an ICH score of 3 or greater compared with college diplomates (OR 2.37, 95% CI 1.77 to 3.19). Discussion: Prestroke educational attainment is independently associated with ICH severity and short-term prognosis, with lower educational attainment associated with larger ICH volumes and higher ICH scores. Future studies should examine how educational attainment impacts exposure to traditional clinical risk factors.
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Importance: Secondary prevention interventions to reduce post-stroke cognitive impairment (PSCI) can be aided by the early identification of high-risk individuals who would benefit from risk factor modification. Objective: To develop and evaluate a predictive model to identify patients at increased risk of PSCI over 5 years using data easily accessible from electronic health records. Design: Cohort study with patients enrolled between 2003-2016 with follow-up through 2022. Setting: Primary care practices affiliated with two academic medical centers. Participants: Individuals 45 years or older, without prior stroke or prevalent cognitive impairment, with primary care visits and an incident ischemic stroke between 2003-2016 (development/internal validation cohort) or 2010-2022 (external validation cohort). Exposures: Predictors of PSCI were ascertained from the electronic health record. Main Outcome: The outcome was incident dementia/cognitive impairment within 5 years and beginning 3 months following stroke, ascertained using ICD-9/10 codes. For model variable selection, we considered potential predictors of PSCI and constructed 400 bootstrap samples with two-thirds of the model derivation sample. We ran 10-fold cross-validated Cox proportional hazards models using a least absolute shrinkage and selection operator (LASSO) penalty. Variables selected in >25% of samples were included. Results: The analysis included 332 incident diagnoses of PSCI in the development cohort (n=3,741), and 161 and 128 incident diagnoses in the internal (n=1,925) and external (n=2,237) validation cohorts. The c-statistic for predicting PSCI was 0.731 (95% CI: 0.694-0.768) in the internal validation cohort, and 0.724 (95% CI: 0.681-0.766) in the external validation cohort. A risk score based on the beta coefficients of predictors from the development cohort stratified patients into low (0-7 points), intermediate (8-11 points), and high (12-35 points) risk groups. The hazard ratios for incident PSCI were significantly different by risk categories in internal (High, HR: 6.2, 95% CI 4.1-9.3; Intermediate, HR 2.7, 95% CI: 1.8-4.1) and external (High, HR: 6.1, 95% CI: 3.9-9.6; Intermediate, HR 2.8, 95% CI: 1.9-4.3) validation cohorts. Conclusions and Relevance: Five-year risk of PSCI can be accurately predicted using routinely collected data. Model output can be used to risk stratify and identify individuals at increased risk for PSCI for preventive efforts.
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BACKGROUND: Secondary prevention interventions to reduce post-stroke cognitive impairment (PSCI) can be aided by the early identification of high-risk individuals who would benefit from risk factor modification. AIMS: To develop and evaluate a predictive model to identify patients at increased risk of PSCI over 5 years using data easily accessible from electronic health records. METHODS: Cohort study that included primary care patients from two academic medical centers. Patients were aged 45 years or older, without prior stroke or prevalent cognitive impairment, with primary care visits and an incident ischemic stroke between 2003 and 2016 (development/internal validation cohort) or 2010 and 2022 (external validation cohort). Predictors of PSCI were ascertained from the electronic health record. The outcome was incident dementia/cognitive impairment within 5 years and beginning 3 months following stroke, ascertained using International Classification of Diseases, Ninth/Tenth Revision (ICD-9/10) codes. For model variable selection, we considered potential predictors of PSCI and constructed 400 bootstrap samples with two-thirds of the model derivation sample. We ran 10-fold cross-validated Cox proportional hazards models using a least absolute shrinkage and selection operator (LASSO) penalty. Variables selected in >25% of samples were included. RESULTS: The analysis included 332 incident diagnoses of PSCI in the development cohort (n = 3741), and 161 and 128 incident diagnoses in the internal (n = 1925) and external (n = 2237) validation cohorts, respectively. The C-statistic for predicting PSCI was 0.731 (95% confidence interval (CI): 0.694-0.768) in the internal validation cohort, and 0.724 (95% CI: 0.681-0.766) in the external validation cohort. A risk score based on the beta coefficients of predictors from the development cohort stratified patients into low (0-7 points), intermediate (8-11 points), and high (12-23 points) risk groups. The hazard ratios (HRs) for incident PSCI were significantly different by risk categories in internal (high, HR: 6.2, 95% CI: 4.1-9.3; Intermediate, HR: 2.7, 95% CI: 1.8-4.1) and external (high, HR: 6.1, 95% CI: 3.9-9.6; Intermediate, HR: 2.8, 95% CI: 1.9-4.3) validation cohorts. CONCLUSION: Five-year risk of PSCI can be accurately predicted using routinely collected data. Model output can be used to risk stratify and identify individuals at increased risk for PSCI for preventive efforts. DATA ACCESS STATEMENT: Mass General Brigham data contain protected health information and cannot be shared publicly. The data processing scripts used to perform analyses will be made available to interested researchers upon reasonable request to the corresponding author.
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Introduction: The 21-point Brain Care Score (BCS) is a novel tool designed to motivate individuals and care providers to take action to reduce the risk of stroke and dementia by encouraging lifestyle changes. Given that late-life depression is increasingly recognized to share risk factors with stroke and dementia, and is an important clinical endpoint for brain health, we tested the hypothesis that a higher BCS is associated with a reduced incidence of future depression. Additionally, we examined its association with a brain health composite outcome comprising stroke, dementia, and late-life depression. Methods: The BCS was derived from the United Kingdom Biobank baseline evaluation in participants with complete data on BCS items. Associations of BCS with the risk of subsequent incident late-life depression and the composite brain health outcome were estimated using multivariable Cox proportional hazard models. These models were adjusted for age at baseline and sex assigned at birth. Results: A total of 363,323 participants were included in this analysis, with a median BCS at baseline of 12 (IQR: 11-14). There were 6,628 incident cases of late-life depression during a median follow-up period of 13 years. Each five-point increase in baseline BCS was associated with a 33% lower risk of incident late-life depression (95% CI: 29%-36%) and a 27% lower risk of the incident composite outcome (95% CI: 24%-30%). Discussion: These data further demonstrate the shared risk factors across depression, dementia, and stroke. The findings suggest that a higher BCS, indicative of healthier lifestyle choices, is significantly associated with a lower incidence of late-life depression and a composite brain health outcome. Additional validation of the BCS is warranted to assess the weighting of its components, its motivational aspects, and its acceptability and adaptability in routine clinical care worldwide.
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OBJECTIVES: To investigate associations between health-related behaviors as measured using the Brain Care Score (BCS) and neuroimaging markers of white matter injury. METHODS: This prospective cohort study in the UK Biobank assessed the BCS, a novel tool designed to empower patients to address 12 dementia and stroke risk factors. The BCS ranges from 0 to 21, with higher scores suggesting better brain care. Outcomes included white matter hyperintensities (WMH) volume, fractional anisotropy (FA), and mean diffusivity (MD) obtained during 2 imaging assessments, as well as their progression between assessments, using multivariable linear regression adjusted for age and sex. RESULTS: We included 34,509 participants (average age 55 years, 53% female) with no stroke or dementia history. At first and repeat imaging assessments, every 5-point increase in baseline BCS was linked to significantly lower WMH volumes (25% 95% CI [23%-27%] first, 33% [27%-39%] repeat) and higher FA (18% [16%-20%] first, 22% [15%-28%] repeat), with a decrease in MD (9% [7%-11%] first, 10% [4%-16%] repeat). In addition, a higher baseline BCS was associated with a 10% [3%-17%] reduction in WMH progression and FA decline over time. DISCUSSION: This study extends the impact of the BCS to neuroimaging markers of clinically silent cerebrovascular disease. Our results suggest that improving one's BCS could be a valuable intervention to prevent early brain health decline.
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Neuroimagen , Humanos , Femenino , Masculino , Persona de Mediana Edad , Neuroimagen/métodos , Estudios Prospectivos , Encéfalo/diagnóstico por imagen , Sustancia Blanca/diagnóstico por imagen , Sustancia Blanca/patología , Imagen por Resonancia Magnética , Estudios de Cohortes , Imagen de Difusión Tensora , Factores de Riesgo , Anciano , AdultoRESUMEN
Cerebral small vessel disease is highly prevalent, particularly in marginalized communities, and its incidence is expected to increase given the aging global population. Cerebral small vessel disease contributes to risk for stroke, vascular cognitive impairment and dementia, late-life depression, and gait disorders. A growing body of evidence suggests that adverse outcomes, including cerebral small vessel disease, caused by traditional cardiovascular risk factors are at least partly mediated by epigenetic changes, some of them already beginning during fetal development. Societal and health care access inequities, summarized under the umbrella term social determinants of health, put a higher burden of cardiovascular risk factors on marginalized populations and expose them to an increased risk for adverse outcomes. Social epigenetics has begun to deliver solid evidence that social determinants of health lead to distinct epigenetic signatures that potentially mediate the biological effect of environmental exposures on cardiovascular risk factors. Here, we provide a review of the most recent advances in the epigenetics of cerebral small vessel disease risk factors and social determinants of health and call for research efforts combining insights from both fields to reach a deeper understanding of the causal pathways, ultimately facilitating discovery of new treatment targets for a disease whose burden is magnified by existing health disparities.
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Enfermedades de los Pequeños Vasos Cerebrales , Disfunción Cognitiva , Accidente Cerebrovascular , Humanos , Determinantes Sociales de la Salud , Enfermedades de los Pequeños Vasos Cerebrales/epidemiología , Enfermedades de los Pequeños Vasos Cerebrales/genética , Factores de RiesgoRESUMEN
Background: Intracerebral hemorrhage (ICH) disproportionally affects underserved populations, and coincides with risk factors for cardiovascular events and cognitive decline after ICH. We investigated associations between social determinants of health and management of blood pressure (BP), hyperlipidemia, diabetes, obstructive sleep apnea (OSA), and hearing impairment before and after ICH hospitalization. Methods: Survivors of the Massachusetts General Hospital longitudinal ICH study between 2016 and 2019 who received healthcare at least 6 months after ICH were analyzed. Measurements of BP, LDL and HbA1c and their management in the year surrounding ICH and referrals for sleep studies and audiology up to 6 months after ICH were gathered from electronic health records. The US-wide area deprivation index (ADI) was used as proxy for social determinants of health. Results: The study included 234 patients (mean 71 years, 42% female). BP measurements were performed in 109 (47%) before ICH, LDL measurements were performed in 165 (71%), and HbA1c measurements in 154 (66%) patients before or after ICH. 27/59 (46%) with off-target LDL and 3/12 (25%) with off-target HbA1c were managed appropriately. Of those without history of OSA or hearing impairment before ICH, 47/207 (23%) were referred for sleep studies and 16/212 (8%) to audiology. Higher ADI was associated with lower odds of BP, LDL, and HbA1c measurement prior to ICH [OR 0.94 (0.90-0.99), 0.96 (0.93-0.99), and 0.96 (0.93-0.99), respectively, per decile] but not with management during or after hospitalization. Conclusion: Social determinants of health are associated with pre-ICH management of cerebrovascular risk factors. More than 25% of patients were not assessed for hyperlipidemia and diabetes in the year surrounding ICH hospitalization, and less than half of those with off-target values received treatment intensification. Few patients were evaluated for OSA and hearing impairment, both common among ICH survivors. Future trials should evaluate whether using the ICH hospitalization to systematically address co-morbidities can improve long-term outcomes.
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Introduction: The 21-point Brain Care Score (BCS) was developed through a modified Delphi process in partnership with practitioners and patients to promote behavior changes and lifestyle choices in order to sustainably reduce the risk of dementia and stroke. We aimed to assess the associations of the BCS with risk of incident dementia and stroke. Methods: The BCS was derived from the United Kingdom Biobank (UKB) baseline evaluation for participants aged 40-69 years, recruited between 2006-2010. Associations of BCS and risk of subsequent incident dementia and stroke were estimated using Cox proportional hazard regressions, adjusted for sex assigned at birth and stratified by age groups at baseline. Results: The BCS (median: 12; IQR:11-14) was derived for 398,990 UKB participants (mean age: 57; females: 54%). There were 5,354 incident cases of dementia and 7,259 incident cases of stroke recorded during a median follow-up of 12.5 years. A five-point higher BCS at baseline was associated with a 59% (95%CI: 40-72%) lower risk of dementia among participants aged <50. Among those aged 50-59, the figure was 32% (95%CI: 20-42%) and 8% (95%CI: 2-14%) for those aged >59 years. A five-point higher BCS was associated with a 48% (95%CI: 39-56%) lower risk of stroke among participants aged <50, 52% (95%CI, 47-56%) among those aged 50-59, and 33% (95%CI, 29-37%) among those aged >59. Discussion: The BCS has clinically relevant and statistically significant associations with risk of dementia and stroke in approximately 0.4 million UK people. Future research includes investigating the feasibility, adaptability and implementation of the BCS for patients and providers worldwide.
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OBJECTIVES: Topographical distribution of white matter hyperintensities (WMH) are hypothesized to vary by cerebrovascular risk factors. We used an unbiased pattern discovery approach to identify distinct WMH spatial patterns and investigate their association with different WMH etiologies. METHODS: We performed a cross-sectional study on participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) to identify spatially distinct WMH distribution patterns using voxel-based spectral clustering analysis of aligned WMH probability maps. We included all participants from the ADNI Grand Opportunity/ADNI 2 study with available baseline 2D-FLAIR MRI scans, without prior history of stroke or presence of infarction on imaging. We evaluated the associations of these WMH spatial patterns with vascular risk factors, amyloid-ß PET, and imaging biomarkers of cerebral amyloid angiopathy (CAA), characterizing different forms of cerebral small vessel disease (CSVD) using multivariable regression. We also used linear regression models to investigate whether WMH spatial distribution influenced cognitive impairment. RESULTS: We analyzed MRI scans of 1,046 ADNI participants with mixed vascular and amyloid-related risk factors (mean age 72.9, 47.7% female, 31.4% hypertensive, 48.3% with abnormal amyloid PET). We observed unbiased partitioning of WMH into five unique spatial patterns: deep frontal, periventricular, juxtacortical, parietal, and posterior. Juxtacortical WMH were independently associated with probable CAA, deep frontal WMH were associated with risk factors for arteriolosclerosis (hypertension and diabetes), and parietal WMH were associated with brain amyloid accumulation, consistent with an Alzheimer's disease (AD) phenotype. Juxtacortical, deep frontal, and parietal WMH spatial patterns were associated with cognitive impairment. Periventricular and posterior WMH spatial patterns were unrelated to any disease phenotype or cognitive decline. DISCUSSION: Data-driven WMH spatial patterns reflect discrete underlying etiologies including arteriolosclerosis, CAA, AD, and normal aging. Global measures of WMH volume may miss important spatial distinctions. WMH spatial signatures may serve as etiology-specific imaging markers, helping to resolve WMH heterogeneity, identify the dominant underlying pathological process, and improve prediction of clinical-relevant trajectories that influence cognitive decline.
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INTRODUCTION: Although overall mortality of status epilepticus is high, baseline patient characteristics and co-morbidities may be helpful to predict outcomes and shape treatment decisions. Two previously published scoring systems exist to predict outcomes: the Status Epilepticus Severity Score (STESS) and the Epidemiology-based Mortality Score in Status Epilepticus (EMSE). However, a comparison of the two scores has not previously been completed in an American intensive care unit. We hypothesize that both scores will adequately predict the primary outcome of in-hospital death, but that the EMSE may more accurately predict functional outcomes, and significantly impact treatment decisions for both clinicians and families. METHODS: We performed a retrospective analysis of all cases of status epilepticus admitted to the Neuro-Critical Care Unit (NCCU) at the Ohio State University Wexner Medical Center from 6/1/2014 - 8/31/2015. We collected data on age, comorbidities, EEG findings, and seizure history. The primary outcome measured was in-hospital death; secondary outcomes included length of stay in the NCCU, placement of a tracheostomy and/or a percutaneous endoscopic gastrostomy upon discharge, and discharge location were used as surrogate markers for outcome severity. A sensitivity and specificity analysis was carried out, in addition to a student's t-test for a comparison of the two scores. ANOVA was completed to compare secondary outcomes RESULTS: Forty-six patients were admitted to the NCCU for management of status epilepticus during June 2014 and January 2016, thirteen of which experienced in-hospital death. The median age of the sample was 60, with approximately half of the sample (52.63%) having 3 or more comorbidities. The sensitivity of both EMSE and STESS were very high (100% and 90% respectively); however, the specificities were very low (28.6% and 42.9% respectively). A student's t-test between those who experienced in-hospital death and those who did not was only significant for EMSE at the p < 0.1 level (p = 0.055). Additionally, mean EMSE scores but not STESS scores, were significantly higher (p < 0.001) for those patients who were discharged to skilled nursing facilities or with hospice than compared to those who were discharged to home or to acute inpatient rehabilitation. CONCLUSIONS: The EMSE and STESS may be useful to predict outcomes of status epilepticus in populations with few comorbid conditions, but are less helpful when patients have multiple medical problems. Secondly, while neither score may be specific enough to differentiate for the primary outcome of death, their utility may be helpful to predict secondary outcomes that strongly affect clinical decisions. Based on these results, we believe a prospective trial of EMSE and STESS should be carried out to obtain more information on their utility, especially in American patients who may have more relevant comorbidities than in other countries.