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.

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.

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.

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.

Systematic Review of Sex Differences in Ischemic Strokes Among Young Adults: Are Young Women Disproportionately at Risk?

BACKGROUND AND PURPOSE: Recent evidence suggests that young women (18-45 years) may be at higher risk of ischemic strokes than men of the same age. The goal of this systematic review is to reconcile and synthesize existing evidence of sex differences among young adults with ischemic strokes. METHODS: We searched PubMed from January 2008 to July 2021 for relevant articles and reviews and consulted their references. We included original studies that (1) were population based and (2) reported stroke incidence by sex or sex-specific incidence rate ratios of young adults ≤45 years. We excluded studies that (1) omitted measurements of error for incidence rates or incidence rate ratios, (2) omitted age adjustment, and (3) were not in English. Statistical synthesis was performed to estimate sex difference by age group (≤35, 35-45, and ≤45) and stroke type. RESULTS: We found 19 studies that reported on sex-specific stroke incidence among young adults, including 3 that reported on overlapping data. Nine studies did not find a statistically significant sex difference among young adults ≤45 years. Three studies found higher rates of ischemic stroke among men among young adults ≥30 to 35 years. Four studies found more women with ischemic strokes among young adults ≤35 years. Overall, in young adults ≤35 years, the estimated effect size favored more ischemic strokes in women (incidence rate ratio, 1.44 [1.18-1.76], I2=82%) and a nonsignificant sex difference in young adults 35 to 45 years (incidence rate ratio, 1.08 [0.85-1.38], I2=95%). CONCLUSIONS: Overall, there were 44% more women ≤35 years with ischemic strokes than men. This gap narrows in young adults, 35 to 45 years, and there is conflicting evidence whether more men or women have ischemic strokes in the 35 to 45 age group.

Antiseizure medication treatment pathways for US Medicare beneficiaries with newly treated epilepsy.

OBJECTIVE: This study was undertaken to characterize antiseizure medication (ASM) treatment pathways in Medicare beneficiaries with newly treated epilepsy. METHODS: This was a retrospective cohort study using Medicare claims. Medicare is the United States' federal health insurance program for people aged 65 years and older plus younger people with disabilities or end-stage renal disease. We included beneficiaries with newly treated epilepsy (International Classification of Diseases codes for epilepsy/convulsions 2014-2017, no ASM in the previous 2 years). We displayed the sequence of ASM fills using sunburst plots overall, then stratified by mood disorder, age, and neurologist prescriber. We tabulated drug costs for each pathway. RESULTS: We included 21 458 beneficiaries. Levetiracetam comprised the greatest number of pill days (56%), followed by gabapentin (11%) and valproate (8%). There were 22 288 unique treatment pathways. The most common pathways were levetiracetam monotherapy (43%), gabapentin monotherapy (10%), and valproate monotherapy (5%). Gabapentin was the most common second- and third-line ASM. Whereas only 2% of pathways involved first-line lacosamide, those pathways accounted for 19% of cost. Gabapentin and valproate use was increased and levetiracetam use was decreased in beneficiaries with mood disorders compared to beneficiaries without mood disorders. Levetiracetam use was increased and gabapentin, valproate, lamotrigine, and topiramate use was decreased in beneficiaries aged >65 years compared with those aged 65 years or less. Lamotrigine, levetiracetam, and lacosamide use was increased and gabapentin use was decreased in beneficiaries whose initial prescriber was a neurologist compared to those whose prescriber was not a neurologist. SIGNIFICANCE: Levetiracetam monotherapy was the most common pathway, although substantial heterogeneity existed. Lacosamide accounted for a small percentage of ASMs but a disproportionately large share of cost. Neurologists were more likely to prescribe lamotrigine compared with nonneurologists, and lamotrigine was prescribed far less frequently than may be endorsed by guidelines. Future work may explore patient- and physician-driven factors underlying ASM choices.

Reappraisal of the Medical Research Council Antiepileptic Drug Withdrawal Study: Contamination-adjusted and dose-response re-analysis.

OBJECTIVE: The 1991 Medical Research Council (MRC) Study compared seizure relapse for seizure-free patients randomized to withdraw vs continue of antiseizure medications (ASMs). We re-analyzed this trial to account for crossover between arms using contamination-adjusted intention to treat (CA ITT) methods, to explore dose-response curves, and to validate predictions against external data. ITT assesses the effect of being randomized to withdraw, as-treated analysis assesses the confounded effect of withdrawing, but CA ITT assesses the unconfounded effect of actually withdrawing. METHODS: CA ITT involves two stages. First, we used randomized arm to predict whether patients withdrew their ASM (logistic) or total daily ASM dose (linear). Second, we used those values to predict seizure occurrence (logistic). RESULTS: The trial randomized 503 patients to withdraw and 501 patients to continue ASMs. We found that 316 of 376 patients (88%) who were randomized to withdraw decreased their dose at every pre-seizure visit, compared with 35 of 424 (8%) who were randomized to continue (p < .01). Adjusted odds ratios of a 2-year seizure for those who withdrew vs those who did not was 1.3 (95% confidence interval [CI] 0.9-1.9) in the as-treated analysis, 2.5 (95% CI 1.9-3.4) comparing those randomized to withdraw vs continue for ITT, and 3.1 (95% CI 2.1-4.5) for CA ITT. Probabilities (withdrawal vs continue) were 28% vs 24% (as-treated), 40% vs 22% (ITT), and 43% vs 21% (CA ITT). Differences between ITT and CA ITT were greater when varying the predictor (reaching zero ASMs) or outcome (1-year seizures). As-treated dose-response curves demonstrated little to no effects, but larger effects in CA ITT analysis. MRC data overpredicted risk in Lossius data, with moderate discrimination (areas under the curve ~0.70). SIGNIFICANCE: CA ITT results (the effect of actually withdrawing ASMs on seizures) were slightly greater than ITT effects (the effect of recommend withdrawing ASMs on seizures). How these findings affect clinical practice must be individualized.

Community Intent to Activate Emergency Medical Services May Be Associated with Regional tPA Treatment.

INTRODUCTION: Acute stroke treatments are underutilized in the USA. Enhancing stroke preparedness, the recognition of stroke symptoms, and intent to call emergency medical services (EMS) could reduce delay in hospital arrival thereby increasing eligibility for time-sensitive stroke treatments. Whether higher stroke preparedness is associated with higher tissue plasminogen activator (tPA) treatment rates is however uncertain. We therefore set out to determine the contribution of stroke preparedness to regional variation in tPA treatment. METHODS: The region was defined by hospital service area (HSA). Stroke preparedness was determined by using Behavioral Risk Factor Surveillance System survey questions assessing stroke symptom recognition and intent to call 911 in response to a stroke. We used Medicare data to determine the percentage of tPA-treated hospitalized stroke patients in 2007, 2009, and 2011, adjusting for number of stroke hospitalizations in each HSA (primary outcome). We performed multivariate linear regression to estimate the association of regional stroke preparedness on log-transformed tPA treatment rates controlling for demographic, EMS, and hospital characteristics. RESULTS: The adjusted percentage of stroke patients receiving tPA ranged from 1.4% (MIN) to 11.3% (MAX) of stroke/TIA hospitalizations. Across HSAs, a median (IQR) of 86% (81-90%) of responses to a witnessed stroke indicated intent to call 911, and a median (IQR) of 4.4 (4.2-4.6) out of 6 stroke symptoms was recognized. Every 1% increase in an HSA's intent to call 911 was associated with a 0.44% increase in adjusted tPA treatment rate (p = 0.05). Lower accuracy of recognition of stroke symptoms was associated with higher adjusted tPA treatment rates (p = 0.05). CONCLUSIONS: There was little regional variation in intent to call EMS and stroke symptom recognition. Intent to call EMS and stroke symptom recognition are modest contributors to regional variation in tPA treatment.

Incidence of and predictors for antiseizure medication gaps in Medicare beneficiaries with epilepsy: a retrospective cohort study.

BACKGROUND: For the two-thirds of patients with epilepsy who achieve seizure remission on antiseizure medications (ASMs), patients and clinicians must weigh the pros and cons of long-term ASM treatment. However, little work has evaluated how often ASM discontinuation occurs in practice. We describe the incidence of and predictors for sustained ASM fill gaps to measure discontinuation in individuals potentially eligible for ASM withdrawal. METHODS: This was a retrospective cohort of Medicare beneficiaries. We included patients with epilepsy by requiring International Classification of Diseases codes for epilepsy/convulsions plus at least one ASM prescription each year 2014-2016, and no acute visit for epilepsy 2014-2015 (i.e., potentially eligible for ASM discontinuation). The main outcome was the first day of a gap in ASM supply (30, 90, 180, or 360 days with no pills) in 2016-2018. We displayed cumulative incidence functions and identified predictors using Cox regressions. RESULTS: Among 21,819 beneficiaries, 5191 (24%) had a 30-day gap, 1753 (8%) had a 90-day gap, 803 (4%) had a 180-day gap, and 381 (2%) had a 360-day gap. Predictors increasing the chance of a 180-day gap included number of unique medications in 2015 (hazard ratio [HR] 1.03 per medication, 95% confidence interval [CI] 1.01-1.05) and epileptologist prescribing physician (≥25% of that physician's visits for epilepsy; HR 2.37, 95% CI 1.39-4.03). Predictors decreasing the chance of a 180-day gap included Medicaid dual eligibility (HR 0.75, 95% CI 0.60-0.95), number of unique ASMs in 2015 (e.g., 2 versus 1: HR 0.37, 95% CI 0.30-0.45), and greater baseline adherence (> 80% versus ≤80% of days in 2015 with ASM pill supply: HR 0.38, 95% CI 0.32-0.44). CONCLUSIONS: Sustained ASM gaps were rarer than current guidelines may suggest. Future work should further explore barriers and enablers of ASM discontinuation to understand the optimal discontinuation rate.

Headache neuroimaging: A survey of current practice, barriers, and facilitators to optimal use.

OBJECTIVE: The objective of this study was to understand current practice, clinician understanding, attitudes, barriers, and facilitators to optimal headache neuroimaging practices. BACKGROUND: Headaches are common in adults, and neuroimaging for these patients is common, costly, and increasing. Although guidelines recommend against routine headache neuroimaging in low-risk scenarios, guideline-discordant neuroimaging is still frequently performed. METHODS: We administered a 60-item survey to headache clinicians at the Veterans Affairs health system to assess clinician understanding and attitudes on headache neuroimaging and to determine neuroimaging practice patterns for three scenarios describing hypothetical patients with headaches. Descriptive statistics were used to summarize responses, stratified by clinician type (physicians or advanced practice clinicians [APCs]) and specialty (neurology or primary care). RESULTS: The survey was successfully completed by 431 of 1426 clinicians (30.2% response rate). Overall, 317 of 429 (73.9%) believed neuroimaging was overused for patients with headaches. However, clinicians would utilize neuroimaging a mean (SD) 30.9% (31.7) of the time in a low-risk scenario without red flags, and a mean 67.1% (31.9) of the time in the presence of minor red flags. Clinicians had stronger beliefs in the potential benefits (268/429, 62.5%) of neuroimaging compared to harms (181/429, 42.2%) and more clinicians were bothered by harms stemming from the omission of neuroimaging (377/426, 88.5%) compared to commission (329/424, 77.6%). Additionally, APCs utilized neuroimaging more frequently than physicians and were more receptive to potential interventions to improve neuroimaging utilization. CONCLUSIONS: Although a majority of clinicians believed neuroimaging was overused for patients with headaches, many would utilize neuroimaging in low-risk scenarios with a small probability of changing management. Future studies are needed to define the role of currently used red flags given their importance in neuroimaging decisions. Importantly, APCs may be an ideal target for future optimization efforts.

Real-World Midazolam Use and Outcomes With Out-of-Hospital Treatment of Status Epilepticus in the United States.

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.

Polypharmacy composition and patient- and provider-related variation in patients with epilepsy.

OBJECTIVE: To describe polypharmacy composition, and the degree to which patients versus providers contribute to variation in medication fills, in people with epilepsy. METHODS: We performed a retrospective study of Medicare beneficiaries with epilepsy (antiseizure medication plus diagnostic codes) in 2014 (N = 78,048). We described total number of medications and prescribers, and specific medications. Multilevel models evaluated the percentage of variation in two outcomes (1. number of medications per patient-provider dyad, and 2. whether a medication was filled within thirty days of a visit) due to patient-to-patient differences versus provider-to-provider differences. RESULTS: Patients filled a median of 12 (interquartile range [IQR] 8-17) medications, from median of 5 (IQR 3-7) prescribers. Twenty-two percent filled an opioid, and 61% filled at least three central nervous system medications. Levetiracetam was the most common medication (40%), followed by hydrocodone/acetaminophen (27%). The strongest predictor of medications per patient was Charlson comorbidity index (7.5 [95% confidence interval (CI) 7.2-7.8] additional medications for index 8+ versus 0). Provider-to-provider variation explained 36% of variation in number of medications per patient, whereas patient-to-patient variation explained only 2% of variation. Provider-to-provider variation explained 57% of variation in whether a patient filled a medication within 30 days of a visit, whereas patient-to-patient variation explained only 30% of variation. CONCLUSION: Patients with epilepsy fill a large number of medications from a large number of providers, including high-risk medications. Variation in medication fills was substantially more related to provider-to-provider rather than patient-to-patient variation. The better understanding of drivers of high-prescribing practices may reduce avoidable medication-related harms.

Blood Pressure in the First 6 Hours Following Endovascular Treatment for Ischemic Stroke Is Associated With Outcome.

Background and Purpose: Optimal blood pressure (BP) management in the acute phase of ischemic stroke remains an unresolved issue. It is uncertain whether guidelines for BP management during and after intravenous alteplase can be extrapolated to endovascular treatment (EVT) for stroke due to large artery occlusion in the anterior circulation. We evaluated the associations between systolic BP (SBP) in the first 6 hours following EVT and functional outcome as well as symptomatic intracranial hemorrhage. Methods: Patients of 8 MR CLEAN (Multicenter Randomized Controlled Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) Registry centers, with available data on SBP in the 6 hours following EVT, were analyzed. We evaluated maximum, minimum, and mean SBP. Study outcomes were functional outcome (modified Rankin Scale) at 90 days and symptomatic intracranial hemorrhage. We used multivariable ordinal and binary regression analysis to adjust for important prognostic factors and studied possible effect modification by successful reperfusion. Results: Post-EVT SBP data were available for 1161/1796 patients. Higher maximum SBP (per 10 mm Hg increments) was associated with worse functional outcome (adjusted common odds ratio, 0.93 [95% CI, 0.88­0.98]) and a higher rate of symptomatic intracranial hemorrhage (adjusted odds ratio, 1.17 [95% CI, 1.02­1.36]). The association between minimum SBP and functional outcome was nonlinear with an inflection point at 124 mm Hg. Minimum SBP lower and higher than the inflection point were associated with worse functional outcomes (adjusted common odds ratio, 0.85 per 10 mm Hg decrements [95% CI, 0.76­0.95] and adjusted common odds ratio, 0.81 per 10 mm Hg increments [95% CI, 0.71­0.92]). No association between mean SBP and functional outcome was observed. Successful reperfusion did not modify the relation of SBP with any of the outcomes. Conclusions: Maximum SBP in the first 6 hours following EVT is positively associated with worse functional outcome and an increased risk of symptomatic intracranial hemorrhage. Both lower and higher minimum SBP are associated with worse outcomes. A randomized trial to evaluate whether modifying post-intervention SBP results in better outcomes after EVT for ischemic stroke seems justified.

Antiseizure medication adherence trajectories in Medicare beneficiaries with newly treated epilepsy.

OBJECTIVE: This study was undertaken to characterize trajectories of antiseizure medication (ASM) adherence in adults with newly treated epilepsy and to determine predictors of trajectories. METHODS: This was a retrospective cohort study using Medicare. We included beneficiaries with newly treated epilepsy (one or more ASM and none in the preceding 2 years, plus International Classification of Diseases codes) in 2010-2013. We calculated the proportion of days covered (proportion of total days with any ASM pill supply) for 8 quarters or until death. Group-based trajectory models characterized and determined predictors of trajectories. RESULTS: We included 24 923 beneficiaries. Models identified four groups: early adherent (60%), early nonadherent (18%), late adherent (11%), and late nonadherent (11%). Numerous predictors were associated with being in the early nonadherent versus early adherent group: non-White race (e.g., Black, odds ratio [OR] = 1.7, 95% confidence interval [CI] = 1.5-1.8), region (e.g., South vs. Northeast: OR = 1.2, 95% CI = 1.1-1.4), and once daily initial medication (OR = 1.1, 95% CI = 1.0-1.3). Predictors associated with decreased odds of being in the early nonadherent group included older age (OR = .9 per decade, 95% CI = .9-.9), female sex (OR = .9, 95% CI = .8-1.0), full Medicaid eligibility (OR = .6, 95% CI = .4-.8), neurologist visit (OR = .6, 95% CI = .6-.7), and initial older generation ASM (OR = .6, 95% CI = .6-.7). SIGNIFICANCE: We identified four ASM adherence trajectories in individuals with newly treated epilepsy. Whereas risk factors for early nonadherence such as race or geographic region are nonmodifiable, our work highlighted a modifiable risk factor for early nonadherence: lacking a neurologist. These data may guide future interventions aimed at improving ASM adherence, in terms of both timing and target populations.

Increasing false positive diagnoses may lead to overestimation of stroke incidence, particularly in the young: a cross-sectional study.

BACKGROUND: Stroke incidence is reportedly increasing in younger populations, although the reasons for this are not clear. We explored possible reasons by quantifying trends in neurologically focused emergency department (ED) visits, classification of stroke vs. TIA, and imaging use. METHODS: We performed a retrospective, serial, cross-sectional study using the National Hospital Ambulatory Medical Care Survey to examine time trends in age-stratified primary reasons for visit, stroke/TIA diagnoses, and MRI utilization from 1995 to 2000 and 2005-2015. RESULTS: Five million eight hundred thousand ED visits with a primary diagnosis of stroke (CI 5.3 M-6.4 M) were represented in the data. The incidence of neurologically focused reason for visits (Neuro RFVs) increased over time in both the young and in older adults (young: + 111 Neuro RFVs/100,000 population/year, CI + 94 - + 130; older adults: + 70 Neuro RFVs/100,000 population/year, CI + 34 - + 108). The proportion of combined stroke and TIA diagnoses decreased over time amongst older adults with a Neuro RFV (OR 0.95 per year, p < 0.01, CI 0.94-0.96) but did not change in the young (OR 1.00 per year, p = 0.88, CI 0.95-1.04). Within the stroke/TIA population, no changes in the proportion of stroke or TIA were identified. MRI utilization rates amongst patients with a Neuro RFV increased for both age groups. CONCLUSIONS: We found, but did not anticipate, increased incidence of neurologically focused ED visits in both age groups. Given the lower pre-test probability of a stroke in younger adults, this suggests that false positive stroke diagnoses may be increasing and may be increasing more rapidly in the young than in older adults.

Cardiovascular disease risk, awareness, and treatment in people with epilepsy.

OBJECTIVE: To evaluate whether cardiovascular risk, risk awareness, and guideline concordant treatment differ in individuals with versus without epilepsy. METHODS: This was a retrospective cross-sectional study using the National Health and Nutrition Examination Survey. We included participants ≥18 years for 2013-2018. We classified participants as having epilepsy if reporting ≥1 medication treating seizures. We calculated 10-year atherosclerotic cardiovascular disease (ASCVD) risk using the revised pooled cohort equation. We compared unadjusted and adjusted risk for participants with versus without epilepsy. We then assessed hypertension and diabetes disease awareness and control, plus statin guideline-concordance. We assessed mediators for both ASCVD risk and cardiovascular disease awareness. RESULTS: Of 17,961 participants, 154 (0.9%) had epilepsy. Participants with epilepsy reported poorer diet (p = 0.03), fewer minutes of moderate-vigorous activity per day (p < 0.01), and increased frequency of cardiovascular conditions (e.g. coronary heart disease, myocardial infarction, stroke). There was no difference in control of individual examination and laboratory risk factors between groups (A1c, systolic blood pressure, diastolic blood pressure, high-density lipoprotein, low-density lipoprotein, total cholesterol). However, epilepsy was associated with 52% (95% confidence interval [CI]: 0-130%) increase in ASCVD risk, which became nonsignificant after adjusting for health behaviors. No single studied variable (income, Patient Health Questionnaire-9 (PHQ-9), diet, smoking) had a significant indirect effect. Participants with epilepsy reported increased hypertension awareness which was trivially but significantly mediated by having a routine place of healthcare (indirect effect: 1% absolute increase (95% CI: 0-1%), and they reported increased rates of hypertension treatment and guideline-concordant statin therapy. Participants with versus without epilepsy reported similar rates of blood pressure control and diabetes awareness, treatment, and control. CONCLUSIONS: Participants with epilepsy had increased ASCVD risk, despite similar or better awareness, treatment, and control of individual risk factors such as diabetes and hypertension. Our results suggest that epilepsy is associated with numerous health behaviors leading to cardiovascular disease, though the causal pathway is complex as these variables (income, depression, diet, exercise, smoking) generally served as confounders rather than mediators.

Trends in acute ischemic stroke treatments and mortality in the United States from 2012 to 2018.

OBJECTIVE: The establishment of mechanical thrombectomy (MT) as a first-line treatment for select patients with acute ischemic stroke (AIS) and the expansion of stroke systems of care have been major advancements in the care of patients with AIS. In this study, the authors aimed to identify temporal trends in the usage of tissue-type plasminogen activator (tPA) and MT within the AIS population from 2012 to 2018, and the relationship to mortality. METHODS: Using a nationwide private health insurance database, 117,834 patients who presented with a primary AIS between 2012 and 2018 in the United States were identified. The authors evaluated temporal trends in tPA and MT usage and clinical outcomes stratified by treatment and age using descriptive statistics. RESULTS: Among patients presenting with AIS in this population, the mean age was 69.1 years (SD ± 12.3 years), and 51.7% were female. Between 2012 and 2018, the use of tPA and MT increased significantly (tPA, 6.3% to 11.8%, p < 0.0001; MT, 1.6% to 5.7%, p < 0.0001). Mortality at 90 days decreased significantly in the overall AIS population (8.7% to 6.7%, p < 0.0001). The largest reduction in 90-day mortality was seen in patients treated with MT (21.4% to 14.1%, p = 0.0414) versus tPA (11.8% to 7.0%, p < 0.0001) versus no treatment (8.3% to 6.3%, p < 0.0001). Age-standardized mortality at 90 days decreased significantly only in patients aged 71-80 years (11.4% to 7.8%, p < 0.0001) and > 81 years (17.8% to 11.6%, p < 0.0001). Mortality at 90 days stagnated in patients aged 18 to 50 years (3.0% to 2.2%, p = 0.4919), 51 to 60 years (3.8% to 3.9%, p = 0.7632), and 61 to 70 years (5.5% to 5.2%, p = 0.2448). CONCLUSIONS: From 2012 to 2018, use of tPA and MT increased significantly, irrespective of age, while mortality decreased in the entire AIS population. The most dramatic decrease in mortality was seen in the MT-treated population. Age-standardized mortality improved only in patients older than 70 years, with no change in younger patients.

Mechanical Thrombectomy Improves Outcome for Large Vessel Occlusion Stroke after Cardiac Surgery.

BACKGROUND: Stroke is a feared complication of cardiac surgery. Modern clot-retrieval techniques provide effective treatment for large vessel occlusion (LVO) strokes. The purpose of this study was to 1) report the incidence of LVO stroke after cardiac surgery at a large academic center, and 2) describe outcomes of postoperative LVO strokes. METHODS: All patients experiencing stroke within 30 days after undergoing cardiac surgery at a single center in 2014-2018 were reviewed. LVOs were identified through review of imaging and medical records, and their characteristics and clinical courses were examined. RESULTS: Over the study period, 7,112 cardiac surgeries, including endovascular procedures, were performed. Acute ischemic stroke within 30 days after surgery was noted in 163 patients (2.3%). Among those with a stroke, 51/163 (31.3%) had a CTA or MRA, and 15/163 (9.2%) presented with LVO stroke. For all stroke patients, the median time from surgery to stroke was 2 days (interquartile range, IQR, 0-6 days), and for patients with LVO, the median time from surgery to stroke was 4 days (IQR 0-6 days). The overall rate of postoperative LVO was 0.2% (95% CI 0.1-0.4%), though only 6/15 received thrombectomy. LVO patients receiving thrombectomy were significantly more likely to return to independent living compared to those managed medically (n = 4/6, 66.6% for mechanical thrombectomy vs. n = 0/9, 0% for medical management, P = .01). Of the 9 patients who did not get thrombectomy, 6 may currently be candidates for thrombectomy given new expanded treatment windows. CONCLUSIONS: The rate of LVO after cardiac surgery is low, though substantially elevated above the general population, and the majority do not receive thrombectomy currently. Patients receiving thrombectomy had improved neurologic outcomes compared to patients managed medically. Optimized postoperative care may increase the rate of LVO recognition, and cardiac surgery patients and their caregivers should be aware of this effective therapy.

Exploring Factors Contributing to Race Differences in Poststroke Disability.

Background and Purpose- Cross sectional analyses have found large race differences in poststroke disability, yet these analyses do not account for prestroke disability, hospitalization factors, postacute care, transitions, or mortality. In this context, we explore mortality, nursing home placement, and disability in a longitudinal analysis of older stroke survivors who survived at least 90 days poststroke. Methods- A prospective cohort of black or white stroke survivors from the National Health and Aging Trends Study (2009-2016) linked to Medicare were used. Disability was assessed during in-person interviews with validated scales (0-7). We used cox proportional hazards models to separately assess mortality and nursing home admission adjusting for age, sex, sociodemographics (marital status, education, income, insurance status, social network size), comorbidities, hospitalization factors, postacute care, and 90-day readmissions. To estimate racial differences in disability, we used a multilevel linear regression model initially adjusting for age and sex and then compared with a model adjusted for sociodemographics, comorbidities, hospitalization factors, postacute care, and 90-day readmissions. Results- There were 282 stroke survivors, of which 76 (12.6%) were black. There were no race differences in long-term mortality (hazard ratio for black, 1.2 [95% CI, 0.7-2.2]; P=0.5) or nursing home placement (hazard ratio for black, 0.7 [95% CI, 0.2-2.4]; P=0.5). The largest race differences in disability were observed immediately prestroke, estimated age- and sex-adjusted activity limitations were (2.6 [2.0-3.2] in blacks versus 1.4 [1.0-1.8] in whites, mean difference, 1.2 [0.5-1.9], P<0.001) and immediately poststroke (2.6 [2.0-3.3] in blacks versus 1.7 [1.2-2.1] in whites, mean difference, 1.0 [0.2-1.7], P<0.01). Full adjustment did not substantially change the associations between race and disability. Conclusions- Race differences in nursing home placement, long-term mortality, sociodemographics, comorbidities, hospitalization factors, postacute care, and readmissions are unlikely to be large contributors to race differences in poststroke disability. Further research is needed to understand the drivers of race differences in poststroke disability.