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.

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.

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.

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.

Association of the Stroke Ready Community-Based Participatory Research Intervention With Incidence of Acute Stroke Thrombolysis in Flint, Michigan.

Importance: Acute stroke treatment rates in the US lag behind those in other high-income nations. Objective: To assess whether a hospital emergency department (ED) and community intervention was associated with an increased proportion of patients with stroke receiving thrombolysis. Design, Setting, and Participants: This nonrandomized controlled trial of the Stroke Ready intervention took place in Flint, Michigan, from October 2017 to March 2020. Participants included adults living in the community. Data analysis was completed from July 2022 to May 2023. Intervention: Stroke Ready combined implementation science and community-based participatory research approaches. Acute stroke care was optimized in a safety-net ED, and then a community-wide, theory-based health behavior intervention, including peer-led workshops, mailers, and social media, was conducted. Main Outcomes and Measures: The prespecified primary outcome was the proportion of patients hospitalized with ischemic stroke or transient ischemic attack from Flint who received thrombolysis before and after the intervention. The association between thrombolysis and the Stroke Ready combined intervention, including the ED and community components, was estimated using logistic regression models, clustering at the hospital level and adjusting for time and stroke type. In prespecified secondary analyses, the ED and community intervention were explored separately, adjusting for hospital, time, and stroke type. Results: In total, 5970 people received in-person stroke preparedness workshops, corresponding to 9.7% of the adult population in Flint. There were 3327 ischemic stroke and TIA visits (1848 women [55.6%]; 1747 Black individuals [52.5%]; mean [SD] age, 67.8 [14.5] years) among patients from Flint seen in the relevant EDs, including 2305 in the preintervention period from July 2010 to September 2017 and 1022 in the postintervention period from October 2017 to March 2020. The proportion of thrombolysis usage increased from 4% in 2010 to 14% in 2020. The combined Stroke Ready intervention was not associated with thrombolysis use (adjusted odds ratio [OR], 1.13; 95% CI, 0.74-1.70; P = .58). The ED component was associated with an increase in thrombolysis use (adjusted OR, 1.63; 95% CI, 1.04-2.56; P = .03), but the community component was not (adjusted OR, 0.99; 95% CI, 0.96-1.01; P = .30). Conclusions and Relevance: This nonrandomized controlled trial found that a multilevel ED and community stroke preparedness intervention was not associated with increased thrombolysis treatments. The ED intervention was associated with increased thrombolysis usage, suggesting that implementation strategies in partnership with safety-net hospitals may increase thrombolysis usage. Trial Registration: ClinicalTrials.gov Identifier: NCT036455900.

Prescription Opioid Initiation for Neuropathy, Headache, and Low Back Pain: A US Population-based Medicare Study.

Neuropathy, headache, and low back pain (LBP) are common conditions requiring pain management. Yet little is known regarding whether access to specialists impacts opioid prescribing. We aimed to identify factors associated with opioid initiation among opioid-naïve older adults and evaluate how access to particular specialists impacts prescribing. This retrospective cohort study used a 20% Medicare sample from 2010 to 2017. Opioid initiation was defined as a first opioid prescription filled within 12 months after a diagnosis encounter. Disease-related opioid initiation was defined as a first opioid prescription filled within 7 days following a disease-specific claim. Logistic regression using generalized estimating equations was used to determine the association of patient demographics, provider types, and regional physician specialty density with disease-related opioid initiation, accounting for within-region correlation. We found opioid initiation steadily declined from 2010 to 2017 (neuropathy: 26-19%, headache: 31-20%, LBP: 45-32%), as did disease-related opioid initiation (4-3%, 12-7%, 29-19%) and 5 to 10% of initial disease-related prescriptions resulted in chronic opioid use within 12 months of initiation. Certain specialist visits were associated with a lower likelihood of disease-related opioid initiation compared with primary care. Residence in high neurologist density regions had a lower likelihood of disease-related opioid initiation (headache odds ratio [OR] .76 [95% CI: .63-.92]) and LBP (OR .7 [95% CI: .61-.81]) and high podiatrist density regions for neuropathy (OR .56 [95% CI: .41-.78]). We found that specialist visits and greater access to specialists were associated with a lower likelihood of disease-related opioid initiation. These data could inform strategies to perpetuate reductions in opioid use for these common pain conditions. PERSPECTIVE: This article presents how opioid initiation for opioid-naïve patients with newly diagnosed neuropathy, headache, and LBP varies across providers. Greater access to certain specialists decreased the likelihood of opioid initiation. Future work may consider interventions to support alternative treatments and better access to specialists in low-density regions.

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.

Lecanemab: Looking Before We Leap.

Lecanemab, a novel amyloid-sequestering agent, recently received accelerated Food and Drug Administration approval for the treatment of mild dementia due to Alzheimer disease (AD) and mild cognitive impairment (MCI). Approval was based on a large phase 3 trial, Clarity, which demonstrated reductions in amyloid plaque burden and cognitive decline with lecanemab. Three major concerns should give us pause before adopting this medication: Its beneficial effects are small, its harms are substantial, and its potential costs are unprecedented. Although lecanemab has a clear and statistically significant effect on cognition, its effect size is small and may not be clinically significant. The magnitude of lecanemab's cognitive effect is smaller than independent estimates of the minimally important clinical difference, implying that the effect may be imperceptible to a majority of patients and caregivers. Lecanemab's cognitive effects were numerically smaller than the effect of cholinesterase inhibitors and may be much smaller. The main argument in lecanemab's favor is that it may lead to greater cognitive benefit over time. Although plausible, there is a lack of evidence to support this conclusion. Lecanemab's harms are substantial. In Clarity, it caused symptomatic brain edema in 11% and symptomatic intracranial bleeding in 0.5% of participants. These estimates likely significantly underestimate these risks in general practice for 3 reasons: (1) Lecanemab likely interacts with other medications that increase bleeding, an effect minimized in Clarity. (2) The Clarity population is much younger than the real-world population with mild AD dementia and MCI (age 71 years vs 85 years) and bleeding risk increases with age. (3) Bleeding rates in trials are typically much lower than in clinical practice. Lecanemab's costs are unprecedented. Its proposed price of $26,500 is based on cost-effectiveness analyses with tenuous assumptions. However, even if cost-effective, it is likely to result in higher expenditures than any other medication. If its entire target population were treated, the aggregate medication expenditures would be $120 billion US dollars per year-more than is currently spent on all medications in Medicare Part D. Before adopting lecanemab, we need to know that lecanemab is not less effective, vastly more harmful, and 100× more costly than donepezil.

Predictors of not maintaining regular medical follow-up after stroke.

BACKGROUND: Regular medical follow-up after stroke is important to reduce the risk of post-stroke complications and hospital readmission. Little is known about the factors associated with stroke survivors not maintaining regular medical follow-up. We sought to quantify the prevalence and predictors of stroke survivors not maintaining regular medical follow-up over time. METHODS: We conducted a retrospective cohort study of stroke survivors in the National Health and Aging Trends Study (2011-2018), a national longitudinal sample of United States Medicare beneficiaries. Our primary outcome was not maintaining regular medical follow-up. We performed a cox regression to estimate predictors of not maintaining regular medical follow-up. RESULTS: There were 1330 stroke survivors included, 150 of whom (11.3%) did not maintain regular medical follow-up. Stroke survivor characteristics associated with not maintaining regular medical follow-up included not having restrictions in social activities (HR 0.64, 95% CI 0.41, 1.01 for having restrictions in social activities compared to not having restrictions in social activities), greater limitations in self-care activities (HR 1.13, 95% CI 1.03, 1.23), and probable dementia (HR 2.23, 95% CI 1.42, 3.49 compared to no dementia). CONCLUSIONS: The majority of stroke survivors maintain regular medical follow-up over time. Strategies to retain stroke survivors in regular medical follow-up should be directed towards stroke survivors who do not have restrictions in social activity participation, those with greater limitations in self-care activities, and those with probable dementia.

Associations Between Vascular Risk Factor Levels and Cognitive Decline Among Stroke Survivors.

Importance: Incident stroke is associated with accelerated cognitive decline. Whether poststroke vascular risk factor levels are associated with faster cognitive decline is uncertain. Objective: To evaluate associations of poststroke systolic blood pressure (SBP), glucose, and low-density lipoprotein (LDL) cholesterol levels with cognitive decline. Design, Setting, and Participants: Individual participant data meta-analysis of 4 US cohort studies (conducted 1971-2019). Linear mixed-effects models estimated changes in cognition after incident stroke. Median (IQR) follow-up was 4.7 (2.6-7.9) years. Analysis began August 2021 and was completed March 2023. Exposures: Time-dependent cumulative mean poststroke SBP, glucose, and LDL cholesterol levels. Main Outcomes and Measures: The primary outcome was change in global cognition. Secondary outcomes were change in executive function and memory. Outcomes were standardized as t scores (mean [SD], 50 [10]); a 1-point difference represents a 0.1-SD difference in cognition. Results: A total of 1120 eligible dementia-free individuals with incident stroke were identified; 982 (87.7%) had available covariate data and 138 (12.3%) were excluded for missing covariate data. Of the 982, 480 (48.9%) were female individuals, and 289 (29.4%) were Black individuals. The median age at incident stroke was 74.6 (IQR, 69.1-79.8; range, 44.1-96.4) years. Cumulative mean poststroke SBP and LDL cholesterol levels were not associated with any cognitive outcome. However, after accounting for cumulative mean poststroke SBP and LDL cholesterol levels, higher cumulative mean poststroke glucose level was associated with faster decline in global cognition (-0.04 points/y faster per each 10-mg/dL increase [95% CI, -0.08 to -0.001 points/y]; P = .046) but not executive function or memory. After restricting to 798 participants with apolipoprotein E4 (APOE4) data and controlling for APOE4 and APOE4 × time, higher cumulative mean poststroke glucose level was associated with a faster decline in global cognition in models without and with adjustment for cumulative mean poststroke SBP and LDL cholesterol levels (-0.05 points/y faster per 10-mg/dL increase [95% CI, -0.09 to -0.01 points/y]; P = .01; -0.07 points/y faster per 10-mg/dL increase [95% CI, -0.11 to -0.03 points/y]; P = .002) but not executive function or memory declines. Conclusions and Relevance: In this cohort study, higher poststroke glucose levels were associated with faster global cognitive decline. We found no evidence that poststroke LDL cholesterol and SBP levels were associated with cognitive decline.

Antiseizure Medication Withdrawal Practice Patterns: A Survey Among Members of the American Academy of Neurology and EpiCARE.

Background and Objectives: To describe neurologist practice patterns, challenges, and decision support needs pertaining to withdrawal of antiseizure medications (ASMs) in patients with well-controlled epilepsy. Methods: We sent an electronic survey to (1) US and (2) European physician members of the American Academy of Neurology and (3) members of EpiCARE, a European Reference Network for rare and complex epilepsies. Analyses included frequencies and percentages, and we showed distributions through histograms and violin plots. Results: We sent the survey to 4,923 individuals; 463 consented, 411 passed eligibility questions, and 287 responded to at least 1 of these questions. Most respondents indicated that they might ever consider ASM withdrawal, with respondents treating mostly children being more likely ever to consider withdrawal (e.g., medical monotherapy: children 96% vs adults 81%; p < 0.05). The most important factors when making decisions included seizure probability (83%), consequences of seizures (73%), and driving (74%). The top challenges when making decisions included unclear seizure probability (81%), inadequate guidelines (50%), and difficulty communicating probabilities (45%). Respondents would consider withdrawal after a median of 2-year seizure freedom, but also responded that they would begin withdrawal on average only when the postwithdrawal seizure relapse risk in the coming 2 years was less than 15%-30%. Wide variation existed in the use of words or numbers in respondents' counsel methods, for example, percentages vs frequencies or probability of seizure freedom vs seizure. The most highly rated point-of-care methods to inform providers of calculated risk were Kaplan-Meier curves and showing percentages only, rather than pictographs or text recommendations alone. Discussion: Most surveyed neurologists would consider withdrawing ASMs in seizure-free individuals. Seizure probability was the largest factor driving decisions, yet estimating seizure probabilities was the greatest challenge. Respondents on average indicated that they may withdraw ASM after a minimum seizure-free duration of 2 years, yet also on average were willing to withdraw when seizure risk decreased below 15%-30%, which is lower than most patients' postwithdrawal risk at 2-year seizure freedom and lower than the equivalent even of a first seizure of life. These findings will inform future efforts at developing decision support tools aimed at optimizing ASM withdrawal decisions.