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Background and ObjectiveTo characterize trends in antiseizure medication (ASM) fills and total prescription costs in people with epilepsy.MethodsThis was a retrospective cohort study of beneficiaries with epilepsy (ASM, plus ICD codes) in a 20% random Medicare sample, with continuous Fee-For-Service coverage (Parts A, B, and D) in 2008–2018. We summed the number of pill days and costs (adjusted to 2018 dollars) per person-year for each ASM. ASMs were categorized into brand vs generic, first vs newer generation, and enzyme inducers vs noninducers.ResultsThere were 77,000–133,000 beneficiaries with epilepsy per year. The most common ASM was phenytoin in 2008, which shifted to levetiracetam in 2018 (2008: phenytoin 25%, levetiracetam 14%; 2018: phenytoin 9%, levetiracetam 27%). Brand name (2008: 56%; 2018: 14%), first-generation (2008: 55%; 2018: 32%), and enzyme-inducing ASMs (2008: 44%; 2018: 24%) each decreased over time as a proportion of pill days. The number of brand pill days per person-year initially decreased (e.g., 2008: 250; 2009: 121; 2010: 96) but then plateaued (2013–2018: between 66 and 69) given a notable increase in lacosamide pill days per person (2008: 0; 2018: 20). Total brand name costs per year initially decreased 2008–2010 (2008: $150 million; 2010: $72 million) but then increased after 2010 (2018: $256 million). In 2018, brand name ASMs represented 79% of costs despite representing only 14% of pill days, a 1-year pill supply became 277% more expensive for brand name medications but 42% less expensive for generic medications over time (2008: brand ∼$2,800 vs generic ∼$800; 2018: brand ∼$10,700 vs generic ∼$460), and many common brand name ASMs cost approximately 10-fold more per pill day than their generic equivalents.DiscussionFirst-generation and enzyme-inducing ASMs waned from 2008 to 2018. Although brand name ASMs initially waned translating into lower costs and potentially higher value care, after 2010, brand name costs markedly increased because of increasing use of lacosamide plus a 277% increase in per-pill cost of brand name ASMs. Brand name ASMs represented a minority of prescriptions, but the majority of costs.

This study was undertaken to characterize antiseizure medication (ASM) treatment pathways in Medicare beneficiaries with newly treated epilepsy.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.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 aged65 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.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.

Infectious endocarditis is associated with substantial in-hospital mortality of 15%-20%. Effective management requires coordination between multiple medical and surgical subspecialties, which can often lead to disjointed care. Previous European studies have identified multidisciplinary endocarditis teams as a tool for reducing endocarditis mortality.The multidisciplinary endocarditis team was formed in May 2018. The group developed an evidence-based algorithm for management of endocarditis that was used to provide recommendations for hospitalized patients over a 1-year period. Mortality outcomes were then retroactively assessed and compared to a historical control utilizing propensity matching.Between June 2018 and June 2019 the team provided guideline-based recommendations on 56 patients with Duke Criteria-definite endocarditis and at least 1 American Heart Association indication for surgery. The historical control included 68 patients with definite endocarditis and surgical indications admitted between July 1, 2014, and June 30, 2015. In-hospital mortality decreased significantly from 29.4% in 2014-2015 to 7.1% in 2018-2019 (P.0001). There was a non-significant increase in the rate of surgical intervention after implementation of the team (41.2% vs 55.4%; P = 0.12). Propensity score matching demonstrated similar results.Implementation of a multidisciplinary endocarditis team was associated with a significant 1-year decrease in all-cause in-hospital mortality for patients with definite endocarditis and surgical indications, in the presence of notable differences between the 2 studied cohorts. In conjunction with previous studies demonstrating their effectiveness, these data support the idea that widespread adoption of endocarditis teams in North America could improve outcomes for this patient population.

Background: Due to its lower incidence, strokes in young adults, studies have difficulty answering why there are more women than men less than 35 with incident strokes. The goal of this study is to link claims and registry data to create a new longitudinal and clinical cohort of strokes in young adults. Methods: Colorado mandates reporting of commercial and public insurance (Medicaid and Medicare) claims to the All Payer Claims Database (APCD). We identified all first-time stroke admissions using ICD-9 /10 codes between 2012 to 2018 in young adults (18-55). Get with the Guidelines (GWTG) Stroke registry has stroke cases from 41 hospitals in Colorado since 2010. Matching was based on exact birthdate, sex and +/- 1day in admission/discharge dates. Confirmation of match was based on comparing the admitting hospital between the two databases. Cardiovascular(CV) and non-CV risk factors occurring from enrollment until 1 day prior to stroke date in the APCD were included. Student’s T-test, and Z-tests were used to test differences between men and women. Results: We identified 3032 stroke cases in the APCD. Of these, 1455 (48.0%) matched to an admission in the GWTG-Stroke registry. Of these, 1303 (89.6%) also matched based on the admitting hospital (Table). The final cohort contained 51% women, 11.3% Conclusions: Clinical registries such as GWTG-Stroke can be used to supplement longitudinal administrative cohorts of young adults with stroke to get richer data on stroke etiology and severity.

Introduction: Providers are often concerned about missing stroke in Emergency Department (ED) dizziness visits. Prior studies found that the cumulative incidence of stroke after ED discharge for dizziness is low. However, little is known about the magnitude of disability and/or severity of subsequent strokes which is important for informing the scope of the problem. We aimed to estimate the cumulative incidence of stroke-disability/mortality following ED dizziness visits that were discharged home. Methods: We conducted a retrospective cohort study from January 2016 to December 2020 across 13 EDs within Kaiser Permanente Southern California (KPSC). We included all index visits for adults who were discharged home from the ED after a primary dizziness visit, excluding those with DNR/hospice status, trauma, or index stroke diagnosis. Post-stroke disability/mortality - defined as stroke hospitalization not discharged home - was captured over a 30-day follow-up period. Cumulative incidence of stroke-disability/mortality was calculated using Kaplan-Meier estimates censored for non-stroke death. Acute stroke management was also summarized. Results: We identified 77,315 index dizziness visits discharged home from the ED. Median age was 59 years (IQR,44-71) and 62% were female. The 30-day cumulative incidence of stroke-hospitalization was 0.12% (95% CI 0.10-0.15%; 1 in 823) and the cumulative incidence of post stroke-disability/mortality was 0.04% (95%CI 0.03-0.06; 1 in 2,342). At the subsequent stroke-hospitalizations, the frequency of acute interventions was as follows: 3% (3/94) intra-arterial thrombolytics, 5% (5/94) thrombectomy, 2% (2/94) suboccipital craniotomy, 3% (3/94) tracheostomy, 3% (3/94) gastrostomy, 10% (9/94) mechanical intubation. Conclusions: The cumulative incidence of post stroke-disability/mortality among patients discharged from the ED for dizziness is low and acute interventions used to manage severe strokes were infrequent. These data are important for planning studies to optimize outcomes of patients presenting to the ED for dizziness.

Background: Emergency Department (ED) transfers to tertiary centers are a critical component of stroke systems of care, yet little is known about the status of the transfer networks used to execute this process. Our objective is to characterize these transfer networks and assess rates of acute treatments among transfers to identify potential targets for improving organization of stroke systems of care. Methods: Using the 2017 US Centers of Medicare and Medicaid Inpatient and Outpatient Fee-for-Service files, we captured patients with inpatient ischemic stroke claims based on ICD 10 codes. We defined ED-hospital transfers as: 1) any outpatient ED claim ≤48 hrs prior to the inpatient stroke claim, 2) ED discharge status indicating an acute care hospital, and 3) originating and receiving facilities with different NPI numbers. We characterized the structure of transfer networks and acute treatment rates (based on ICD 10 codes and DRGs for thrombolysis and thrombectomy) using descriptive statistics. Results: We identified 225,177 patients with inpatient stroke claims. Of these, 7,907 (3.5%) had an ED-hospital transfer, involving 2083 different acute care hospitals. Amongst EDs that transferred a patient, the median number of receiving hospitals was 1 (IQR 1; range [1,7]) and the median volume of transferred patients was 3 (IQR 5; range [1,53]). Amongst hospitals that had stroke patients transfer in, the median number of originating EDs was 2 (IQR 5; range [1,28]) and the median volume of transferred patients was 5 [IQR 14; 1-158]. Amongst all ED-hospital transfer pairs, the median volume of transferred patients was 2 (IQR 2; range[1,53]). Amongst transferred patients, 60% received thrombolysis and 16% received mechanical thrombectomy. Conclusions: We found wide variation in the volumes of ED-hospital transfers for acute stroke, with a large number of these transfers occurring between hospitals with low transfer volumes. Given that high volume centers generally have better outcomes and the majority of identified transfers received acute therapies, a better understanding of the clinical circumstances driving these low-volume transfer connections is needed.

Introduction: Mexican Americans (MAs) use less preventative healthcare than NHWs and this may result in in more emergency department (ED) visits or readmissions. We sought to explore ethnic differences in ED and hospital utilization immediately before and after stroke. Methods: BASIC is a stroke epidemiologic study in Corpus Christi TX. We performed probabilistic matching to identify hospital claims for all BASIC-identified index strokes (ischemic or ICH) from 2010-2020 continuously enrolled in Medicare fee-for-service (FFS). Matching was performed using demographics (including date of birth), stroke admission/discharge dates, vascular risk factors, comorbidities, and in-hospital procedures. All emergency department (ED) visits and hospital readmissions within 90 days before and after the index stroke were identified using Medicare claims. Logistic regression models were used to determine the association of MA ethnicity (compared to NHWs) with prior ED/inpatient visits and cox regression models were used to estimate the associations with subsequent ED visits/readmissions (censoring at death), adjusting for patient age, sex, stroke severity, and stroke type. Results: We identified 1,180 incident BASIC strokes that could be matched with Medicare FFS inpatient claims: 84% with ischemic stroke, 46.2% NHWs vs 45.7% MAs, mean age 76.4, median (IQR) NIHSS 5 (2-13). Both ED visits and hospitalizations were relatively common before and after stroke (Table). Compared to NHWs, MAs were more likely to have ED visits before stroke than NHWs (OR 1.5, 95%CI [1.1-2.1]) and hospitalizations after stroke (HR 1.3, [1.1-1.7], but no ethinc differences were observed in pre-stroke hospitalizations or post-stroke ED visits. ( Table ) Conclusion: The increased rate of pre-stroke ED visits in MAs suggests the potential for missed opportunities to prevent stroke may exist and merits further scrutiny.

Introduction: Despite their high risk of mortality, recurrent stroke, and dementia, stroke survivors underutilize ACP. In a non-prespecified subgroup analysis of a randomized trial to increase ACP, we compared the efficacy of the PREPARE for Your Care (PREPARE) plus an easy-to-read advance directive (AD) to an AD alone among stroke survivors. Methods: PREPARE is an interactive digital program with easy-to-read, state-specific ADs, and video stories. Stroke survivors in the PREPARE trial were identified using the International Classification of Diseases codes. The primary outcome was new ACP documentation in the electronic medical record after 12 months; secondary outcome was self-reported ACP completion of: (1) signing official papers naming a surrogate decision maker; (2) discussion of patients’ wishes with surrogates; (3) discussion of patients’ wishes with medical providers; and (4) an AD, scored 0-4. We calculated the change from baseline to 12-month follow-up. Mixed-effects regression models were used, adjusted for health literacy (adequate or limited), baseline ACP documentation, and clustering by physician. Results: Of 986 PREPARE trial participants, 91 (9.2%) were stroke survivors and 72 had complete data. The mean age was 64 years (SD, 6.8 years), 47% were women, 74% identified as a minority race/ethnicity, 40% were Spanish-speaking, 49% had limited health literacy, and 41% had ACP before enrollment. There was a trend toward greater ACP documentation in the PREPARE-arm (table). The PREPARE-arm had significantly greater increase in completed ACP elements than the AD-only arm. Discussion: The PREPARE program shows promise to engage ethnically diverse stroke survivors in ACP and should be studied further. Addition of stroke-specific content and engagement of acute stroke survivors in adaptations may increase the impact of the program.

Background Epilepsy is a common, serious condition characterized by an increased risk for seizures. Fortunately, seizure risk decreases with increasing seizure-free time on antiseizure medications (ASMs). Eventually, patients may consider whether to stop ASMs, which requires weighing treatment benefit versus burden. We developed a novel questionnaire to quantify patient preferences relevant to ASM decision-making. Methods Respondents rated items relevant to ASM decision-making (e.g., different seizure risks, various side effects, cost) on a Visual Analogue Scale (VAS, rated 0-100) how concerning they would find each item and then repeatedly chose the most and least concerning item from subsets (best-worst scaling, BWS). We pretested with five neurologists, then recruited adults with epilepsy who were seizure-free at least one year. Our primary outcomes were recruitment rate, and qualitative and Likert-based feedback. Secondary outcomes included VAS ratings and best-minus-worst scores (number of times an item was chosen as the most minus number of times an item was chosen as the least concerning). Results Thirty-one of 60 (52%) contacted patients completed the study. Most patients felt VAS questions were clear (28; 90%), easy to use (27; 87%), and assessed preferences well (25; 83%). Corresponding results for BWS questions were 27 (87%), 29 (97%), and 23 (77%). Physicians suggested adding a ‘warmup’ question showing a completed example and simplifying terminology. Patients suggested ways to clarify instructions. Cost, inconvenience of taking medication, and laboratory monitoring were the least concerning items. Cognitive side effects and a 50% seizure risk in the next year were the most concerning items. Twelve (39%) of patients made at least one ‘inconsistent choice’ for example ranking a higher seizure risk as lower concern compared with a lower seizure risk, though ‘inconsistent choices’ represented only 3% of all question blocks. Conclusions Our recruitment rate was favorable, most patients agreed the survey was clear, and we describe areas for survey improvement. ‘Inconsistent’ responses during this development phase may lead us to collapse seizure probability items into a single ‘seizure’ category. Evidence regarding how patients weigh benefits and harms is crucial inform clinical care and guideline development.

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 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.

ImportanceIncident stroke is associated with accelerated cognitive decline. Whether poststroke vascular risk factor levels are associated with faster cognitive decline is uncertain.ObjectiveTo evaluate associations of poststroke systolic blood pressure (SBP), glucose, and low-density lipoprotein (LDL) cholesterol levels with cognitive decline.Design, Setting, and ParticipantsIndividual 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.ExposuresTime-dependent cumulative mean poststroke SBP, glucose, and LDL cholesterol levels.Main Outcomes and MeasuresThe 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.ResultsA 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 RelevanceIn 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.

Obstructive sleep apnea (OSA) is prevalent among older adults. Although treatment with positive airway pressure (PAP) lowers subsequent morbidity, PAP adherence is inconsistent. Socioeconomic disparities have been observed in OSA treatment, but regional differences in OSA care are unknown. This study examined geographic variations in PAP treatment and adherence among older Americans.This study utilized a representative 5% sample of all Medicare fee-for-service beneficiaries aged 65+ years. An OSA diagnosis, treatment, and PAP adherence were confirmed with International Classification of Diseases, Ninth Revision, HCPCS (Health Care Common Procedure Coding System) codes, and ≥2 HCPCS claims for PAP supplies respectively. Descriptive statistics were used to examine proportions of Medicare beneficiaries who obtained and adhered to PAP. Maps described the proportion of treated and adherent beneficiaries by state and hospital referral region.For state-level data, PAP treatment and adherence proportions among beneficiaries with an OSA diagnosis ranged between 54-87% and 59-81%, respectively. Proportions of treated patients were higher in Midwest states (80%), in comparison to Northwest, Northeast, and Southern states (73%). Southern states and California had lowest proportions of PAP adherence (70%). Within-state variability in treatment patterns were apparent along the East and West coasts. Correlations of PAP treatment and adherence proportions were low in Washington, DC, New York, and New Jersey. Discordant treatment and adherence proportions were observed in Alabama and Mississippi.Significant state-level and regional disparities of PAP treatment and adherence among Medicare beneficiaries with OSA suggest gaps in delivery of OSA care for older Americans.

A physical performance evaluation can inform fall risk in older people, however, the predictiveness of a one-time assessment is limited. The trajectory of physical performance over time has not been well characterized and might improve fall prediction. We aimed to characterize trajectories in physical performance and determine if fall prediction improves using trajectories of performance.This was a cohort design using data from the National Health and Aging Trends Study. Physical performance was measured by the short physical performance battery (SPPB) with scores ranging from 0 (worst) to 12 (best). The trajectory of SPPB was categorized using latent class modeling and slope-based multilevel linear regression. We used Cox proportional hazards models with an outcome of time to ≥2 falls from annual self-report to assess predictiveness after adding SPPB trajectories to models of baseline SPPB and established non-physical-performance-based variables.The sample was 5969 community-dwelling Medicare beneficiaries aged ≥65 years. The median number of annual SPPB evaluations was 4 (IQR, 3-7). Mean baseline SPPB was 9.2 (SD, 3.0). The latent class model defined SPPB trajectories over a range of two to nineteen categories. The mean slope from the slope-based model was -0.01 SPPB points/year (SD, 0.14). Discrimination of the baseline SPPB model to predict time to ≥2 falls was fair (Harrell's C, 0.65) and increased after adding the non-performance-based predictors (Harrell's C, 0.70). Discrimination slightly improved with the SPPB trajectory category variable that had the best fit (Harrell's C, 0.71) but did not improve with the SPPB linear slope. Calibration with and without the trajectory categories was similar.We found that the trajectory of physical performance did not meaningfully improve upon fall prediction from a baseline physical performance assessment and established non-performance-based information. These results do not support longitudinal SPPB assessments for fall prediction.

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.

ObjectiveTo measure the out-of-pocket (OOP) costs of evaluation and management (E/M) services and common diagnostic testing for neurology patients.MethodsUsing a large, privately insured health care claims database, we identified patients with a neurologic visit or diagnostic test from 2001 to 2016 and assessed inflation-adjusted OOP costs for E/M visits, neuroimaging, and neurophysiologic testing. For each diagnostic service each year, we estimated the proportion of patients with OOP costs, the mean OOP cost, and the proportion of the total service cost paid OOP. We modeled OOP cost as a function of patient and insurance factors.ResultsWe identified 3,724,342 patients. The most frequent neurologic services were E/M visits (78.5%), EMG/nerve conduction studies (NCS) (7.7%), MRIs (5.3%), and EEGs (4.5%). Annually, 86.5%–95.2% of patients paid OOP costs for E/M visits and 23.1%–69.5% for diagnostic tests. For patients paying any OOP cost, the mean OOP cost increased over time, most substantially for EEG, MRI, and E/M. OOP costs varied considerably; for an MRI in 2016, the 50th percentile paid $103.10 and the 95th percentile paid $875.40. The proportion of total service cost paid OOP increased. High deductible health plan (HDHP) enrollment was associated with higher OOP costs for MRI, EMG/NCS, and EEG.ConclusionAn increasing number of patients pay OOP for neurologic diagnostic services. These costs are rising and vary greatly across patients and tests. The cost sharing burden is particularly high for the growing population with HDHPs. In this setting, neurologic evaluation might result in financial hardship for patients.

Background and Purpose: Ischemic stroke patients with large vessel occlusion (LVO) could benefit from direct transportation to an intervention center for endovascular treatment, but non-LVO patients need rapid IV thrombolysis in the nearest center. Our aim was to evaluate prehospital triage strategies for suspected stroke patients in the United States. Methods: We used a decision tree model and geographic information system to estimate outcome of suspected stroke patients transported by ambulance within 4.5 hours after symptom onset. We compared the following strategies: (1) Always to nearest center, (2) American Heart Association algorithm (ie, directly to intervention center if a prehospital stroke scale suggests LVO and total driving time from scene to intervention center is 2). Results: Nationwide implementation of the American Heart Association algorithm increased the number of good outcomes by 594 (+1.0%) compared with transportation to the nearest center. The associated number of non-LVO patients transported to the intervention center was 16 714 (NNTI 28). The modified algorithms yielded an increase of 1013 (+1.8%) to 1369 (+2.4%) good outcomes, with a NNTI varying between 28 and 32. The algorithm without time limit was preferred in the majority of states (n=32 [65%]), followed by the algorithm with Conclusions: Prehospital triage strategies can greatly improve outcomes of the ischemic stroke population in the United States, but increase the number of non-LVO stroke patients transported to an intervention center. The current American Heart Association algorithm is suboptimal as a nationwide policy and should be modified to allow more delay when directly transporting LVO-suspected patients to an intervention center.

Background and Purpose: Cardiovascular risk factors, which are overall more prevalent in men, are considered the major risk factors for strokes among young adults. However, recent European data found the incidence of strokes to be higher in young women. Using a large US claims sample, we examined sex differences in the index stroke rate of young adults. Methods: We performed a retrospective cohort study of enrollees in a 10% random sample of PharMetrics, a nationally representative claims database of insured Americans from 2001 to 2014. Outcomes were index ischemic stroke events, based on inpatient admissions using International Classification of Diseases-Ninth Revision codes. The index stroke rate was estimated from Poisson rate models with time varying covariates for 2-year periods, stratified by sex and age groups. Results: We identified 20 554 index strokes (50.4% women; mean age 63) including 5198 in young adults ages 15 to 54. There was no difference by sex in the index stroke rate in the extremes of age groups 15 to 24 and ≥75 years old. However, in the 25 to 34 and 35 to 44 year age groups, more women had strokes than men (incidence rate ratio: men:women, 0.70 [95% CI, 0.57–0.86]; 0.87 [95% CI, 0.78–0.98], respectively). In contrast, in the 45 to 54, 55 to 64, and 65 to 74 year age groups, more men had strokes (incidence rate ratio, 1.25 [95% CI, 1.16–1.33]; 1.41 [95% CI, 1.18–1.34]; 1.18 [95% CI, 1.12–125], respectively). Conclusions: More young women than men have strokes, suggesting possible importance of sex-mediated etiologies of stroke. Understanding these drivers is critical to stroke treatment and prevention efforts in young adults.

BACKGROUND: No completed trials have compared carotid artery stenting to medical therapy. We examined the effectiveness of carotid artery stenting compared to medical therapy in patients with asymptomatic carotid stenosis. METHODS: We conducted a retrospective cohort study of 219,979 Veterans 65 years and older who received carotid imaging for asymptomatic carotid stenosis between 2005 and 2009 in the United States Veterans Health Administration. We constructed a sample of patients who received medical therapy (n=2509) and comparable patients who received carotid artery stenting (n=551) and followed them for five years. Using target trial methodology, we computed weighted Kaplan-Meier curves and estimated the risk of fatal and non-fatal stroke in each group over five years of follow-up. We also estimated the cumulative incidence functions for fatal and non-fatal stroke accounting for non-stroke deaths as competing risks. RESULTS: 551 patients received carotid artery stenting and 2509 patients received medical therapy. The observed rate of stroke or death (perioperative complications) within 30 days in the carotid artery stenting arm was 2.2%. Using the target-trial methodology, the 5-year risk of fatal and non-fatal stroke was similar among patients assigned to carotid artery stenting (6.9%) compared to patients assigned to medical therapy (7.1%) [(risk difference,- 0.1%, 95% CI (−2.6%, 2.7%)]. In an analysis that incorporated the competing risk of death, the risk difference between the two arms remained non-significant ([risk difference −1.5% (95%CI, (−3.0%, 0.3%)]. CONCLUSIONS: In this sample of older male adults, we found no difference between medical therapy and CAS in the treatment of asymptomatic carotid stenosis. Future studies in other settings are needed to confirm these findings.

Introduction: Associations between post-stroke vascular risk factors levels with post-stroke cognitive decline are uncertain. We determined associations between systolic blood pressure (BP), glucose, and low-density lipoprotein (LDL) cholesterol levels with post-stroke cognitive decline. Hypothesis: Higher post-stroke systolic BP, glucose, and LDL cholesterol levels are associated with faster post-stroke cognitive decline. Methods: This cohort study pooled data from 832 participants 18 and older with incident stroke and free of dementia before stroke (50% women and 32% Black) from 4 cohort studies from 1971-2019: Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, Framingham Offspring Study, and REasons for Geographic and Racial Differences in Stroke Study. Linear mixed-effects models were used to estimate longitudinal changes in cognition after incident stroke. The primary outcome was change in global cognition. Global cognition was harmonized across studies and standardized as T-scores (mean [SD], 50 [10]); a 1-point difference represents a 0.1-SD difference in cognition. Median (IQR) follow-up was 5.5 (3.3-8.3) years. Results: In separate models, higher post-stroke glucose and LDL levels, but not systolic BP, were associated with faster declines in global cognition (Models M1a, M1b, and M1c, Table 1). In a model with all three vascular risk factors, higher post-stroke mean glucose and LDL levels were associated with faster global cognition decline, though not to traditional levels of statistical significance; however, post-stroke mean systolic BP was not associated with global cognition decline (Model M2, Table 1). Older age was associated with faster cognitive decline in all models. Conclusions: Our results suggest that higher post-stroke glucose and LDL levels are associated with faster post-stroke cognitive decline. We found no evidence that post-stroke BP levels are associated with post-stroke cognitive decline.

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], I 2 =82%) and a nonsignificant sex difference in young adults 35 to 45 years (incidence rate ratio, 1.08 [0.85–1.38], I 2 =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.

Acute optic neuritis (ON) is variably treated with glucocorticoids. We aimed to describe factors associated with glucocorticoid use. In this retrospective, longitudinal cohort study of insured patients in the United States (2005–2019), adults 18–50 years old with one inpatient or ≥2 outpatient diagnoses of ON within 90 days were included. Glucocorticoid use was classified as none, any dose, and high-dose (>100 mg prednisone equivalent ≥1 days). The primary outcome was glucocorticoid receipt within 90 days of the first ON diagnosis. Multivariable logistic regression models assessed the relationship between glucocorticoid use and sociodemographics, comorbidities, clinician specialty, visit number, and year. Of 3026 people with ON, 65.8% were women (n = 1991), median age (interquartile range) was 38 years (31,44), and 68.6% were white (n = 2075). Glucocorticoids were received by 46% (n = 1385); 54.6% (n = 760/1385) of whom received high-dose. The odds of receiving glucocorticoids were higher among patients with multiple sclerosis (OR 1.61 [95%CI 1.28–2.04]; P < .001), MRI (OR 1.75 [95%CI 1.09–2.80]; P = .02), 3 (OR 1.80 [95%CI 1.46–2.22]; P < .001) or more (OR 4.08 [95%CI 3.37–4.95]; P < .001) outpatient ON visits, and in certain regions. Compared to ophthalmologists, patients diagnosed by neurologists (OR 1.36 [95%CI: 1.10–1.69], p = .005), emergency medicine (OR 3.97 [95%CI: 2.66–5.94]; P < .001) or inpatient clinicians (OR 2.94 [95%CI: 2.22–3.90]; P < .001) had higher odds of receiving glucocorticoids. Use increased 1.1% annually (P < .001). Demyelinating disease, care intensity, setting, region, and clinician type were associated with glucocorticoid use for ON. To optimize care, future studies should explore reasons for ON care variation, and patient/clinician preferences.

BACKGROUND: Ethnic differences in cognitive decline have been reported. Whether they can be explained by differences in systolic blood pressure (SBP) is uncertain. OBJECTIVE: Determine whether cumulative mean SBP levels explain differences in cognitive decline between Hispanic and White individuals. METHODS: Pooled cohort study of individual participant data from six cohorts (1971–2017). The present study reports results on SBP and cognition among Hispanic and White individuals. Outcomes were changes in global cognition (GC) (primary), executive function (EF) (secondary), and memory standardized as t-scores (mean [SD], 50 [10]); a 1-point difference represents a 0.1 SD difference in cognition. Median follow-up was 7.7 (Q1–Q3, 5.2–20.1) years. RESULTS: We included 24,570 participants free of stroke and dementia: 2,475 Hispanic individuals (median age, cumulative mean SBP at first cognitive assessment, 67 years, 132.5 mmHg; 40.8% men) and 22,095 White individuals (60 years,134 mmHg; 47.3% men). Hispanic individuals had slower declines in GC, EF, and memory than White individuals when all six cohorts were examined. Two cohorts recruited Hispanic individuals by design. In a sensitivity analysis, Hispanic individuals in these cohorts had faster decline in GC, similar decline in EF, and slower decline in memory than White individuals. Higher time-varying cumulative mean SBP was associated with faster declines in GC, EF, and memory in all analyses. After adjusting for time-varying cumulative mean SBP, differences in cognitive slopes between Hispanic and White individuals did not change. CONCLUSION: We found no evidence that cumulative mean SBP differences explained differences in cognitive decline between Hispanic and White individuals.

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

Epilepsy is a common, serious condition. Fortunately, seizure risk decreases with increasing seizure-free time on antiseizure medications (ASMs). Eventually, patients may consider whether to stop ASMs, which requires weighing treatment benefit versus burden. We developed a questionnaire to quantify patient preferences relevant to ASM decision-making. Respondents rated how concerning they would finding relevant items (e.g., seizure risks, side effects, cost) on a Visual Analogue Scale (VAS, 0–100) and then repeatedly chose the most and least concerning item from subsets (best-worst scaling, BWS). We pretested with neurologists, then recruited adults with epilepsy who were seizure-free at least one year. Primary outcomes were recruitment rate, and qualitative and Likert-based feedback. Secondary outcomes included VAS ratings and best-minus-worst scores. Thirty-one of 60 (52%) contacted patients completed the study. Most patients felt VAS questions were clear (28; 90%), easy to use (27; 87%), and assessed preferences well (25; 83%). Corresponding results for BWS questions were 27 (87%), 29 (97%), and 23 (77%). Physicians suggested adding a ‘warmup’ question showing a completed example and simplifying terminology. Patients suggested ways to clarify instructions. Cost, inconvenience of taking medication, and laboratory monitoring were the least concerning items. Cognitive side effects and a 50% seizure risk in the next year were the most concerning items. Twelve (39%) of patients made at least one ‘inconsistent choice’ for example ranking a higher seizure risk as lower concern compared with a lower seizure risk, though ‘inconsistent choices’ represented only 3% of all question blocks. Our recruitment rate was favorable, most patients agreed the survey was clear, and we describe areas for improvement. ‘Inconsistent’ responses may lead us to collapse seizure probability items into a single ‘seizure’ category. Evidence regarding how patients weigh benefits and harms may inform care and guideline development.

Background and ObjectivesTo describe neurologist practice patterns, challenges, and decision support needs pertaining to withdrawal of antiseizure medications (ASMs) in patients with well-controlled epilepsy.MethodsWe 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.ResultsWe 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.DiscussionMost 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.

This study assesses whether patients with status epilepticus are receiving first-line treatment consistent with current guidelines.

Introduction: Variation exists in outcomes following out-of-hospital cardiac arrest (OHCA), but whether racial/ethnic disparities exist in post-arrest provision of therapeutic hypothermia (TH) is unknown. Hypothesis: Racial/ethnic disparities exist in the utilization of guideline-recommended TH following OHCA. Methods: We performed a retrospective analysis of a cohort of 96,695 patients who survived to hospital admission following OHCA from the Cardiac Arrest Registry to Enhance Survival, whose catchment area represents ~40% of the United States, from 2013 through 2019. Our primary exposure was race/ethnicity, and the primary outcome was utilization of TH. We performed a secondary analysis to assess for racial/ethnic disparities in the reasons why TH was not used (supplemental data element data available since 2016). Results: Among 96,695 patients [mean (SD) age 61.4 (16.3) years, 24.6% Black, 8.0% Hispanic/Latino, 63.4% White] that survived to hospital admission following OHCA, 54,687 (56.6%) did not receive TH. Using a mixed-effects model that adjusted for patient, arrest, neighborhood, and hospital factors with state of arrest modeled as a random intercept to account for clustering, we found that Hispanics/Latinos were less likely to receive TH than Whites (Odds Ratio [OR] 0.79, 95 % Confidence Interval [CI] 0.75-0.83). When the clustering variable was changed from the state of arrest to the admitting hospital, Hispanics/Latinos were more likely to receive TH (OR 1.07, 95% CI 1.00 to 1.14). In the 22,896 patients with data regarding why they did not receive TH, a higher percentage of Hispanics/Latinos compared to Blacks and Whites did not receive TH due to lack of a TH program at the hospital (4.0% vs. 2.5 % vs 1.8%, p < .001). No disparity in TH utilization was found for Black patients. Conclusion: We found disparities in access to TH for Hispanics/Latinos following OHCA. Reassuringly, we did not find any disparity in TH utilization for Black patients.

Background Variation exists in outcomes following out‐of‐hospital cardiac arrest (OHCA), but whether racial and ethnic disparities exist in post‐arrest provision of targeted temperature management (TTM) is unknown. Methods and Results We performed a retrospective analysis of a prospectively collected cohort of patients who survived to admission following OHCA from the Cardiac Arrest Registry to Enhance Survival, whose catchment area represents ~50% of the United States from 2013‐2019. Our primary exposure was race/ethnicity and primary outcome was utilization of TTM. We built a mixed‐effects model with both state of arrest and admitting hospital modeled as random intercepts to account for clustering. Among 96,695 patients (24.6% Black, 8.0% Hispanic/Latino, 63.4% White), a smaller percentage of Hispanic/Latino patients received TTM than Black or White patients (37.5% vs. 45.0 % vs 43.3%, P < .001) following OHCA. In the mixed‐effects model, Black patients (Odds Ratio [OR] 1.153, 95% Confidence Interval [CI] 1.102‐1.207, P < .001) and Hispanic/Latino patients (OR 1.086, 95% CI 1.017‐1.159, P < .001) were slightly more likely to receive TTM compared to White patients, perhaps due to worse admission neurological status. We did find community level disparity as Hispanic/Latino‐serving hospitals (defined as the top decile of hospitals that cared for the highest proportion of Hispanic/Latino patients) provided less TTM (OR 0.587, 95% CI 0.474 to 0.742, P < .001). Conclusions Reassuringly, we did not find evidence of intrahospital or interpersonal racial or ethnic disparity in the provision of TTM. However, we did find inter‐hospital, community level disparity. Hispanic/Latino‐serving hospitals provided less guideline‐recommended TTM after OHCA.

Background and ObjectiveTo assess the accuracy of definitions of drug-resistant epilepsy applied to administrative claims data.MethodsWe randomly sampled 450 patients from a tertiary health system with ≥1 epilepsy/convulsion encounter, ≥2 distinct antiseizure medications (ASMs) from 2014 to 2020, and ≥2 years of electronic medical records (EMR) data. We established a drug-resistant epilepsy diagnosis at a specific visit by reviewing EMR data and using a rubric based on the 2010 International League Against Epilepsy definition. We performed logistic regressions to assess clinically relevant predictors of drug-resistant epilepsy and to inform claims-based definitions.ResultsOf 450 patients reviewed, 150 were excluded for insufficient EMR data. Of the 300 patients included, 98 (33%) met criteria for current drug-resistant epilepsy. The strongest predictors of current drug-resistant epilepsy were drug-resistant epilepsy diagnosis code (odds ratio [OR] 16.9, 95% confidence interval [CI] 8.8–32.2), ≥2 ASMs in the prior 2 years (OR 13.0, 95% CI 5.1–33.3), ≥3 nongabapentinoid ASMs (OR 10.3, 95% CI 5.4–19.6), neurosurgery visit (OR 45.2, 95% CI 5.9–344.3), and epilepsy surgery (OR 30.7, 95% CI 7.1–133.3). We created claims-based drug-resistant epilepsy definitions (1) to maximize overall predictiveness (drug-resistant epilepsy diagnosis; sensitivity 0.86, specificity 0.74, area under the receiver operating characteristics curve [AUROC] 0.80), (2) to maximize sensitivity (drug-resistant epilepsy diagnosis or ≥3 ASMs; sensitivity 0.98, specificity 0.47, AUROC 0.72), and (3) to maximize specificity (drug-resistant epilepsy diagnosis and ≥3 nongabapentinoid ASMs; sensitivity 0.42, specificity 0.98, AUROC 0.70).DiscussionOur findings provide validation for several claims-based definitions of drug-resistant epilepsy that can be applied to a variety of research questions.

OBJECTIVE: 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 3 scenarios describing hypothetical patients with headaches. Descriptive statistics were used to summarize responses, stratified by clinician type (physicians or advanced practice clinicians (APC)) and specialty (neurology or primary care). RESULTS: The survey was successfully completed by 431/1426 clinicians (30.2% response rate). Overall, 317/429 (73.9%) believed neuroimaging was overused for patients with headaches. However, clinicians would utilize neuroimaging a mean (standard deviation (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.