Background

To explore intubation rates among patients with status epilepticus (SE) and the degree of institutional variation.

Methods

Serial cross-sectional study of SE-related hospitalizations from 2004 to 2013 using data from the National Inpatient Sample. The primary outcome was intubation of patients with SE. Multivariable models identified predictors of intubation, institutional variation in intubation rates, and the proportion of variance attributable to individual hospitals. This analysis was repeated using data from 5 states in the State Inpatient Databases (SID).

Results

There were 119 337 SE hospitalizations. The overall intubation rate was 32.7% (95% confidence interval [CI]: 32.2%-33.3%). There was marked variation in estimated intubation rates, ranging from 2% to 80% in the lowest and highest quintile after adjustment. There was somewhat less variability in the SID cohort where quintiles ranged from 10% to 54%. Those undergoing intubation were more often men and presenting with stroke, intracerebral hemorrhage, central nervous system infection, hyponatremia, and alcohol withdrawal. Urban location (odds ratio [OR]: 3.8, 95% CI: 2.7-5.5) and hospitalization at a teaching institution (OR: 3.9, 95% CI: 1.2-12.6) were even stronger predictors of intubation after adjustment for clinical factors. A regression including both patient- and hospital-level variables to predict intubation also performed better than a regression including patient factors alone (C statistic 0.81 vs 0.59, respectively).

Conclusions

There is considerable institutional variation in intubation rates for SE independent of patient characteristics suggesting that decisions around intubation rest heavily on where one is hospitalized. Further work is needed to clarify how this variation influences outcomes.

Objective

To characterize the most common neurologic diagnoses leading to hospitalization for homeless compared to housed individuals and to assess whether homelessness is an independent risk factor for 30-day readmission after an admission for a neurologic illness.

Methods

We performed a retrospective serial cross-sectional study using data from the Healthcare Cost and Utilization Project California State Inpatient Database from 2006 to 2011. Adult patients with a primary neurologic discharge diagnosis were included. The primary outcome was 30-day readmission. We used multilevel logistic regression to examine the association between homelessness and readmission after adjustment for patient factors.

Results

We identified 1,082,347 patients with a neurologic primary diagnosis. The rate of homelessness was 0.37%. The most common indications for hospitalization among homeless patients were seizure and traumatic brain injury, both of which were more common in the homeless compared to housed population (19.3% vs 8.1% and 31.9% vs 9.2%, respectively, p < 0.001). A multilevel mixed-effects model controlling for patient age, sex, race, insurance type, comorbid conditions, and clustering on the hospital level found that homelessness was associated with increased 30-day readmission (odds ratio 1.5, 95% confidence interval 1.4-1.6, p < 0.001). This association persisted after this analysis was repeated within specific diagnoses (patients with epilepsy, trauma, encephalopathy, and neuromuscular disease).

Conclusion

The most common neurologic reasons for admission among homeless patients are seizure and traumatic brain injury; these patients are at high risk for readmission. Future interventions should target the drivers of readmissions in this vulnerable population.

Background

We sought to determine the cumulative incidence of readmissions after a seizure-related hospitalization and identify risk factors and readmission diagnoses.

Methods

We performed a retrospective cohort study of adult patients hospitalized with a primary discharge diagnosis of seizure (International Classification of Diseases, Ninth Edition, Clinical Modification codes 345.xx and 780.3x) using the State Inpatient Databases across 11 states from 2009 to 2012. Hospital and community characteristics were obtained from the American Hospital Association and Robert Wood Johnson Foundation. We performed logistic regressions to explore effects of patient, hospital, and community factors on readmissions within 30 days of discharge.

Results

Of 98,712 patients, 13,929 (14%) were readmitted within 30 days. Reasons for readmission included epilepsy/convulsions (30% of readmitted patients), mood disorders (5%), schizophrenia (4%), and septicemia (4%). The strongest predictors of readmission were diagnoses of CNS tumor (odds ratio [OR] 2.1, 95% confidence interval [CI] 1.9-2.4) or psychosis (OR 1.8, 95% CI 1.7-1.8), urgent index admission (OR 2.0, 95% CI 1.8-2.2), transfer to nonacute facilities (OR 1.7, 95% CI 1.6-1.8), long length of stay (OR 1.7, 95% CI 1.6-1.8), and for-profit hospitals (OR 1.7, 95% CI 1.6-1.8). Our main model's c-statistic was 0.66. Predictors of readmission for status epilepticus included index admission for status epilepticus (OR 3.5, 95% CI 2.6-4.7), low hospital epilepsy volume (OR 0.4, 95% CI 0.3-0.7), and rural hospitals (OR 4.8, 95% CI 2.1-10.9).

Conclusion

Readmission is common after hospitalization for seizures. Prevention strategies should focus on recurrent seizures, the most common readmission diagnosis. Many factors were associated with readmission, although readmissions remain challenging to predict.

Background

Studies of emergent neuroimaging in the management of patients presenting with a breakthrough seizure are lacking. We sought to determine how often emergent computed tomography (CT) scans are obtained in patients with known epilepsy presenting with a seizure and how often acute abnormalities are found.

Methods

This multicenter retrospective cohort study was performed in the emergency department at 2 academic medical centers. The primary outcomes were percentage of visits where a CT scan was obtained, whether CT findings represented acute abnormalities, and whether these findings changed acute management.

Results

Of the 396 visits included, CT scans were obtained in 39%, and 8% of these scans demonstrated acute abnormalities. Patients who were older, had status epilepticus, a brain tumor, head trauma, or an abnormal examination were all significantly more likely to undergo acute neuroimaging (P < .05). In the multivariable model, only history of brain tumor (odds ratio [OR] 5.88, 95% confidence interval [CI], 1.33-26.1) and head trauma as a result of seizure (OR 3.92, 95% CI, 1.01-15.2) reached statistical significance in predicting an acutely abnormal scan. The likelihood of an acute imaging abnormality in visits for patients without a history of brain tumor or head trauma as a result of the seizure was 2.7% (2 visits). Both of these patients had abnormal neurological examinations.

Conclusion

Obtaining an emergent CT scan for patients with epilepsy presenting with a seizure may be avoidable in most cases, but might be indicated for patients with a history of brain tumor or head trauma as a result of seizure.

Objective

To examine the use of benzodiazepines and the association between low benzodiazepine dose, breakthrough seizures, and respiratory support in patients with status epilepticus.

Methods

In this cross-sectional analysis of adult patients with status epilepticus treated by an emergency medical services agency from 2013 to 2018, the primary outcome was treatment with a second benzodiazepine dose, an indicator for breakthrough seizure. The secondary outcome was receiving respiratory support. Midazolam was the only benzodiazepine administered.

Results

Among 2,494 patients with status epilepticus, mean age was 54.0 years and 1,146 (46%) were female. There were 1,537 patients given midazolam at any dose, yielding an administration rate of 62%. No patients received a dose and route consistent with national guidelines. Rescue therapy with a second midazolam dose was required in 282 (18%) patients. Higher midazolam doses were associated with lower odds of rescue therapy (odds ratio [OR], 0.8; 95% confidence interval [CI], 0.7-0.9) and were not associated with increased respiratory support. If anything, higher doses of midazolam were associated with decreased need for respiratory support after adjustment (OR, 0.9; 95% CI, 0.8-1.0).

Conclusions

An overwhelming majority of patients with status epilepticus did not receive evidence-based benzodiazepine treatment. Higher midazolam doses were associated with reduced use of rescue therapy and there was no evidence of respiratory harm, suggesting that benzodiazepines are withheld without clinical benefit.

Classification of evidence

This study provides Class III evidence that for patients with status epilepticus, higher doses of midazolam led to a reduced use of rescue therapy without an increased need for ventilatory support.

Importance

Identifying infectious causes of subacute or chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed.

Objective

To present a case series of patients with diagnostically challenging subacute or chronic meningitis using metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) supported by a statistical framework generated from mNGS of control samples from the environment and from patients who were noninfectious.

Design, setting, and participants

In this case series, mNGS data obtained from the CSF of 94 patients with noninfectious neuroinflammatory disorders and from 24 water and reagent control samples were used to develop and implement a weighted scoring metric based on z scores at the species and genus levels for both nucleotide and protein alignments to prioritize and rank the mNGS results. Total RNA was extracted for mNGS from the CSF of 7 participants with subacute or chronic meningitis who were recruited between September 2013 and March 2017 as part of a multicenter study of mNGS pathogen discovery among patients with suspected neuroinflammatory conditions. The neurologic infections identified by mNGS in these 7 participants represented a diverse array of pathogens. The patients were referred from the University of California, San Francisco Medical Center (n = 2), Zuckerberg San Francisco General Hospital and Trauma Center (n = 2), Cleveland Clinic (n = 1), University of Washington (n = 1), and Kaiser Permanente (n = 1). A weighted z score was used to filter out environmental contaminants and facilitate efficient data triage and analysis.

Main outcomes and measures

Pathogens identified by mNGS and the ability of a statistical model to prioritize, rank, and simplify mNGS results.

Results

The 7 participants ranged in age from 10 to 55 years, and 3 (43%) were female. A parasitic worm (Taenia solium, in 2 participants), a virus (HIV-1), and 4 fungi (Cryptococcus neoformans, Aspergillus oryzae, Histoplasma capsulatum, and Candida dubliniensis) were identified among the 7 participants by using mNGS. Evaluating mNGS data with a weighted z score-based scoring algorithm reduced the reported microbial taxa by a mean of 87% (range, 41%-99%) when taxa with a combined score of 0 or less were removed, effectively separating bona fide pathogen sequences from spurious environmental sequences so that, in each case, the causative pathogen was found within the top 2 scoring microbes identified using the algorithm.

Conclusions and relevance

Diverse microbial pathogens were identified by mNGS in the CSF of patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for 1 year, the first reported case of CNS vasculitis caused by Aspergillus oryzae, and the fourth reported case of C dubliniensis meningitis. Prioritizing metagenomic data with a scoring algorithm greatly clarified data interpretation and highlighted the problem of attributing biological significance to organisms present in control samples used for metagenomic sequencing studies.