BACKGROUND: Data comprehensively examining trends in central nervous system (CNS)-active polypharmacy are limited. The objective of this cross-sectional study was to characterize the composition of and trends in CNS-active medication use in US adults. METHODS: We included all participants ≥ 18 years old in the National Health and Nutrition Examination Study (NHANES), 2009-2020. The primary outcome was the percent of adults with CNS-active polypharmacy. This was defined as ≥ 3 medications among antidepressants [tricyclic, selective and serotonin-norepinephrine reuptake inhibitors (SSRIs and SNRIs), opioids, antiepileptics, antipsychotics, benzodiazepines, and nonbenzodiazepine receptor agonists (Z-drugs)]. Secondary outcomes included prevalence of any CNS-active medication and specific medications and classes over time, and their indications. Percentages were weighted according to NHANESs nationally representative sampling frame. log binomial regressions evaluated the relative risk (RR) for each outcome, comparing the last (2017-2020) versus the first (2010-2011) survey cycle. RESULTS: We included 34,189 adults (18.8% at least 65 years old) from five serial cross-sections (survey cycles). The prevalence of CNS-active polypharmacy was 2.1% in 2009-2010 and 2.6% in 2017-2020 [RR 1.18, 95% confidence interval (CI) 0.94-1.47]. The prevalence of CNS-active polypharmacy did not significantly change within any specific age group (e.g., age at least 65 years: RR 1.29, CI 0.74-2.24). The prevalence of any CNS-active medication was 21.0% in 2009 and 24.6% in 2017-2020 (RR] 1.12, 95% CI 1.02-1.25). A substantial increase occurred for antiepileptics (5.1-8.3%), specifically among participants aged 65 years and older (8.3-13.7%). This was largely driven by increasing gabapentin prevalence (1.4-3.6% overall; 3.3-7.9% age 65 years and older). Anticholinergic, SSRIs/SNRIs, antiepileptics, and benzodiazepines were elevated in most cycles for participants at least 65 years old compared with participants less than 65 years, and opioid use was increased in several cycles for older participants as well. Alprazolam was the most common benzodiazepine and third most common medication for anxiety/depression. Gabapentin was the most common CNS-active medication (3.6% of all participants in 2017-2020), followed by sertraline, citalopram, and acetaminophen-hydrocodone (each ~2%). The most common categories were antidepressants (13.7% in 2017-2020), followed by opioids (5.1% in 2017-2020). CONCLUSIONS: CNS-active medications are increasingly common, particularly gabapentin, and use of any CNS-active medication increased by 12%. Numerous CNS-active classes also increased in older adults throughout the years. Increasing suboptimal medication use highlight the need for further investigation into causes for potentially inappropriate prescribing, particularly for older adults.

BACKGROUND AND OBJECTIVES: EEG is widely recommended for status epilepticus (SE) management. However, EEG access and use across the United States is poorly characterized. We aimed to evaluate changes in inpatient EEG access over time and whether availability of EEG is associated with interhospital transfers for patients hospitalized with SE. METHODS: We performed a cross-sectional study using data available in the National Inpatient Sample data set from 2012 to 2018. We identified hospitals that used continuous or routine EEG during at least 1 seizure-related hospitalization in a given year using ICD-9 and ICD-10 procedure codes and defined these hospitals as EEG capable. We examined annual change in the proportion of hospitals that were EEG capable during the study period, compared characteristics of hospitals that were EEG capable with those that were not, and fit multivariable logistic regression models to determine whether hospital EEG capability was associated with likelihood of interhospital transfer. RESULTS: Among 4,550 hospitals in 2018, 1,241 (27.3%) were EEG capable. Of these, 1,188 hospitals (95.7%) were in urban settings. From 2012 to 2018, the proportion of hospitals that were EEG capable increased in urban settings (30.5%-41.1%, Mann-Kendall [M-K] test p < 0.001) and decreased in rural settings (4.0%-3.2%, M-K p = 0.026). Among 130,580 patients hospitalized with SE, 80,725 (61.8%) presented directly to an EEG-capable hospital. However, EEG use during hospitalization varied from 8% to 98%. Initial admission to a hospital without EEG capability was associated with 22% increased likelihood of interhospital transfer (adjusted RR 1.22, [95% CI, 1.09-1.37]; p < 0.01). Among those hospitalized at an EEG-capable hospital, patients admitted to hospitals in the lowest quintile of EEG volume were more than 2 times more likely to undergo interhospital transfer (adjusted RR 2.22, [95% CI 1.65-2.93]; p < 0.001). DISCUSSION: A minority of hospitals are EEG capable yet care for most patients with SE. Inpatient EEG use, however, varies widely among EEG-capable hospitals, and lack of inpatient EEG access is associated with interhospital transfer. Given the high incidence and cost of SE, there is a need to better understand the importance and use of EEG in this patient population to further organize inpatient epilepsy systems of care to optimize outcomes.

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

Traumatic brain injury (TBI) is thought to be a risk factor for Parkinson disease (PD), but results are conflicting. Many studies do not account for confounding or reverse causation. We sought to address these concerns by quantifying risk of PD after TBI compared to non-TBI trauma (NTT; defined as fractures).

Methods

Using inpatient/emergency department (ED) International Classification of Disease, Ninth Revision code data for California hospitals from 2005-2006, we identified patients aged ≥55 years with TBI (n = 52,393) or NTT (n = 113,406) and without baseline PD or dementia who survived hospitalization. Using Kaplan-Meier estimates and Cox proportional hazards models (adjusted for age, sex, race/ethnicity, income, comorbidities, health care use, and trauma severity), we estimated risk of PD after TBI during follow-up ending in 2011. We also assessed interaction with mechanism of injury (fall vs nonfall) and effect of TBI severity (mild vs moderate/severe) and TBI frequency (1 TBI vs >1 TBI).

Results

TBI patients were significantly more likely to be diagnosed with PD compared to NTT patients (1.7% vs 1.1%, p < 0.001, adjusted hazard ratio [HR] = 1.44, 95% confidence interval [CI] = 1.31-1.58). Risk of PD was similar for TBI sustained via falls versus nonfalls (interaction p = 0.6). Assessment by TBI severity (mild TBI: HR = 1.24, 95% CI = 1.04-1.48; moderate/severe TBI: HR = 1.50, 95% CI = 1.35-1.66) and TBI frequency (1 TBI: HR = 1.45, 95% CI = 1.30-1.60; >1 TBI: HR = 1.87, 95% CI = 1.58-2.21) revealed a dose response.

Interpretation

Among patients aged ≥55 years presenting to inpatient/ED settings with trauma, TBI is associated with a 44% increased risk of developing PD over 5 to 7 years that is unlikely to be due to confounding or reverse causation.

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.

STUDY OBJECTIVE: Guidelines recommend 10-mg intramuscular midazolam as the first-line treatment option for status epilepticus. However, in real-world practice, it is frequently administered intranasally or intravenously and is dosed lower. Therefore, we used conventional and instrumental variable approaches to examine the effectiveness of midazolam in a national out-of-hospital cohort. METHODS: This retrospective cohort study of adults with status epilepticus used the ESO Data Collaborative research dataset (January 1, 2019, to December 31, 2019). The exposures were the route and dose of midazolam. We performed hierarchical logistic regression and 2-stage least squares regression using agency treatment patterns as an instrument to examine our outcomes, rescue therapy, and ventilatory support. RESULTS: There were 7,634 out-of-hospital encounters from 657 EMS agencies. Midazolam was administered intranasally in 20%, intravenously in 46%, and intramuscularly in 35% of the encounters. Compared with intramuscular administration, intranasal midazolam increased (risk difference [RD], 6.5%; 95% confidence interval [CI], 2.4% to 10.5%) and intravenous midazolam decreased (RD, -11.1%; 95% CI, -14.7% to -7.5%) the risk of rescue therapy. The differences in ventilatory support were not statistically significant (intranasal RD, -1.5%; 95% CI, -3.2% to 0.3%; intravenous RD, -0.3%; 95% CI, -1.9% to 1.2%). Higher doses were associated with a lower risk of rescue therapy (RD, -2.6%; 95% CI, -3.3% to -1.9%) and increased ventilatory support (RD, 0.4%; 95% CI, 0.1% to 0.7%). The instrumental variable analysis yielded similar results, except that dose was not associated with ventilatory support. CONCLUSION: The route and dose of midazolam affect clinical outcomes. Compared with intramuscular administration, intranasal administration may be less effective and intravenous administration more effective in terminating status epilepticus, although the differences between these and previous results may reflect the nature of real-world data as opposed to randomized data.

OBJECTIVE: Dizziness is a common reason patients present to doctors, but effective diagnostic tests and treatments for dizziness are underused. The internet is a way to disseminate medical information and is emerging as an intervention platform. The objective of this study was to describe internet searches for dizziness terms to assess the possible consumer demand for internet-based dizziness diagnostic and treatment tools. STUDY DESIGN/METHODS: Google AdWords and Google Insights for Search were used for keyword search data on the following generic terms: vertigo, dizzy, dizziness, lightheaded, and lightheadedness. Data collected included keyword ideas (i.e., additional keywords identified by Google as being related search terms), global and US only monthly search frequencies, as well as trends in top searches related to dizziness terms from 2004 to 2012. Keywords suggestive of benign paroxysmal positional vertigo (BPPV) or BPPV processes were identified. RESULTS: Of the five generic dizziness terms, vertigo had the most global searches per month (1.83 million) and lightheadedness had the least (90,500). Four BPPV-specific terms had more than 100,000 global searches per month. Three BPPV terms (positional vertigo, benign vertigo, and benign positional vertigo) have been in the list of top searches related to vertigo every quarter since 2004. CONCLUSION: Substantial demand exists for dizziness information via the internet. Future studies should seek to better characterize the population seeking this information. The magnitude of this potential demand suggests that validated and tested diagnostic and treatment tools could contribute to healthcare efficiencies and patient outcomes.

Importance

Epidemiologic evidence regarding the importance of traumatic brain injury (TBI) as a risk factor for dementia is conflicting. Few previous studies have used patients with non-TBI trauma (NTT) as controls to investigate the influence of age and TBI severity.

Objective

To quantify the risk of dementia among adults with recent TBI compared with adults with NTT.

Design, setting, and participants

This retrospective cohort study was performed from January 1, 2005, through December 31, 2011 (follow-up, 5-7 years). All patients 55 years or older diagnosed as having TBI or NTT in 2005 and 2006 and who did not have baseline dementia or die during hospitalization (n = 164,661) were identified in a California statewide administrative health database of emergency department (ED) and inpatient visits.

Exposures

Mild vs moderate to severe TBI diagnosed by Centers for Disease Control and Prevention criteria using International Classification of Diseases, Ninth Revision (ICD-9)codes, and NTT, defined as fractures excluding fractures of the head and neck, diagnosed using ICD-9 codes.

Main outcomes and measures

Incident ED or inpatient diagnosis of dementia (using ICD-9 codes) 1 year or more after initial TBI or NTT. The association between TBI and risk of dementia was estimated using Cox proportional hazards models before and after adjusting for common dementia predictors and potential confounders. We also stratified by TBI severity and age category (55-64, 65-74, 75-84, and ≥85 years).

Results

A total of 51,799 patients with trauma (31.5%) had TBI. Of these, 4361 (8.4%) developed dementia compared with 6610 patients with NTT (5.9%) (P < .001). We found that TBI was associated with increased dementia risk (hazard ratio [HR], 1.46; 95% CI, 1.41-1.52; P < .001). Adjustment for covariates had little effect except adjustment for age category (fully adjusted model HR, 1.26; 95% CI, 1.21-1.32; P < .001). In stratified adjusted analyses, moderate to severe TBI was associated with increased risk of dementia across all ages (age 55-64: HR, 1.72; 95% CI, 1.40-2.10; P < .001; vs age 65-74: HR, 1.46; 95% CI, 1.30-1.64; P < .001), whereas mild TBI may be a more important risk factor with increasing age (age 55-64: HR, 1.11; 95% CI, 0.80-1.53; P = .55; vs age 65-74: HR, 1.25; 95% CI, 1.04-1.51; P = .02; age interaction P < .001).

Conclusions and relevance

Among patients evaluated in the ED or inpatient settings, those with moderate to severe TBI at 55 years or older or mild TBI at 65 years or older had an increased risk of developing dementia. Younger adults may be more resilient to the effects of recent mild TBI than older adults.

Purpose

To assess the intraocular pressure (IOP)-lowering effects of bimatoprost sustained-release implant (BimSR) in normotensive monkeys receiving topical bimatoprost.

Methods

Six eyes from six female, normotensive, cynomolgus monkeys were treated with once-daily topical latanoprost 0.005% plus twice-daily fixed-combination dorzolamide 2%/timolol 0.5%. At week 5, topical latanoprost was switched to once-daily topical bimatoprost 0.03% and twice-daily dorzolamide 2%/timolol 0.5% was continued. At week 8, BimSR 20 μg was administered intracamerally to three eyes and topical therapy was continued in all eyes. At week 12, all topical therapy was discontinued and animals were monitored for another 4 weeks. IOP was measured with a TonoVet rebound tonometer in nonsedated animals weekly for 16 weeks.

Results

Average mean (standard deviation) IOP was 19.8 (1.6) mm Hg at baseline, 15.7 (0.9) mm Hg during treatment with topical latanoprost/dorzolamide/timolol from weeks 1 to 5, and 14.2 (0.5) mm Hg during weeks 6 to 8 after topical latanoprost was switched to topical bimatoprost. After BimSR was added, average mean IOP during weeks 9 to 12 was 10.8 (1.3) mm Hg, a decrease of 3.9 mm Hg compared with the topical-only arm. When topical therapy was discontinued, IOP in BimSR-treated eyes remained below that in unmedicated eyes (15.8 [0.9] vs. 20.2 [0.2] mm Hg at weeks 14-16).

Conclusions

Intracameral BimSR has IOP-lowering effects additive to those of topical bimatoprost, suggesting an additional mechanism of action with intracameral drug delivery.

Translational relevance

Compared with topical bimatoprost, intracameral BimSR may have an additional mechanism of action of IOP lowering.

Deciphering the mechanisms that regulate the sensitivity of pathogen recognition receptors is imperative to understanding infection and inflammation. Here we demonstrate that the RNA triphosphatase dual-specificity phosphatase 11 (DUSP11) acts on both host and virus-derived 5'-triphosphate RNAs rendering them less active in inducing a RIG-I-mediated immune response. Reducing DUSP11 levels alters host triphosphate RNA packaged in extracellular vesicles and induces enhanced RIG-I activation in cells exposed to extracellular vesicles. Virus infection of cells lacking DUSP11 results in a higher proportion of triphosphorylated viral transcripts and attenuated virus replication, which is rescued by reducing RIG-I expression. Consistent with the activity of DUSP11 in the cellular RIG-I response, mice lacking DUSP11 display lower viral loads, greater sensitivity to triphosphorylated RNA, and a signature of enhanced interferon activity in select tissues. Our results reveal the importance of controlling 5'-triphosphate RNA levels to prevent aberrant RIG-I signaling and demonstrate DUSP11 as a key effector of this mechanism.