Geographic Variation of Prevalence of Alzheimer's Disease and Related Dementias in Central Appalachia.

Background: Alzheimer's disease and related dementias (ADRD) prevalence varies geographically in the United States. Objective: To assess whether the geographic variation of ADRD in Central Appalachia is explained by county-level sociodemographics or access to care. Methods: Centers for Medicare and Medicaid Services Public Use Files from 2015- 2018 were used to estimate county-level ADRD prevalence among all fee-for-service (FFS) beneficiaries with≥1 inpatient, skilled nursing facility, home health agency, hospital outpatient or Carrier claim with a valid ADRD ICD-9/10 code over three-years in Central Appalachia (Kentucky, North Carolina, Ohio, Tennessee, Virginia, and West Virginia). Negative binomial regression was used to estimate prevalence overall, by Appalachian/non-Appalachian designation, and by rural/urban classification. Models were then adjusted for county-level: 1) FFS demographics (age, gender, and Medicaid eligibility), comorbidities; 2) population sociodemographics (race/ethnicity, education, aging population distribution, and renter-occupied housing); and 3) diagnostic access (PCP visits, neurology visits, and imaging scans). Results: Across the 591 counties in the Central Appalachian region, the average prevalence of ADRD from 2015- 2018 was 11.8%. ADRD prevalence was modestly higher for Appalachian counties both overall (PR: 1.03; 95% CI: 1.02, 1.04) and after adjustment (PR: 1.02; 95% CI: 1.00, 1.03) compared to non-Appalachian counties. This difference was similar among rural and urban counties (p = 0.326) but varied by state (p = 0.004). Conclusions: The relative variation in ADRD prevalence in the Appalachian region was smaller than hypothesized. The case mixture of the dual eligible population, accuracy of the outcome measurement, and impact of educational attainment in this region may contribute to this observation.

Are adverse events higher among patients with acute optic neuritis prescribed glucocorticoids? A retrospective, longitudinal cohort study.

OBJECTIVE: Optic neuritis (ON) is an acute focal inflammation of the optic nerve routinely treated with glucocorticoids. We aimed to compare adverse events (AE) among glucocorticoid-treated and untreated patients in the real world to guide clinical decision making about treatment tradeoffs. DESIGN: Retrospective, longitudinal cohort study. SETTING: Claims study from a large, private insurer in the USA (2005-2019). PARTICIPANTS: Adults≥18 years old with ≥1 ICD9/10 ON diagnosis with an evaluation/management visit code, and ≥6 months continuous enrolment prior to and following ON diagnosis. INTERVENTION: Glucocorticoid prescription exposure. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome was any AE within 90 days of glucocorticoid prescription. Secondary outcome was AE assessment by severity. Generalised estimating equations with logit link assessed relationships between glucocorticoid prescription and AEs. High-dimensional propensity score analyses accounted for potential confounding (eg, sociodemographics and comorbidities). Sensitivity analyses restricted the cohort to high-dose prescriptions (≥100 mg prednisone equivalent, injection/infusion), AEs within 30 days, highly specific ON definition and traditional propensity score match. RESULTS: Of the 14 311 people with 17 404 ON claims, 66.3% were women (n=9481), predominantly White (78.2%; n=9940), with median age (IQR)=48 (37,60) years. Within 90 days of the claim, 15.7% (n=2733/17 404) were prescribed glucocorticoids. The median (IQR) prescription duration=10 (6,20) days. Any and severe AEs were higher among patients prescribed glucocorticoids versus none (any AEs: n=437/2733 (16.0%) vs n=1784/14 671 (12.2%), adjusted OR 1.33 (95% CI: 1.18 to 1.50); severe AEs: n=72/2733 (2.6%) vs n=273/14 671 (1.9%), adjusted OR 1.82 (95% CI: 1.37 to 2.35)). Sensitivity analyses were similar. CONCLUSIONS: Real-world glucocorticoid prescriptions among ON patients were short-term, associated with a 30% relative increase in potentially serious AEs captured within healthcare encounters, including those not previously observed, such as VTE. These results can inform treatment decisions, particularly for ON patients likely to experience only marginal benefits.

Billed advance care planning visits may be occurring among older adults with high risk of mortality.

CONTEXT: Advance care planning (ACP) is a process that helps people prepare to make decisions about their future medical care. OBJECTIVES: We sought to understand who was received billed ACP visits and measure the association with health care utilization, cost, and mortality. METHODS: We used a randomly sampled 20 % cohort of Medicare fee-for-service (FFS) beneficiaries' files to conduct a retrospective cohort study. Beneficiaries with a billed ACP visit were matched to controls using a 2-stage propensity score matching process that included assigning a pseudo-ACP visit date for controls. Outcomes included healthcare utilization, mortality, and total medical cost per month. We used descriptive statistics for univariate analysis and fit multilevel logistic regression, multilevel linear regression, or Cox regression models. RESULTS: We identified 183,513 beneficiaries who received any billed ACP visit and 550,539 matched controls. Of those who had a ACP visit, the mean age was 76.5 years and high-risk comorbidities were common: 16 % dementia, 10 % congestive heart failure, 10 % cancer. Beneficiaries who had an ACP visit had slightly more health care utilization than controls. Beneficiaries who had an ACP visit were more likely to die (3.1% vs. 1.0 %, p < 0.01, OR=3.0, 95 %CI 2.9-3.2) in the unadjusted and adjusted analyses compared to matched controls. Total monthly medical costs were 33 % higher among beneficiaries who had an ACP visit. CONCLUSION: Our results suggest that ACP visits may be preferentially utilized amongst individuals with higher risk of mortality. There may be an opportunity to increase ACP visits among older adults at lower risk for mortality. KEY MESSAGE: This article suggests that ACP visits are likely targeted to older adults with a higher risk of mortality than those at lower risk of mortality suggesting an opportunity to reach people before they are facing end-of-life decisions.

Status Epilepticus Identification and Treatment Among Emergency Medical Services Agencies.

This cross-sectional study examines the association between unidentified status epilepticus and prehospital benzodiazepine treatment.

Effect of Population-Level Blood Pressure Treatment Strategies on Cardiovascular and Cognitive Outcomes.

BACKGROUND: The large and increasing number of adults living with dementia is a pressing societal priority, which may be partially mitigated through improved population-level blood pressure (BP) control. We explored how tighter population-level BP control affects the incidence of atherosclerotic cardiovascular disease (ASCVD) events and dementia. METHODS: Using an open-source ASCVD and dementia simulation analysis platform, the Michigan Chronic Disease Simulation Model, we evaluated how optimal implementation of 2 BP treatments based on the Eighth Joint National Committee recommendations and SPRINT (Systolic Blood Pressure Intervention Trial) protocol would influence population-level ASCVD events, global cognitive performance, and all-cause dementia. We simulated 3 populations (usual care, Eighth Joint National Committee based, SPRINT based) using nationally representative data to annually update risk factors and assign ASCVD events, global cognitive performance scores, and dementia, applying different BP treatments in each population. We tabulated total ASCVD events, global cognitive performance, all-cause dementia, optimal brain health, and years lived in each state per population. RESULTS: Optimal implementation of SPRINT-based BP treatment strategy, compared with usual care, reduced ASCVD events in the United States by ≈77 000 per year and produced 0.4 more years of stroke- or myocardial infarction-free survival when averaged across all Americans. Population-level gains in years lived free of ASCVD events were greater for SPRINT-based than Eighth Joint National Committee-based treatment. Survival and years spent with optimal brain health improved with optimal SPRINT-based BP treatment implementation versus usual care: the average patient with hypertension lived 0.19 additional years and 0.3 additional years in optimal brain health. SPRINT-based BP treatment increased the number of years lived without dementia (by an average of 0.13 years/person with hypertension), but increased the total number of individuals with dementia, mainly through more adults surviving to advanced ages. CONCLUSIONS: Tighter BP control likely benefits most individuals but is unlikely to reduce dementia prevalence and might even increase the number of older adults living with dementia.

Development and validation of the Michigan Chronic Disease Simulation Model (MICROSIM).

Strategies to prevent or delay Alzheimer's disease and related dementias (AD/ADRD) are urgently needed, and blood pressure (BP) management is a promising strategy. Yet the effects of different BP control strategies across the life course on AD/ADRD are unknown. Randomized trials may be infeasible due to prolonged follow-up and large sample sizes. Simulation analysis is a practical approach to estimating these effects using the best available existing data. However, existing simulation frameworks cannot estimate the effects of BP control on both dementia and cardiovascular disease. This manuscript describes the design principles, implementation details, and population-level validation of a novel population-health microsimulation framework, the MIchigan ChROnic Disease SIMulation (MICROSIM), for The Effect of Lower Blood Pressure over the Life Course on Late-life Cognition in Blacks, Hispanics, and Whites (BP-COG) study of the effect of BP levels over the life course on dementia and cardiovascular disease. MICROSIM is an agent-based Monte Carlo simulation designed using computer programming best practices. MICROSIM estimates annual vascular risk factor levels and transition probabilities in all-cause dementia, stroke, myocardial infarction, and mortality in a nationally representative sample of US adults 18+ using the National Health and Nutrition Examination Survey (NHANES). MICROSIM models changes in risk factors over time, cognition and dementia using changes from a pooled dataset of individual participant data from 6 US prospective cardiovascular cohort studies. Cardiovascular risks were estimated using a widely used risk model and BP treatment effects were derived from meta-analyses of randomized trials. MICROSIM is an extensible, open-source framework designed to estimate the population-level impact of different BP management strategies and reproduces US population-level estimates of BP and other vascular risk factors levels, their change over time, and incident all-cause dementia, stroke, myocardial infarction, and mortality.

Association of Traditional and Nontraditional Risk Factors in the Development of Strokes Among Young Adults by Sex and Age Group: A Retrospective Case-Control Study.

BACKGROUND: Despite women having fewer traditional risk factors (eg, hypertension, diabetes), strokes are more common in women than men aged ≤45 years. This study examined the contributions of traditional and nontraditional risk factors (eg, migraine, thrombophilia) in the development of strokes among young adults. METHODS: This retrospective case-control study used Colorado's All Payer Claims Database (2012-2019). We identified index stroke events in young adults (aged 18-55 years), matched 1:3 to stroke-free controls, by (1) sex, (2) age±2 years, (3) insurance type, and (4) prestroke period. All traditional and nontraditional risk factors were identified from enrollment until a stroke or proxy-stroke date (defined as the prestroke period). Conditional logistic regression models stratified by sex and age group first assessed the association of stroke with counts of risk factors by type and then computed their individual and aggregated population attributable risks. RESULTS: We included 2618 cases (52% women; 73.3% ischemic strokes) and 7827 controls. Each additional traditional and nontraditional risk factors were associated with an increased risk of stroke in all sex and age groups. In adults aged 18 to 34 years, more strokes were associated with nontraditional (population attributable risk: 31.4% men and 42.7% women) than traditional risk factors (25.3% men and 33.3% women). The contribution of nontraditional risk factors declined with age (19.4% men and 27.9% women aged 45-55 years). The contribution of traditional risk factors peaked among patients aged 35 to 44 years (32.8% men and 39.7% women). Hypertension was the most important traditional risk factor and increased in contribution with age (population attributable risk: 27.8% men and 26.7% women aged 45 to 55 years). Migraine was the most important nontraditional risk factor and decreased in contribution with age (population attributable risk: 20.1% men and 34.5% women aged 18-35 years). CONCLUSIONS: Nontraditional risk factors were as important as traditional risk factors in the development of strokes for both young men and women and have a stronger association with the development of strokes in adults younger than 35 years of age.

Prescription Drug Prices: An AAN Position Statement.

This position statement serves to establish the AAN's stance on the methods to address the cost of prescription drugs being considered by state and federal policymakers so that the AAN can continue to advocate effectively for its members. Neurologists seek to provide high-value care for patients with neurologic diseases at the lowest cost possible. However, many therapies for neurologic diseases are among the most expensive in the United States. The 3 major cost challenges include (1) unjustified increases in the pricing for drugs used to treat neurologic disorders, (2) the high cost of medications used to treat rare diseases where there are limited or no therapeutic options available, and (3) the high cost of noninnovative (already FDA-approved) therapies that used accelerated FDA approval pathways or Orphan Drug Act designated to expedite approvals in neurologic disorders. In each of these cases, AAN is concerned that the high cost does not deliver sufficient value to patients or society. The AAN's position is that action must be taken to ensure that effective prescription medications are accessible for patients with complex, chronic neurologic conditions. Potential solutions should be affordable, simple, and transparent. Cost-containment efforts must also address the burden on the entire healthcare system because high prescription drug prices may be shifted and absorbed in ways that negatively affect patient and prescriber access to important medications. AAN supports price negotiations, the cost saving potential of generics and biosimilars, development of novel therapeutics, price transparency, and importation.

Hospital variation of outcomes in status epilepticus.

OBJECTIVE: Understanding factors driving variation in status epilepticus outcomes would be critical to improve care. We evaluated the degree to which patient and hospital characteristics explained hospital-to-hospital variability in intubation and postacute outcomes. METHODS: This was a retrospective cohort study of Medicare beneficiaries admitted with status epilepticus between 2009 and 2019. Outcomes included intubation, discharge to a facility, and 30- and 90-day readmissions and mortality. Multilevel models calculated percent variation in each outcome due to hospital-to-hospital differences. RESULTS: We included 29 150 beneficiaries. The median age was 68 years (interquartile range [IQR] = 57-78), and 18 084 (62%) were eligible for Medicare due to disability. The median (IQR) percentages of each outcome across hospitals were: 30-day mortality 25% (0%-38%), any 30-day readmission 14% (0%-25%), 30-day status epilepticus readmission 0% (0%-3%), 30-day facility stay 40% (25%-53%), and intubation 46% (20%-61%). However, after accounting for many hospitals with small sample size, hospital-to-hospital differences accounted for 2%-6% of variation in all unadjusted outcomes, and approximately 1%-5% (maximally 8% for 30-day readmission for status epilepticus) after adjusting for patient, hospitalization, and/or hospital characteristics. Although many characteristics significantly predicted outcomes, the largest effect size was cardiac arrest predicting death (odds ratio = 10.1, 95% confidence interval = 8.8-11.7), whereas hospital characteristics (e.g., staffing, accreditation, volume, setting, services) all had lesser effects. SIGNIFICANCE: Hospital-to-hospital variation explained little variation in studied outcomes. Rather, certain patient characteristics (e.g., cardiac arrest) had greater effects. Interventions to improve outcomes after status epilepticus may be better focused on individual or prehospital factors, rather than at the inpatient systems level.

Validation of Vascular Location Subcodes for Acute Ischemic Stroke by the International Classification of Diseases-10.

BACKGROUND: Vascular region of infarct is part of the International Classification of Diseases-10 (ICD-10) coding scheme for ischemic stroke. These data could potentially be used for studies about vascular location, such as comparisons of anterior versus posterior circulation stroke. The objective of this study was to evaluate the validity of these subcodes. METHODS: We selected a random sample of 100 hospitalizations specifying 50 with anterior circulation ICD-10 ischemic stroke (carotid, anterior cerebral artery [CA], middle CA) and 50 with posterior circulation stroke (vertebral, basilar, cerebellar, posterior CA). The gold standard primary vascular distribution was scored using imaging studies and reports, blinded to the subcode. We compared gold-standard distribution to coded distribution and calculated the operating characteristics of ICD-10 posterior circulation versus anterior circulation codes with the gold standard. We also calculated the kappa statistic for agreement across all 7 vascular regions. RESULTS: In our population of 100 strokes, mean NIHSS was 8 (SD, 8). Head CT was performed in 95 % (95/100) and MRI in 77 % (77/100). The gold standard classified 55 primary posterior circulation strokes (26 PCA, 16 cerebellar, 8 basilar, 5 vertebral), 44 primary anterior circulation strokes (35 MCA, 6 carotid, 3 ACA), and 1 stroke with no infarct on imaging. The accuracy of the ICD-10 classification for primary posterior circulation stroke versus anterior circulation/no infarct was: sensitivity 89 % (49/55); specificity 98 % (44/45); positive predictive value 98 % (49/50); negative predictive value 88 % (44/50). The reliability of the 7-region classification was excellent (kappa 0.85). CONCLUSIONS: We found that ICD-10 classification of vascular location in routine practice correlates strongly with gold-standard localization for hospitalized ischemic stroke and supports validity in differentiating posterior versus anterior circulation. At a more granular vascular level, the location reliability was excellent, although limited data were available for some subcodes.

National- and State-Level Trends in Medicare Hospice Beneficiaries for Stroke During 2013 to 2019 in the United States.

BACKGROUND: Stroke is the fifth leading cause of death in the United States, one of the leading contributors to Medicare cost, including through Medicare hospice benefits, and the rate of stroke mortality has been increasing since 2013. We hypothesized that hospice utilization among Medicare beneficiaries with stroke has increased over time and that the increase is associated with trends in stroke death rate. METHODS: Using Medicare Part A claims data and Centers for Disease Control mortality data at a national and state level from 2013 to 2019, we report the proportion and count of Medicare hospice beneficiaries with stroke as well as the stroke death rate (per 100 000) in Medicare-eligible individuals aged ≥65 years. RESULTS: From 2013 to 2019, the number of Medicare hospice beneficiaries with stroke as their primary diagnosis increased 104.1% from 78 812 to 160 884. The number of stroke deaths in the United States in individuals aged ≥65 years also increased from 109 602 in 2013 to 129 193 in 2019 (17.9% increase). In 2013, stroke was the sixth most common primary diagnosis for Medicare hospice, while in 2019 it was the third most common, surpassed only by cancer and dementia. The correlation between the change from 2013 to 2019 in state-level Medicare hospice for stroke and stroke death rate for Medicare-eligible adults was significant (Spearman ρ=0.5; P<0.001). In a mixed-effects model, the variance in the state-level proportion of Medicare hospice for stroke explained by the state-level stroke death rate was 48.2%. CONCLUSIONS: From 2013 to 2019, the number of Medicare hospice beneficiaries with a primary diagnosis of stroke more than doubled and stroke jumped from the sixth most common indication for hospice to the third most common. While increases in stroke mortality in the Medicare-eligible population accounts for some of the increase of Medicare hospice beneficiaries, over half the variance remains unexplained and requires additional research.

Variation in seizure risk increases from antiseizure medication withdrawal among patients with well-controlled epilepsy: A pooled analysis.

OBJECTIVE: Guidelines suggest considering antiseizure medication (ASM) discontinuation in seizure-free patients with epilepsy. Past work has poorly explored how discontinuation effects vary between patients. We evaluated (1) what factors modify the influence of discontinuation on seizure risk; and (2) the range of seizure risk increase due to discontinuation across low- versus high-risk patients. METHODS: We pooled three datasets including seizure-free patients who did and did not discontinue ASMs. We conducted time-to-first-seizure analyses. First, we evaluated what individual patient factors modified the relative effect of ASM discontinuation on seizure risk via interaction terms. Then, we assessed the distribution of 2-year risk increase as predicted by our adjusted logistic regressions. RESULTS: We included 1626 patients, of whom 678 (42%) planned to discontinue all ASMs. The mean predicted 2-year seizure risk was 43% [95% confidence interval (CI) 39%-46%] for discontinuation versus 21% (95% CI 19%-24%) for continuation. The mean 2-year absolute seizure risk increase was 21% (95% CI 18%-26%). No individual interaction term was significant after correcting for multiple comparisons. The median [interquartile range (IQR)] risk increase across patients was 19% (IQR 14%-24%; range 7%-37%). Results were unchanged when restricting analyses to only the two RCTs. SIGNIFICANCE: No single patient factor significantly modified the influence of discontinuation on seizure risk, although we captured how absolute risk increases change for patients that are at low versus high risk. Patients should likely continue ASMs if even a 7% 2-year increase in the chance of any more seizures would be too much and should likely discontinue ASMs if even a 37% risk increase would be too little. In between these extremes, individualized risk calculation and a careful understanding of patient preferences are critical. Future work will further develop a two-armed individualized seizure risk calculator and contextualize seizure risk thresholds below which to consider discontinuation. PLAIN LANGUAGE SUMMARY: Understanding how much antiseizure medications (ASMs) decrease seizure risk is an important part of determining which patients with epilepsy should be treated, especially for patients who have not had a seizure in a while. We found that there was a wide range in the amount that ASM discontinuation increases seizure risk-between 7% and 37%. We found that no single patient factor modified that amount. Understanding what a patient's seizure risk might be if they discontinued versus continued ASM treatment is critical to making informed decisions about whether the benefit of treatment outweighs the downsides.

Geographic Distribution of Social Service Resources for Stroke Survivors in Ohio Varies by Rurality.

BACKGROUND: Both social service resources and stroke prevalence vary by geography, and health care resources are scarcer in rural areas. We assessed whether distributions of resources relevant to stroke survivors were clustered around areas of the highest stroke prevalence in Ohio and whether this is varied by rurality using an ecological study design. METHODS: Census tract (CT)-level self-reported stroke prevalence estimates (Centers for Disease Control and Prevention PLACES-2019 Behavioral Risk Factor Surveillance System) were linked with sociodemographic and rurality data (2019 American Community Survey) and geographic density of resources in Ohio (2020 findhelp data). Resources were grouped into categories: housing, in-home, financial, transportation, education, and therapy. Negative binomial regression models estimated the mean number of resources within 25 miles and 30 minutes of a CT centroid and quartiles of stroke prevalence for each resource group by rurality status (rural, urban, and suburban). Models were sequentially adjusted for total population and CT demographics. RESULTS: In Ohio, stroke prevalence was 3.9% (0.4%-14.2%). The highest stroke prevalence quartile (versus lowest) was associated with fewer resources within 25 miles overall (resource ratio [RR], 0.57-0.98). The most pronounced disparities were in rural CT; rural CTs with the highest quartile stroke prevalence had fewer housing (RR, 0.49 [95% CI, 0.32-0.75]), in-home (RR, 0.31 [95% CI, 0.20-0.49]), and therapy (RR, 0.23 [95% CI, 0.13-0.43]) resources compared with those with the lowest quartile stroke prevalence (reference: mean, 1.2 housing, 5.1 in-home, and 4.9 therapy resources, respectively). Rural disparities no longer persisted after adjustment for federal poverty limit (rural: housing [RR, 0.69 (95% CI, 0.40-1.20)], in-home [RR, 0.65 (95% CI, 0.34-1.23)], and therapy [RR, 0.66 (95% CI, 0.33-1.32)]). CONCLUSIONS: Stroke social service resources are inversely distributed relative to stroke prevalence in Ohio, particularly in rural areas. This inverse link in rural Ohio is likely explained by geographic differences in poverty. Stroke-specific resource-related interventions may be needed and should consider the roles of rurality and poverty.

Secular Trends in Central Nervous System-Active Polypharmacy Among Serial Cross-Sections of US Adults, 2009-2020.

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 NHANES's 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.

Patient Travel Distance to Neurologist Visits.

BACKGROUND AND OBJECTIVES: The density of neurologists within a given geographic region varies greatly across the United States. We aimed to measure patient travel distance and travel time to neurologist visits, across neurologic conditions and subspecialties. Our secondary goal was to identify factors associated with long-distance travel for neurologic care. METHODS: We performed a cross-sectional analysis using a 2018 Medicare sample of patients with at least 1 outpatient neurologist visit. Long-distance travel was defined as driving distance ≥50 miles 1-way to the visit. Travel time was measured as driving time in minutes. Multilevel generalized linear mixed models with logistic link function, which accounted for clustering of patients within hospital referral region and allowed modeling of region-specific random effects, were used to determine the association of patient and regional characteristics with long-distance travel. RESULTS: We identified 563,216 Medicare beneficiaries with a neurologist visit in 2018. Of them, 96,213 (17%) traveled long distance for care. The median driving distance and time were 81.3 (interquartile range [IQR]: 59.9-144.2) miles and 90 (IQR: 69-149) minutes for patients with long-distance travel compared with 13.2 (IQR: 6.5-23) miles and 22 (IQR: 14-33) minutes for patients without long-distance travel. Comparing across neurologic conditions, long-distance travel was most common for nervous system cancer care (39.6%), amyotrophic lateral sclerosis [ALS] (32.1%), and MS (22.8%). Many factors were associated with long-distance travel, most notably low neurologist density (first quintile: OR 3.04 [95% CI 2.41-3.83] vs fifth quintile), rural setting (4.89 [4.79-4.99]), long-distance travel to primary care physician visit (3.6 [3.51-3.69]), and visits for ALS and nervous system cancer care (3.41 [3.14-3.69] and 5.27 [4.72-5.89], respectively). Nearly one-third of patients bypassed the nearest neurologist by 20+ miles, and 7.3% of patients crossed state lines for neurologist care. DISCUSSION: We found that nearly 1 in 5 Medicare beneficiaries who saw a neurologist traveled ≥50 miles 1-way for care, and travel burden was most common for lower-prevalence neurologic conditions that required coordinated multidisciplinary care. Important potentially addressable predictors of long-distance travel were low neurologist density and rural location, suggesting interventions to improve access to care such as telemedicine or neurologic subspecialist support to local neurologists. Future work should evaluate differences in clinical outcomes between patients with long-distance travel and those without.

Prediction of Multiple Individual Primary Cardiovascular Events Using Pooled Cohorts.

Introduction: Most current clinical risk prediction scores for cardiovascular disease prevention use a composite outcome. Risk prediction scores for specific cardiovascular events could identify people who are at higher risk for some events than others informing personalized care and trial recruitment. We sought to predict risk for multiple different events, describe how those risks differ, and examine if these differences could improve treatment priorities. Methods: We used participant-level data from five cohort studies. We included participants between 40 and 79 years old who had no history of myocardial infarction (MI), stroke, or heart failure (HF). We made separate models to predict 10-year rates of first atherosclerotic cardiovascular disease (ASCVD), first fatal or nonfatal MI, first fatal or nonfatal stroke, new-onset HF, fatal ASCVD, fatal MI, fatal stroke, and all-cause mortality using established ASCVD risk factors. To limit overfitting, we used elastic net regularization with alpha = 0.75. We assessed the models for calibration, discrimination, and for correlations between predicted risks for different events. We also estimated the potential impact of varying treatment based on patients who are high risk for some ASCVD events, but not others. Results: Our study included 24,505 people; 55.6% were women, and 20.7% were non-Hispanic Black. Our models had C-statistics between 0.75 for MI and 0.85 for HF, good calibration, and minimal overfitting. The models were least similar for fatal stroke and all MI (0.58). In 1,840 participants whose risk of MI but not stroke or all-cause mortality was in the top quartile, we estimate one blood pressure-lowering medication would have a 2.4% chance of preventing any ASCVD event per 10 years. A moderate-strength statin would have a 2.1% chance. In 1,039 participants who had top quartile risk of stroke but not MI or mortality, a blood pressure-lowering medication would have a 2.5% chance of preventing an event, but a moderate-strength statin, 1.6%. Conclusion: We developed risk scores for eight key clinical events and found that cardiovascular risk varies somewhat for different clinical events. Future work could determine if tailoring decisions by risk of separate events can improve care.

Predictors of referral for long-term EEG monitoring for Medicare beneficiaries with drug-resistant epilepsy.

OBJECTIVE: For people with drug-resistant epilepsy, the use of epilepsy surgery is low despite favorable odds of seizure freedom. To better understand surgery utilization, we explored factors associated with inpatient long-term EEG monitoring (LTM), the first step of the presurgical pathway. METHODS: Using 2001-2018 Medicare files, we identified patients with incident drug-resistant epilepsy using validated criteria of ≥2 distinct antiseizure medication (ASM) prescriptions and ≥1 drug-resistant epilepsy encounter among patients with ≥2 years pre- and ≥1 year post-diagnosis Medicare enrollment. We used multilevel logistic regression to evaluate associations between LTM and patient, provider, and geographic factors. We then analyzed neurologist-diagnosed patients to further evaluate provider/environmental characteristics. RESULTS: Of 12 044 patients with incident drug-resistant epilepsy diagnosis identified, 2% underwent surgery. Most (68%) were diagnosed by a neurologist. In total, 19% underwent LTM near/after drug-resistant epilepsy diagnosis; another 4% only underwent LTM much prior to diagnosis. Patient factors most strongly predicting LTM were age <65 (adjusted odds ratio 1.5 [95% confidence interval 1.3-1.8]), focal epilepsy (1.6 [1.4-1.9]), psychogenic non-epileptic spells diagnosis (1.6 [1.1-2.5]) prior hospitalization (1.7, [1.5-2]), and epilepsy center proximity (1.6 [1.3-1.9]). Additional predictors included female gender, Medicare/Medicaid non-dual eligibility, certain comorbidities, physician specialties, regional neurologist density, and prior LTM. Among neurologist-diagnosed patients, neurologist <10 years from graduation, near an epilepsy center, or epilepsy-specialized increased LTM likelihood (1.5 [1.3-1.9], 2.1 [1.8-2.5], 2.6 [2.1-3.1], respectively). In this model, 37% of variation in LTM completion near/after diagnosis was explained by individual neurologist practice and/or environment rather than measurable patient factors (intraclass correlation coefficient 0.37). SIGNIFICANCE: A small proportion of Medicare beneficiaries with drug-resistant epilepsy completed LTM, a proxy for epilepsy surgery referral. While some patient factors and access measures predicted LTM, non-patient factors explained a sizable proportion of variance in LTM completion. To increase surgery utilization, these data suggest initiatives targeting better support of neurologist referral.