Healthcare utilization impacts of an eConsult program for headache at an academic medical center

INTRODUCTION

Interprofessional consultations ("eConsults") can reduce healthcare utilization. However, the impact of eConsults on healthcare utilization remains poorly characterized among patients with headache.

METHODS

We performed a retrospective, 1:1 matched cohort study comparing patients evaluated for headache via eConsult request or in-person referral at the Mount Sinai Health System in New York. Groups were matched on clinical and demographic characteristics. Our primary outcome was one or more outpatient headache-related encounters in 6 months following referral date. Secondary outcomes included one or more all-cause outpatient neurology and headache-related emergency department (ED) encounters during the same period. We used univariable and multivariable logistic regression to model associations between independent variables and outcomes.

RESULTS

We identified 74 patients with headache eConsults who were matched to 74 patients with in-person referrals. Patients in the eConsult group were less likely to achieve the primary outcome (29.7% vs 62.2%, P < 0.0001) or have an all-cause outpatient neurology encounter (33.8% vs 79.7%, P < 0.0001) than patients in the comparison group. Both groups did not significantly differ by headache-related ED encounters. In multivariable analyses, patients in the eConsult group had significantly lower odds of having one or more headache-related or all-cause neurology encounters than patients in the comparison group (odds ratio (OR) 0.3, 95% confidence interval (CI) 0.1-0.6; OR 0.1, 95% CI 0.1-0.3, respectively).

DISCUSSION

In comparison to in-person referrals, eConsult requests for headache were associated with reduced likelihood of outpatient neurology encounters in the short-term but not with differential use of headache-related ED encounters. Larger-scale, prospective studies should validate our findings and assess patient outcomes.

Latent class analysis of eHealth behaviors among adults with epilepsy

OBJECTIVE

The objective of this study was to determine the proportions of uptake and factors associated with electronic health (eHealth) behaviors among adults with epilepsy.

METHODS

The 2013, 2015, and 2017 National Health Interview Surveys were analyzed. We assessed the proportions of use of five domains of eHealth in those with epilepsy: looked up health information on the internet, filled a prescription on the internet, scheduled a medical appointment on the internet, communicated with a health care provider via email, and used chat groups to learn about health topics. Multivariate logistic regressions were conducted to identify factors associated with any eHealth behaviors among those with active epilepsy. Latent class analysis was performed to identify underlying patterns of eHealth activity. Survey participants were classified into three discrete classes: (1) frequent, (2) infrequent, and (3) nonusers of eHealth. Multinomial logistic regression was performed to identify factors associated with frequency of eHealth use.

RESULTS

There were 1770 adults with epilepsy, of whom 65.87% had at least one eHealth behavior in the prior year. By domain, 62.61% looked up health information on the internet, 15.81% filled a prescription on the internet, 14.95% scheduled a medical appointment on the internet, 17.20% communicated with a health care provider via email, and 8.27% used chat groups to learn about health topics. Among those with active epilepsy, female sex, more frequent computer usage, and internet usage were associated with any eHealth behavior. Female sex and frequent computer use were associated with frequent eHealth use as compared to nonusers.

SIGNIFICANCE

A majority of persons with epilepsy were found to use at least one form of eHealth. Various technological and demographic factors were associated with eHealth behaviors. Individuals with lower eHealth behaviors should be provided with targeted interventions that address barriers to the adoption of these technologies.

Trends in the Utilization of Teleneurology and Other Healthcare Resources Prior to and During the COVID-19 Pandemic in an Urban, Tertiary Health System

BACKGROUND

Patient groups traditionally affected by health disparities were less likely to use video teleneurology (TN) care during the initial COVID-19 pandemic surge in the United States. Whether this asymmetry persisted later in the pandemic or was accompanied with a loss of access to care remains unknown.

METHODS

We conducted a retrospective cohort study using patient data from a multicenter healthcare system in New York City. We identified all established pediatric or adult neurology patients with at least two prior outpatient visits between June 16th, 2019 and March 15th, 2020 using our electronic medical record. For this established pre-COVID cohort, we identified telephone, in-person, video TN or emergency department visits and hospital admissions for any cause between March 16th and December 15th, 2020 ("COVID period"). We determined clinical, sociodemographic, income, and visit characteristics. Our primary outcome was video TN utilization, and our main secondary outcome was loss to follow-up during the COVID period. We used multivariable logistic regression to model the relationship between patient-level characteristics and both outcomes.

RESULTS

We identified 23,714 unique visits during the COVID period, which corresponded to 14,170 established patients from our institutional Neurology clinics during the pre-COVID period. In our cohort, 4,944 (34.9%) utilized TN and 4,997 (35.3%) were entirely lost to follow-up during the COVID period. In the adjusted regression analysis, Black or African-American race [adjusted odds ratio (aOR) 0.60, 97.5%CI 0.52-0.70], non-English preferred language (aOR 0.49, 97.5%CI 0.39-0.61), Medicaid insurance (aOR 0.50, 97.5%CI 0.44-0.57), and Medicare insurance (aOR 0.73, 97.5%CI 0.65-0.83) had decreased odds of TN utilization. Older age (aOR 0.98, 97.5%CI 0.98-0.99), female sex (aOR 0.90 97.5%CI 0.83-0.99), and Medicaid insurance (aOR 0.78, 0.68-0.90) were associated with decreased odds of loss to follow-up.

CONCLUSION

In the first 9 months of the COVID-19 pandemic, we found sociodemographic patterns in TN utilization that were similar to those found very early in the pandemic. However, these sociodemographic characteristics were not associated with loss to follow-up, suggesting that lack of TN utilization may not have coincided with loss of access to care.

Treating High-Risk TIA and Minor Stroke Patients With Dual Antiplatelet Therapy: A National Survey of Emergency Medicine Physicians

BACKGROUND

Treatment with aspirin plus clopidogrel, dual antiplatelet therapy (DAPT), within 24 hours of high-risk transient ischemic attack (TIA) or minor stroke symptoms to eligible patients is recommended by national guidelines. Whether or not this treatment has been adopted by emergency medicine (EM) physicians is uncertain.

METHODS

We conducted an online survey of EM physicians in the United States. The survey consisted of 13 multiple choice questions regarding physician characteristics, practice settings, and usual approach to TIA and minor stroke treatment. We report participant characteristics and use chi-squared tests to compare between groups.

RESULTS

We included 162 participants in the final study analysis. 103 participants (64%) were in practice for >5 years and 96 (59%) were at nonacademic centers; all were EM board-certified or board-eligible. Only 9 (6%) participants reported that they would start DAPT for minor stroke and 8 (5%) reported that they would start DAPT after high-risk TIA. Aspirin alone was the selected treatment by 81 (50%) participants for minor stroke patients who presented within 24 hours of symptom onset and were not candidates for thrombolysis. For minor stroke, 69 (43%) participants indicated that they would defer medical management to consultants or another team. Similarly, 75 (46%) of participants chose aspirin alone to treat high-risk TIA; 74 (46%) reported they would defer medical management after TIA to consultants or another team.

CONCLUSION

In a survey of EM physicians, we found that the reported rate of DAPT treatment for eligible patients with high-risk TIA and minor stroke was low.

Teleneurology Expansion in Response to the COVID-19 Outbreak at a Tertiary Health System in New York City

Objective

To assess the implementation of teleneurology (TN), including patient and clinician experiences, during the coronavirus respiratory disease 2019 (COVID-19) pandemic.

Methods

We studied synchronous (video visit) and asynchronous (store-and-forward, patient-portal evaluation, remote monitoring) TN utilization in the Mount Sinai Health System Neurology Department in New York, 2 months before and after the start of our department's response to the pandemic in mid-March 2020. Weekly division meetings enabled ongoing assessments and analysis of barriers and facilitators according to the Consolidated Framework for Implementation Research and the Expert Recommendations for Implementing Change models. We used postvisit surveys of clinicians (from April 13 to May 15, 2020) and patients (from May 11 to 15, 2020) to determine technology platforms used, and TN experience and acceptability, using Likert scales (1 = very poor/unlikely to 5 = very good/likely).

Results

Over the 4-month period, 117 TN clinicians (n = 14 subspecialties) conducted 4,225 TN visits with 3,717 patients (52 pre- vs 4,173 post-COVID-19). No asynchronous TN services were delivered. Post-COVID-19, the number of TN clinicians, subspecialties performing TN, and visits increased by 963%, 133%, and 7,925%, respectively. Mean acceptability among patients and clinicians was 4.7 (SD 0.6) and 3.4 (SD 1.6), respectively. Most video visits were completed using Epic MyChart (78.5%) and Zoom (8.1%). TN implementation facilitators included Medicare geographic restriction waivers, development of clinician educational materials, and MyChart outreach programs for patients experiencing technical difficulties.

Conclusions

A significant expansion of TN utilization accompanied the COVID-19 response. Patients found TN more acceptable than did clinicians. Proactive application of an implementation framework facilitated rapid and effective TN expansion.

Comparative analysis, applications, and interpretation of electronic health record-based stroke phenotyping methods

BACKGROUND

Accurate identification of acute ischemic stroke (AIS) patient cohorts is essential for a wide range of clinical investigations. Automated phenotyping methods that leverage electronic health records (EHRs) represent a fundamentally new approach cohort identification without current laborious and ungeneralizable generation of phenotyping algorithms. We systematically compared and evaluated the ability of machine learning algorithms and case-control combinations to phenotype acute ischemic stroke patients using data from an EHR.

MATERIALS AND METHODS

Using structured patient data from the EHR at a tertiary-care hospital system, we built and evaluated machine learning models to identify patients with AIS based on 75 different case-control and classifier combinations. We then estimated the prevalence of AIS patients across the EHR. Finally, we externally validated the ability of the models to detect AIS patients without AIS diagnosis codes using the UK Biobank.

RESULTS

Across all models, we found that the mean AUROC for detecting AIS was 0.963 ± 0.0520 and average precision score 0.790 ± 0.196 with minimal feature processing. Classifiers trained with cases with AIS diagnosis codes and controls with no cerebrovascular disease codes had the best average F1 score (0.832 ± 0.0383). In the external validation, we found that the top probabilities from a model-predicted AIS cohort were significantly enriched for AIS patients without AIS diagnosis codes (60-150 fold over expected).

CONCLUSIONS

Our findings support machine learning algorithms as a generalizable way to accurately identify AIS patients without using process-intensive manual feature curation. When a set of AIS patients is unavailable, diagnosis codes may be used to train classifier models.

Emergent Large Vessel Occlusion Stroke During New York City's COVID-19 Outbreak: Clinical Characteristics and Paraclinical Findings

BACKGROUND AND PURPOSE

The 2019 novel coronavirus outbreak and its associated disease (coronavirus disease 2019 [COVID-19]) have created a worldwide pandemic. Early data suggest higher rate of ischemic stroke in severe COVID-19 infection. We evaluated whether a relationship exists between emergent large vessel occlusion (ELVO) and the ongoing COVID-19 outbreak.

METHODS

This is a retrospective, observational case series. Data were collected from all patients who presented with ELVO to the Mount Sinai Health System Hospitals across New York City during the peak 3 weeks of hospitalization and death from COVID-19. Patients' demographic, comorbid conditions, cardiovascular risk factors, COVID-19 disease status, and clinical presentation were extracted from the electronic medical record. Comparison was made between COVID-19 positive and negative cohorts. The incidence of ELVO stroke was compared with the pre-COVID period.

RESULTS

Forty-five consecutive ELVO patients presented during the observation period. Fifty-three percent of patients tested positive for COVID-19. Total patients' mean (±SD) age was 66 (±17). Patients with COVID-19 were significantly younger than patients without COVID-19, 59±13 versus 74±17 (odds ratio [95% CI], 0.94 [0.81-0.98]; P=0.004). Seventy-five percent of patients with COVID-19 were male compared with 43% of patients without COVID-19 (odds ratio [95% CI], 3.99 [1.12-14.17]; P=0.032). Patients with COVID-19 were less likely to be White (8% versus 38% [odds ratio (95% CI), 0.15 (0.04-0.81); P=0.027]). In comparison to a similar time duration before the COVID-19 outbreak, a 2-fold increase in the total number of ELVO was observed (estimate: 0.78 [95% CI, 0.47-1.08], P≤0.0001).

CONCLUSIONS

More than half of the ELVO stroke patients during the peak time of the New York City's COVID-19 outbreak were COVID-19 positive, and those patients with COVID-19 were younger, more likely to be male, and less likely to be White. Our findings also suggest an increase in the incidence of ELVO stroke during the peak of the COVID-19 outbreak.

History of Stroke Is Independently Associated With In-Hospital Death in Patients With COVID-19

Background and Purpose:

In December 2019, an outbreak of severe acute respiratory syndrome coronavirus causing coronavirus disease 2019 (COVID-19) occurred in China, and evolved into a worldwide pandemic. It remains unclear whether the history of cerebrovascular disease is associated with in-hospital death in patients with COVID-19.

Methods:

We conducted a retrospective, multicenter cohort study at Mount Sinai Health System in New York City. Using our institutional data warehouse, we identified all adult patients who were admitted to the hospital between March 1, 2020 and May 1, 2020 and had a positive nasopharyngeal swab polymerase chain reaction test for severe acute respiratory syndrome coronavirus in the emergency department. Using our institutional electronic health record, we extracted clinical characteristics of the cohort, including age, sex, and comorbidities. Using multivariable logistic regression to control for medical comorbidities, we modeled the relationship between history of stroke and all-cause, in-hospital death.

Results:

We identified 3248 patients, of whom 387 (11.9%) had a history of stroke. Compared with patients without history of stroke, patients with a history of stroke were significantly older, and were significantly more likely to have a history of all medical comorbidities except for obesity, which was more prevalent in patients without a history of stroke. Compared with patients without history of stroke, patients with a history of stroke had higher in-hospital death rates during the study period (48.6% versus 31.7%, P<0.001). In the multivariable analysis, history of stroke (adjusted odds ratio, 1.28 [95% CI, 1.01–1.63]) was significantly associated with in-hospital death.

Conclusions:

We found that history of stroke was associated with in-hospital death among hospitalized patients with COVID-19. Further studies should confirm these results.

A Multilevel Analysis of Surgical Category and Individual Patient-Level Risk Factors for Postoperative Stroke

Background and Purpose

Many studies supporting the association between specific surgical procedure categories and postoperative stroke (POS) do not account for differences in patient-level characteristics between and within surgical categories. The risk of POS after high-risk procedure categories remains unknown after adjusting for such differences in patient-level characteristics.

Methods

Using inpatients in the American College of Surgeons National Surgical Quality Initiative Program database, we conducted a retrospective cohort study between January 1, 2000, and December 31, 2010. Our primary outcome was POS within 30 days of surgery. We characterized the relationship between surgical- and individual patient-level factors and POS by using multivariable, multilevel logistic regression that accounted for clustering of patient-level factors with surgical categories.

Results

We identified 729 886 patients, 2703 (0.3%) of whom developed POS. Dependent functional status (odds ratio [OR]: 4.11, 95% confidence interval [95% CI]: 3.60-4.69), history of stroke (OR: 2.35, 95%CI: 2.06-2.69) or transient ischemic attack (OR: 2.49 95%CI: 2.19-2.83), active smoking (OR: 1.20, 95%CI: 1.08-1.32), hypertension (OR: 2.11, 95%CI: 2.19-2.82), chronic obstructive pulmonary disease (OR: 1.39 95%CI: 1.21-1.59), and acute renal failure (OR: 2.35, 95%CI: 1.85-2.99) were significantly associated with POS. After adjusting for clustering, patients who underwent cardiac (OR: 11.25, 95%CI: 8.52-14.87), vascular (OR: 4.75, 95%CI: 3.88-5.82), neurological (OR: 4.60, 95%CI: 3.48-6.08), and general surgery (OR: 1.40, 95%CI: 1.15-1.70) had significantly greater odds of POS compared to patients undergoing other types of surgical procedures.

Conclusions

Vascular, cardiac, and neurological surgery remained strongly associated with POS in an analysis accounting for the association between patient-level factors and surgical categories.

Geographic Analysis of Mobile Stroke Unit Treatment in a Dense Urban Area: The New York City METRONOME Registry

Background Mobile stroke units (MSUs) reduce time to intravenous thrombolysis in acute ischemic stroke. Whether this advantage exists in densely populated urban areas with many proximate hospitals is unclear. Methods and Results We evaluated patients from the METRONOME (Metropolitan New York Mobile Stroke) registry with suspected acute ischemic stroke who were transported by a bi-institutional MSU operating in Manhattan, New York, from October 2016 to September 2017. The comparison group included patients transported to our hospitals via conventional ambulance for acute ischemic stroke during the same hours of MSU operation (Monday to Friday, 9 am to 5 pm). Our exposure was MSU care, and our primary outcome was dispatch-to-thrombolysis time. We estimated mean differences in the primary outcome between both groups, adjusting for clinical, demographic, and geographic factors, including numbers of nearby designated stroke centers and population density. We identified 66 patients treated or transported by MSU and 19 patients transported by conventional ambulance. Patients receiving MSU care had significantly shorter dispatch-to-thrombolysis time than patients receiving conventional care (mean: 61.2 versus 91.6 minutes; P=0.001). Compared with patients receiving conventional care, patients receiving MSU care were significantly more likely to be picked up closer to a higher mean number of designated stroke centers in a 2.0-mile radius (4.8 versus 2.7, P=0.002). In multivariable analysis, MSU care was associated with a mean decrease in dispatch-to-thrombolysis time of 29.7 minutes (95% CI, 6.9-52.5) compared with conventional care. Conclusions In a densely populated urban area with a high number of intermediary stroke centers, MSU care was associated with substantially quicker time to thrombolysis compared with conventional ambulance care.

Neurological Dashboards and Consultation Turnaround Time at an Academic Medical Center

BACKGROUND

Neurologists perform a significant amount of consultative work. Aggregative electronic health record (EHR) dashboards may help to reduce consultation turnaround time (TAT) which may reflect time spent interfacing with the EHR.

OBJECTIVES

This study was aimed to measure the difference in TAT before and after the implementation of a neurological dashboard.

METHODS

We retrospectively studied a neurological dashboard in a read-only, web-based, clinical data review platform at an academic medical center that was separate from our institutional EHR. Using our EHR, we identified all distinct initial neurological consultations at our institution that were completed in the 5 months before, 5 months after, and 12 months after the dashboard go-live in December 2017. Using log data, we determined total dashboard users, unique page hits, patient-chart accesses, and user departments at 5 months after go-live. We calculated TAT as the difference in time between the placement of the consultation order and completion of the consultation note in the EHR.

RESULTS

By April 30th in 2018, we identified 269 unique users, 684 dashboard page hits (median hits/user 1.0, interquartile range [IQR] = 1.0), and 510 unique patient-chart accesses. In 5 months before the go-live, 1,434 neurology consultations were completed with a median TAT of 2.0 hours (IQR = 2.5) which was significantly longer than during 5 months after the go-live, with 1,672 neurology consultations completed with a median TAT of 1.8 hours (IQR = 2.2; p = 0.001). Over the following 7 months, 2,160 consultations were completed and median TAT remained unchanged at 1.8 hours (IQR = 2.5).

CONCLUSION

At a large academic institution, we found a significant decrease in inpatient consult TAT 5 and 12 months after the implementation of a neurological dashboard. Further study is necessary to investigate the cognitive and operational effects of aggregative dashboards in neurology and to optimize their use.

Associations between cerebrovascular risk factors and parkinson disease

OBJECTIVE

To determine whether cerebrovascular risk factors are associated with subsequent diagnoses of Parkinson disease, and whether these associations are similar in magnitude to those with subsequent diagnoses of Alzheimer disease.

METHODS

This was a retrospective cohort study using claims data from a 5% random sample of Medicare beneficiaries from 2008 to 2015. The exposures were stroke, atrial fibrillation, coronary disease, hyperlipidemia, hypertension, sleep apnea, diabetes mellitus, heart failure, peripheral vascular disease, chronic kidney disease, chronic obstructive pulmonary disease, valvular heart disease, tobacco use, and alcohol abuse. The primary outcome was a new diagnosis of idiopathic Parkinson disease. The secondary outcome was a new diagnosis of Alzheimer disease. Marginal structural Cox models adjusting for time-dependent confounding were used to characterize the association between exposures and outcomes. We also evaluated the association between cerebrovascular risk factors and subsequent renal colic (negative control).

RESULTS

Among 1,035,536 Medicare beneficiaries followed for a mean of 5.2 years, 15,531 (1.5%) participants were diagnosed with Parkinson disease and 81,974 (7.9%) were diagnosed with Alzheimer disease. Most evaluated cerebrovascular risk factors, including prior stroke (hazard ratio = 1.55; 95% confidence interval = 1.39-1.72), were associated with the subsequent diagnosis of Parkinson disease. The magnitudes of these associations were similar, but attenuated, to the associations between cerebrovascular risk factors and Alzheimer disease. Confirming the validity of our analytical model, most cerebrovascular risk factors were not associated with the subsequent diagnosis of renal colic.

INTERPRETATION

Cerebrovascular risk factors are associated with Parkinson disease, an effect comparable to their association with Alzheimer disease. ANN NEUROL 2019;86:572-581.

Abstract WP104: Clinical Characteristics of Stroke Mimics Treated on an Urban Mobile Stroke Unit

Introduction: It is unknown how the clinical characteristics of stroke mimics treated on Mobile Stroke Units (MSUs) compare to confirmed acute strokes treated on these units.

Methods: We retrospectively analyzed all patients transported by the NewYork-Presbyterian MSU in New York City from October 2016-May 2018. A vascular neurologist assigned a final diagnosis after comprehensive medical record review. Clinical data were abstracted, including comorbidities, presenting symptoms, stroke severity, acute treatments, and short-term outcomes. We compared characteristics of patients with a stroke mimic diagnosis versus those with acute ischemic or hemorrhagic stroke using targeted minimum loss-based estimation to adjust for demographics, comorbidities, NIH Stroke Scale (NIHSS) score, and intravenous tPA administration.

Results: Among 92 suspected stroke patients transported by MSU, 56 (61%) had confirmed acute stroke (77% ischemic, 23% hemorrhagic) and 36 (39%) had a stroke mimic. Mimics consisted of seizure (n=8), metabolic encephalopathy (n=6), somatoform disorders (n=4), and others (n=18). The mean NIHSS score was 8 (SD 7) among mimics versus 11 (SD 8) among confirmed strokes (p=0.14). The top presenting symptoms among mimics were unilateral weakness (n=8), aphasia (n=6), confusion (n=6), and decreased consciousness (n=6). Nine mimics (25%) received tPA and none had hemorrhagic conversion; while 30 (53%) confirmed strokes received tPA and 2 (7%) had hemorrhagic conversion. There was no difference in MSU arrival-to-tPA time between groups (46 vs. 44 minutes, p=0.70). In multivariable analyses, compared to patients with confirmed stroke, mimics had significantly lower NIHSS scores, higher initial blood pressures, and shorter lengths-of-stay. Rates of death and discharge disposition were similar between groups.

Conclusions: Among patients transported by a MSU for suspected stroke, two-fifths were stroke mimics. Seizure, metabolic encephalopathy, and somatoform disorders were the most common mimic diagnoses. Patients with stroke mimics had lower NIHSS scores and less often were treated with tPA.

Abstract WP92: Radiologist Inter-rater Reliability of Prehospital Alberta Stroke Program Early CT Scores on a Mobile Stroke Unit

Introduction: The computed tomography (CT) capabilities of mobile stroke units (MSUs) may facilitate prehospital triaging of patients with suspected large-vessel occlusion directly to thrombectomy-capable centers. However, little is known about the reliability of radiological interpretation of early ischemic changes on prehospital CTs.

Methods: We identified all patients transported by the NewYork-Presbyterian MSU to Weill Cornell Medical Center with the diagnosis of acute ischemic stroke, transient ischemic attack, or stroke mimic between October 3, 2016 and December 31, 2017. All patients underwent noncontrast head CT on board the MSU using a CereTom® scanner. As controls, we matched these patients 1:1 by diagnosis to patients who were transported by standard ambulance and underwent noncontrast brain CT in our emergency department (ED) over the same period. Two neuroradiologists, blinded to patients’ characteristics and final diagnosis, independently calculated Alberta Stroke Program Early CT Scores (ASPECTS) on all scans. Weighted percent agreement and Cohen’s κ were used to assess inter-rater reliability, and paired t-tests were used to compare these metrics between MSU and ED scans.

Results: Among 46 MSU patients and 46 ED patients, 52% had a diagnosis of acute ischemic stroke, 46% a diagnosis of stroke mimic, and 2% a diagnosis of transient ischemic attack. For ASPECTS score as a continuous outcome, the weighted inter-rater agreement was 98% for MSU scans versus 96% for ED scans (mean difference, 2%; 95% CI, -1% to 5%) and the weighted κ was 0.49 for MSU scans versus 0.54 for ED scans (mean difference, -0.05; 95% CI, -0.61 to 0.51). For ASPECTS score categorized as 0-4, 5-7, or 8-10, the weighted inter-rater agreement was 99% for MSU scans versus 97% for ED scans (mean difference, 2%; 95% CI, -2% to 7%) and the weighted κ was 0.66 for MSU scans versus 0.55 for ED scans (mean difference, 0.10; 95% CI, -0.87 to 1.08).

Conclusions: In a sample of 96 patients, which limited our power to detect small differences, we found no substantial difference in the inter-rater reliability of ASPECTS scores obtained from MSU CTs versus ED CTs.

Impact of Patient Language on Emergency Medical Service Use and Prenotification for Acute Ischemic Stroke

Background and Purpose

Use of emergency medical services (EMS) is associated with decreased door-to-needle time in acute ischemic stroke (AIS). Whether patient language affects EMS utilization and prenotification in AIS has been understudied. We sought to characterize EMS use and prenotification by patient language among intravenous tissue plasminogen activator (IV-tPA) tissue plasminogen (IV-tPA) treated patients at a single center with a large Spanish-speaking patient population.

Methods

We performed a retrospective analysis of all patients who received IV-tPA in our emergency department between July 2011 and June 2016. Baseline characteristics, EMS use, and prenotification were compared between English- and Spanish-speaking patients. Logistic regression was used to measure the association between patient language and EMS use.

Results

Of 391 patients who received IV-tPA, 208 (53%) primarily spoke English and 174 (45%) primarily spoke Spanish. Demographic and clinical factors including National Institutes of Health Stroke Scale (NIHSS) did not differ between language groups. Emergency medical services use was higher among Spanish-speaking patients (82% vs 70%; P < .01). Prenotification did not differ by language (61% vs 63%; P = .8). In a multivariable model adjusted for age, sex, and NIHSS, Spanish speakers remained more likely to use EMS (odds ratio: 1.8, 95% confidence interval: 1.1-3.0).

Conclusion

Emergency medical services usage was higher in Spanish speakers compared to English speakers among AIS patients treated with IV-tPA; however, prenotification rates did not differ. Future studies should evaluate differences in EMS utilization according to primary language and ethnicity.

Risk of seizures and status epilepticus in older patients with liver disease

OBJECTIVE

Seizures can be provoked by systemic diseases associated with metabolic derangements, but the association between liver disease and seizures remains unclear.

METHODS

We performed a retrospective cohort study using inpatient and outpatient claims between 2008 and 2015 from a nationally representative 5% sample of Medicare beneficiaries. The primary exposure variable was cirrhosis, and the secondary exposure was mild, noncirrhotic liver disease. The primary outcome was seizure, and the secondary outcome was status epilepticus. Diagnoses were ascertained using validated International Classification of Diseases, Ninth Edition, Clinical Modification codes. Survival statistics were used to calculate incidence rates, and Cox proportional hazards models were used to examine the association between exposures and outcomes while adjusting for seizure risk factors.

RESULTS

Among 1 782 402 beneficiaries, we identified 10 393 (0.6%) beneficiaries with cirrhosis and 19 557 (1.1%) with mild, noncirrhotic liver disease. Individuals with liver disease were older and had more seizure risk factors than those without liver disease. Over 4.6 ± 2.2 years of follow-up, 49 843 (2.8%) individuals were diagnosed with seizures and 25 patients (0.001%) were diagnosed with status epilepticus. Cirrhosis was not associated with seizures (hazard ratio [HR] = 1.1, 95% confidence interval [CI] = 1.0-1.3), but there was an association with status epilepticus (HR = 1.9, 95% CI = 1.3-2.8). Mild liver disease was not associated with a higher risk of seizures (HR = 0.8, 95% CI = 0.6-0.9) or status epilepticus (HR = 1.1, 95% CI = 0.7-1.5).

SIGNIFICANCE

In a large, population-based cohort, we found an association between cirrhosis and status epilepticus, but no overall association between liver disease and seizures.

Ischemic Stroke After Emergency Department Discharge for Symptoms of Transient Neurological Attack

Background and Purpose

The significance of transient neurological attack (TNA) symptoms is unclear. We sought to determine the risk of ischemic stroke after discharge from the emergency department (ED) with a diagnosis consistent with symptoms of TNA.

Methods

Using administrative claims data, we identified patients discharged from EDs in New York between 2006 and 2012 with a primary discharge diagnosis of a TNA symptom, defined as altered mental status, generalized weakness, and sensory changes. The primary outcome was ischemic stroke. We used Kaplan-Meier survival statistics to calculate cumulative rates, and Cox regression to compare stroke risk after TNA versus after transient ischemic attack (TIA; positive control) or renal colic (negative control) while adjusting for demographics and vascular risk factors.

Results

Of 499 369 patients diagnosed with a TNA symptom and discharged from the ED, 7756 were hospitalized for ischemic stroke over a period of 4.7 (±1.9) years. At 90 days, the cumulative stroke rate was 0.29% (95% confidence interval [CI]: 0.28%-0.31%) after TNA symptoms versus 2.08% (95% CI: 1.89%-2.28%) after TIA and 0.03% (95% CI: 0.02%-0.04%) after renal colic. The hazard ratio (HR) of stroke was higher after TNA than after renal colic (HR: 2.13; 95% CI: 1.90-2.40) but significantly lower than after TIA (HR: 0.47; 95% CI: 0.44-0.50). Compared to TIA, TNA was less strongly associated with stroke among patients under 60 years of age compared to those over 60.

Conclusions

Patients discharged from the ED with TNA symptoms faced a higher risk of ischemic stroke than patients with renal colic, but the magnitude of stroke risk was low, particularly compared to TIA.

Clinical Information Systems Integration in New York City's First Mobile Stroke Unit

BACKGROUND

Mobile stroke units (MSUs) reduce time to thrombolytic therapy in acute ischemic stroke. These units are widely used, but the clinical information systems underlying MSU operations are understudied.

OBJECTIVE

The first MSU on the East Coast of the United States was established at New York Presbyterian Hospital (NYP) in October 2016. We describe our program's 7-month pilot, focusing on the integration of our hospital's clinical information systems into our MSU to support patient care and research efforts.

METHODS

NYP's MSU was staffed by two paramedics, one radiology technologist, and a vascular neurologist. The unit was equipped with four laptop computers and networking infrastructure enabling all staff to access the hospital intranet and clinical applications during operating hours. A telephone-based registration procedure registered patients from the field into our admit/discharge/transfer system, which interfaced with the institutional electronic health record (EHR). We developed and implemented a computerized physician order entry set in our EHR with prefilled values to permit quick ordering of medications, imaging, and laboratory testing. We also developed and implemented a structured clinician note to facilitate care documentation and clinical data extraction.

RESULTS

Our MSU began operating on October 3, 2016. As of April 27, 2017, the MSU transported 49 patients, of whom 16 received tissue plasminogen activator (t-PA). Zero technical problems impacting patient care were reported around registration, order entry, or intranet access. Two onboard network failures occurred, resulting in computed tomography scanner malfunctions, although no patients became ineligible for time-sensitive treatment as a result. Thirteen (26.5%) clinical notes contained at least one incomplete time field.

CONCLUSION

The main technical challenges encountered during the integration of our hospital's clinical information systems into our MSU were onboard network failures and incomplete clinical documentation. Future studies are necessary to determine whether such integrative efforts improve MSU care quality, and which enhancements to information systems will optimize clinical care and research efforts.

Modeling the Impact of Interhospital Transfer Network Design on Stroke Outcomes in a Large City

BACKGROUND AND PURPOSE

We sought to model the effects of interhospital transfer network design on endovascular therapy eligibility and clinical outcomes of stroke because of large-vessel occlusion for the residents of a large city.

METHODS

We modeled 3 transfer network designs for New York City. In model A, patients were transferred from spoke hospitals to the closest hub hospitals with endovascular capabilities irrespective of hospital affiliation. In model B, which was considered the base case, patients were transferred to the closest affiliated hub hospitals. In model C, patients were transferred to the closest affiliated hospitals, and transfer times were adjusted to reflect full implementation of streamlined transfer protocols. Using Monte Carlo methods, we simulated the distributions of endovascular therapy eligibility and good functional outcomes (modified Rankin Scale score, 0-2) in these models.

RESULTS

In our models, 200 patients (interquartile range [IQR], 168-227) with a stroke amenable to endovascular therapy present to New York City spoke hospitals each year. Transferring patients to the closest hub hospital irrespective of affiliation (model A) resulted in 4 (IQR, 1-9) additional patients being eligible for endovascular therapy and an additional 1 (IQR, 0-2) patient achieving functional independence. Transferring patients only to affiliated hospitals while simulating full implementation of streamlined transfer protocols (model C) resulted in 17 (IQR, 3-41) additional patients being eligible for endovascular therapy and 3 (IQR, 1-8) additional patients achieving functional independence.

CONCLUSIONS

Optimizing acute stroke transfer networks resulted in clinically small changes in population-level stroke outcomes in a dense, urban area.

Abstract WP323: Association between Demographic Characteristics and Hospital Admission in Patients Presenting to the Emergency Department for Transient Neurological Attack

Introduction: Significant demographic differences in the management of ischemic stroke and transient ischemic attack exist in the United States. Transient neurological attack (TNA) is a common neurological diagnosis that can result from cerebral ischemia, and is associated with recurrent stroke. Demographic factors may be associated with differences in admission rates for patients that present to the emergency department (ED) with a diagnosis of TNA.

Methods: In a population-based, retrospective, administrative claims-based cohort study, we identified patients who presented to a non-federal ED in Florida from 2005 through 2013 with a complaint consistent with TNA, which was defined as a poorly-localized, non-specific neurological symptom. Our predictor variables were race (white vs. non-white) and sex. Our outcome variable was admission to the hospital. We used multiple logistic regressions to characterize the relationship between the predictor variables and our chosen outcome while adjusting for age, insurance status, income, and vascular risk factors.

Results: We identified 1,231,046 patients presenting to the ED with TNA. Female patients in this cohort were less often white, and had fewer vascular comorbidities than men, including alcohol abuse. Non-white patients were younger, more often had Medicaid or no insurance, less often had atrial fibrillation, coronary heart disease or alcohol abuse, and more commonly had diabetes. Among all patients, 22,300 (1.8%) were admitted. After adjustment for age, insurance status, income, and vascular comorbidities, we found lower odds of hospital admission in female patients (odds ratio [OR], 0.69; 95% confidence interval [CI]; 0.67-0.70) and non-white patients (OR, 0.65; 95% CI, 0.63-0.67).

Conclusions: Among patients presenting to the ED with TNA, female sex and race are associated with decreased odds of admission, even after adjusting for age, income, insurance status, and vascular risk factors. Further studies are warranted to reproduce these findings in other states, and to determine the public health impact of our results.

Abstract TMP72: Modeling the Impact of Interhospital Transfer Protocol Design on Mechanical Thrombectomy Eligibility and Outcomes in a Large Metropolitan Area

Introduction: The effect of mechanical thrombectomy (MT) on functional outcomes after acute ischemic stroke is time-dependent. Interhospital transfer (IHT) introduces delays between stroke onset and MT.

Methods: We created models of two IHT network designs in New York City involving 26 Department of Health designated stroke centers without MT capabilities (spokes) and 14 hospitals able to perform MT (hubs). In Model A, all patients were transferred from the initial hospital without MT capabilities to the closest hub irrespective of hospital affiliation. In Model B, all patients were transferred to the closest affiliated hub. We calculated the number of patients eligible for MT presenting to each spoke annually using publicly available data. With Google Traffic API software, we estimated travel times between spoke and hub hospitals under constant conditions that approximated ambulance travel. We determined the effect of transfer time on MT eligibility based on a reported 2.5% reduction in odds of MT per minute of travel delay beyond a minimum threshold. Rates of a good functional outcome (modified Rankin Scale score 0-2) were predicted based on MT trial data. Last, we calculated the efficiency advantage needed among affiliated hospitals (Model B) to offset increased travel times.

Results: In our models, 371 patients (interquartile range [IQR], 229-628) with a stroke amenable to MT present to New York City spoke hospitals without MT capability each year. The mean travel time to the closest hub was 15.9 (±5.7) minutes in Model A versus 23.0 (±9.5) minutes to the closest affiliated hub in Model B. Transferring patients to the closest hub irrespective of affiliation (Model A) resulted in 71 (IQR, 44-120) additional patients being eligible for MT upon arrival and thereby an additional 14 (IQR, 8-23) patients achieving functional independence per year. To attenuate the differences in outcomes between Model A and Model B, a 10.9-minute decrease was required in the combined door-in to door-out time at the spoke plus the door-in to MT-start time at the affiliated hub.

Conclusions: Optimizing IHT networks requires balancing the efficiency gains of transferring to affiliated hospitals with the travel delays resulting from bypassing nearby MT-capable centers.

Abstract TP283: Association Between Spanish Language and Emergency Medical Service Use in Ischemic Stroke Patients Treated with IV-tPA

Introduction: Use of emergency medical services (EMS) is associated with decreased door-to-needle time in acute ischemic stroke. While racial and ethnic disparities in EMS use are well documented, the role of patient language in EMS use has been understudied. We sought to characterize EMS use by patient language among IV-tPA treated patients at a single center with a large Spanish-speaking patient population.

Methods: We identified all patients who received IV-tPA over five years (7/2011-6/2016) at an academic medical center in New York City. Primary language, EMS use, pre-notification, and patient demographics were recorded from the EMR. We compared baseline characteristics, EMS use, and stroke pre-notification between English and Spanish-speaking patients. Logistic regression was used to measure the association between primary patient language and EMS use, adjusting for potential confounders.

Results: Over the study period, 391 patients received IV-tPA; 208 (53%) primarily spoke English and 174 (45%) primarily spoke Spanish. Nine patients (2%) spoke other languages and were excluded. Mean age (66 vs. 69, p=0.09), male sex (43% vs. 33%, p=0.05) and median NIHSS (7 vs. 6, p=0.12) did not differ between English and Spanish-speaking patients. Of the 380 (97%) patients with EMS data, EMS use was higher among Spanish-speaking patients (69% vs. 80%, p<0.01). Pre-notification did not differ by language (63% vs. 61%, p=0.8). In a multivariable model adjusting for age, sex, and initial NIHSS, Spanish speakers remained more likely to use EMS (OR 1.9, 95% CI 1.1-3.2, p=0.02).

Conclusion: Among patients treated with IV-tPA at an urban academic medical center, EMS usage was higher in Spanish-speakers compared to English-speakers. Although language is not an exact surrogate for ethnicity, these findings are in contrast to previously published work demonstrating low rates of EMS usage among Hispanics. Future studies should evaluate differences in EMS utilization according to primary language as well as ethnicity.

Abstract TP165: Associations Between Parkinson Disease and Stroke

Introduction: Cerebral ischemia and vascular risk factors are associated with the development of Alzheimer disease (AD). While Parkinson disease (PD) is also a common neurodegenerative condition, the relationship between ischemic stroke and PD remains unclear. Some evidence suggests a shared pathogenic pathway between both diseases.

Methods: We used inpatient and outpatient claims data from 2008-2014 in a 5% sample of Medicare beneficiaries ≥66 years of age. Our variables of interest were: 1) a hospital-based diagnosis of ischemic stroke and 2) an outpatient or hospital-based diagnosis of idiopathic PD. Previously validated ICD-9-CM code algorithms were used to identify all diagnoses. We used Cox proportional hazards modeling to characterize the relationship between ischemic stroke and PD, while adjusting for demographics and vascular risk factors. We assessed both the association between PD and subsequent stroke, as well as stroke and subsequent PD. In a separate but identically designed set of analyses, we characterized the relationship between ischemic stroke and AD as a point of comparison.

Results: Our analysis encompassed nearly 1.6 million patients with a mean age of 73(+/- 8) years, of whom 57% were female. The annual incidence of ischemic stroke was 1.75% (95% confidence interval [CI], 1.67-1.85%) after a diagnosis of PD versus 0.96% (95% CI, 0.96-0.97%) in those without PD (adjusted hazard ratio [aHR], 1.25; 95% CI, 1.19-1.32). In contrast, the annual incidence of ischemic stroke was 1.96% (95% CI, 1.89-2.03%) after a diagnosis of AD versus 0.96% (95% CI, 0.96-0.97%) in those without AD (aHR, 0.98; 95% CI, 0.95-1.02). The annual incidence of PD was 0.97% (95% CI, 0.92-1.03%) after ischemic stroke versus 0.39% (95% CI, 0.38-0.39%) in those without ischemic stroke (aHR, 1.62; 95% CI, 1.53-1.72). In contrast, the annual incidence of AD was 3.66% (95% CI, 3.56-3.78%) after a diagnosis of ischemic stroke versus 1.17% (95% CI, 1.16-1.17%) in those without ischemic stroke (aHR, 1.67; 95% CI, 1.61-1.72).

Conclusions: Among Medicare beneficiaries, the relationships between stroke and PD were similar to those between stroke and AD. As in AD, a link may exist between cerebrovascular disease and PD.

Abstract WP223: Ischemic Stroke After Emergency Department Discharge for Symptoms of Transient Neurological Attack

Introduction: Compared to transient ischemic attack (TIA), little is known about the risk of ischemic stroke after the nonspecific symptoms of a transient neurological attack (TNA).

Methods: Using administrative claims data, we identified patients discharged from emergency departments (ED) in New York State between 2006 and 2012 with a primary discharge diagnosis of a TNA symptom, defined as in prior work as altered mental status, generalized weakness, and sensory changes. The primary outcome of ischemic stroke was identified using validated ICD-9-CM diagnosis codes. We used Kaplan-Meier survival statistics to calculate cumulative rates, and Cox regression to compare stroke risk after TNA versus after TIA (positive control) or renal colic (negative control) while adjusting for demographics and vascular risk factors. We performed subgroup analyses stratified by age. In sensitivity analyses, TNA was limited to cases of altered mental status or sensory changes, as these were more commonly associated with stroke in prior work, or limited to discharges without neuroimaging, to assess whether limited evaluation was associated with increased risk.

Results: Of 499,369 patients diagnosed with a TNA symptom and discharged from the ED, 7,756 were hospitalized for ischemic stroke over 4.7 (±1.9) years. At 90 days, the cumulative stroke rate was 0.29% (95% confidence interval [CI], 0.28-0.31%) after TNA symptoms versus 2.08% (95% CI, 1.89-2.28%) after TIA and 0.03% (95% CI, 0.02-0.04%) after renal colic. The hazard of stroke was higher after TNA than after renal colic (hazard ratio [HR], 2.13; 95% CI, 1.90-2.40). However, the risk was lower than after TIA (HR, 0.47; 95% CI, 0.44-0.50). Compared to TIA, TNA was less strongly associated with stroke among patients under 60 years of age (HR, 0.22; 95% CI, 0.19-0.25) than in those over 60 years of age (HR, 0.50; 95% CI, 0.47-0.53) ( P <0.001 for interaction). Our results were unchanged in sensitivity analyses limiting TNA diagnoses to patients with altered mental status or sensory changes or to those who did not undergo neuroimaging.

Conclusions: Patients discharged from the ED with TNA symptoms faced a higher risk of ischemic stroke than low risk controls, but the magnitude of stroke risk was low, particularly in comparison to TIA.

Abstract WP315: An Electronic Health Record Phenotype of Ischemic Stroke Using Non-Claims Clinical Data and Machine Learning

Introduction: Real-time identification of patients with acute ischemic stroke (AIS) in the electronic health record (EHR) can enhance care delivery systems, clinical decision support, and research subject recruitment. EHR data that is accessible during a patient’s admission may be used to identify patients with AIS, but established methods for characterizing which data to use have not yet been determined.

Hypotheses: 1. An EHR “phenotype” of AIS can be identified using clinical EHR data. 2. Machine learning can identify the AIS phenotype using similar inputs with greater accuracy than clinician-specified identification algorithms.

Methods: Two stroke neurologists selected generalizable AIS-related clinical data points from the Columbia University Medical Center EHR (clinical laboratory results and medication, imaging, and stroke service list orders) to identify the AIS phenotype, and determined pre-specified priority logic based on institutional practice patterns. Separately, a regularized logistic regression (RLR) model was applied to all available neurology-related order sets and clinical laboratory inputs. The classification accuracy of the two algorithms was compared using a “gold standard” data set, consisting of our institution’s ischemic stroke registry from January 1 st , 2015 to March 31 st , 2016. Negative controls were selected from all patients admitted to the neurology service at our institution during the same time period.

Results: Our data contained 482 patients with AIS and 3,628 negative controls. The clinician-specified identification algorithm identified the AIS phenotype with sensitivity of 90.6%, specificity of 50.4%, and positive predictive value (PPV) of 93.5%. In comparison, the RLR-based algorithm had a sensitivity of 96.3%, specificity of 52.2%, and PPV of 93.8%.

Conclusions: We determined an AIS phenotype that could be identified using clinical, non-claims data that is available during a patient’s admission, and used machine learning to optimize the classifying ability. While specificity is low, the high sensitivity may allow use for screening and clinical decision support. Further studies are needed to externally validate these findings and optimize algorithm specificity.

External Validation of the Cincinnati Prehospital Stroke Severity Scale

BACKGROUND

The Cincinnati Prehospital Stroke Severity Scale (CPSSS) was recently developed to predict large-vessel occlusions (LVOs) in patients with acute ischemic stroke (AIS). In its derivation study, which consisted of patients enrolled in thrombolysis and endovascular therapy trials, the CPSSS had excellent discriminatory performance. We sought to externally validate the CPSSS in an independent cohort.

METHODS

Using our institution's prospective stroke registry, we calculated CPSSS scores for all patients diagnosed with AIS at Weill Cornell Medical Center in 2013 and 2014. The primary outcome was presence of LVO and the secondary outcome was a National Institutes of Health Stroke Scale (NIHSS) score of 15 or higher. Harrell's c-statistic was calculated to determine the CPSSS score's discriminatory performance. Using the previously defined cut-point of 2 or higher (range 0-4), we evaluated the test properties of the CPSSS for predicting study outcomes.

RESULTS

Among 751 patients with AIS, 664 had vessel imaging and were included in the final analysis. Of these patients, 80 (14.2%) had LVOs and 117 (17.6%) had an NIHSS score of 15 or higher. The median CPSSS score was 0 (interquartile range 0-1) and 133 patients (20%) had scores of 2 or higher. c-statistic was .85 (95% confidence interval [CI] .81-.90) for predicting LVO and .94 (95% CI .92-.97) for predicting an NIHSS score of 15 or higher. Using a cut-point of 2 or higher, the CPSSS was 70.0% sensitive and 86.8% specific for predicting LVO, and 87.2% sensitive and 94.3% specific for predicting an NIHSS score of 15 or higher.

CONCLUSIONS

In a cohort of patients with AIS treated at a tertiary-care stroke center, the CPSSS had reasonable sensitivity and specificity for predicting LVO and severe stroke. Future studies should aim to prospectively validate the score in emergency responders.

Abstract WP200: Post-operative Infection Does not Increase Risk of Post-operative Stroke: Analysis From a Nationwide Quality Initiative Program

Introduction: Infection has been described as a trigger for acute ischemic stroke, but the relationship between postoperative infection and the risk of postoperative stroke is unclear. We investigated the association between postoperative infection and stroke using the American College of Surgeons National Surgical Quality Initiative Program (NSQIP) database.

Hypothesis: Postoperative infection is associated with an increased risk of postoperative stroke.

Methods: We used the NSQIP database to identify all patients who underwent surgery between the years of 2000 and 2010 and developed a postoperative stroke within 30 days of surgery. The group was further stratified according to the presence of infection preceding stroke. Using a logistic regression model adjusted for age, race, sex, medical comorbidities, surgical type, and dichotomized functional status, we compared the risk of stroke in patients with and without preceding infections, and investigated the risk of infection following stroke.

Results: 729,886 surgical patients were identified, of whom 2,703 (0.3%) developed postoperative stroke. 848 (0.12%) patients developed both postoperative stroke and infection. Among patients who had postoperative stroke, 100 (3.7%) had developed an infection prior to developing a stroke. Patients with infection prior to stroke had a lower risk of stroke than patients who did not develop infection prior to stroke (adjusted odds ratio [OR] 0.25, 95%CI 0.20-0.32). 748 patients (0.1%) developed an infection after having a postoperative stroke. These patients had a higher risk of infection (incidence rate ratio 2.76, 95%CI 2.57-2.97) and a higher odds of infection (adjusted odds ratio [OR] 3.47, 95%CI 3.18-3.78) than patients who did not have a stroke.

Conclusions: We found that the presence of a preceding infection was associated with a low risk of postoperative stroke in a large surgical inpatient sample. Although the total number of strokes may have been under-reported, these results conflict with other studies that report that infection is a trigger for ischemic stroke. Further analyses using more granular data are needed to investigate the relationship between postoperative infection and the risk of postoperative stroke.

Abstract 109: The Long-Term Risk of Seizures After Stroke

Introduction: Few data exist on the long-term risk of seizures after stroke.

Hypothesis: Stroke is associated with a similar long-term risk of seizures as compared with traumatic brain injury (TBI), a well-established long-term seizure risk factor.

Methods: Using administrative claims data on all acute care hospitalizations and emergency department (ED) visits at nonfederal facilities in California, Florida, and New York from 2005-2012, we identified patients at the time of a first documented stroke. Stroke was comprised of ischemic stroke, intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH), as defined by previously validated ICD-9-CM codes. As a control group, we identified patients at the time of a first documented TBI. The primary outcome was an ED visit or hospitalization with a discharge diagnosis of seizure. In sensitivity analyses, we limited the outcome to primary discharge diagnoses of seizure or diagnoses of status epilepticus. Survival statistics and Cox proportional hazards analysis was used to compare the rates and hazard of seizures between groups while adjusting for demographic characteristics and Elixhauser comorbidities.

Results: We identified 568,659 patients with stroke and 270,796 patients with TBI. During 2.5 (±2.1) years of follow-up, the cumulative risk of a seizure was 37.6% (95% confidence interval [CI], 37.3-37.8%) in patients with stroke and 29.9% (95% CI, 29.5-30.0%) in patients with TBI. After adjustment for demographic characteristics and comorbidities, stroke remained associated with a slightly higher hazard of seizures when compared with the risk after TBI (hazard ratio [HR], 1.12; 95% CI, 1.11-1.13). This finding was unchanged in sensitivity analyses of only primary discharge diagnoses of seizure or only status epilepticus cases. In subgroup analyses, the cumulative rate of any seizure was 26.2% (95% CI, 25.6-26.9%) after SAH, 33.6% (95% CI, 33.4-33.7%) after ischemic stroke, and 35.0% (95% CI, 34.5-35.4%) after ICH.

Conclusions: We found that a substantial proportion of patients with stroke develop a seizure. The long-term risk of seizure after stroke appears similar to that after TBI, which is widely recognized as a strong long-term seizure risk factor.

Abstract TP177: Preoperative Functional Status and Type of Surgery Influences Postoperative Stroke Risk: analysis from the Nationwide Surgical Quality Initiative Program

Introduction: Post-operative stroke (POS) is associated with vascular and cardiac surgery, but this finding has mainly been reported among populations receiving vascular and cardiac procedures. We investigated the association between type of surgery and risk of POS in a large, generalizable inpatient cohort from the American College of Surgeons National Surgical Quality Initiative Program (NSQIP) database.

Hypothesis: Cardiac and vascular procedures are associated with an increased risk of POS.

Methods: We identified patients that underwent surgery between the years of 2000 and 2010. Our primary outcome was POS within 30 days of surgery. Using a hierarchical model adjusted for age, race, sex, medical comorbidities and dichotomized functional status, we assessed for clustering between type of surgery and POS. We then determined risk factors for POS while adjusting for clustering. Each surgical type was compared against all other surgical types.

Results: We identified 729,886 patients, of whom 2,703 (0.3%) developed POS. In the hierarchical analysis, cardiac surgery (incidence rate ratio (IRR) 6.38, 95%CI 5.37-7.55), vascular surgery (IRR 4.41, 95%CI 4.08-4.76), and neurosurgery (IRR 2.05, 95%CI 1.69-2.48) were associated with increased risk of POS. The only patient-level factor associated with surgery type was poor preoperative functional status. Accounting for clustering, patients with poor pre-operative functional status (OR 4.11, 95%CI 3.60-4.69), history of stroke (OR 2.35 95%CI 2.06-2.69), history of transient ischemic attack (OR 2.49 95%CI 2.19-2.83), active smoking (OR 1.20, 95%CI 1.08-1.32), and COPD (OR 1.39 95%CI 1.21-1.59) were at higher risk of POS. There was no interaction between preoperative functional status and type of surgery.

Conclusions: In a large cohort of surgical inpatients, we found that the risk of POS was significantly associated with cardiac, vascular, and neurosurgical procedures. Certain patient populations, such as those with a dependent pre-operative functional status, may be at a higher risk of POS and may be more likely to undergo cardiac, vascular, or neurosurgical procedures. Further studies are needed to elucidate the relationship between pre-surgical functional status and type of surgery.

Abstract 134: Postoperative Atrial Fibrillation and the Short-term Risk of Ischemic Stroke

Introduction: We have recently shown an association between new-onset postoperative atrial fibrillation (AF) and the long-term risk of ischemic stroke after noncardiac surgery. However, the degree of stroke risk with AF in the postoperative setting remains unclear.

Hypothesis: New-onset postoperative AF is associated with an increased risk of ischemic stroke in the 30 days after surgery.

Methods: Administrative claims data from all discharges at nonfederal acute care hospitals in California, New York, and Florida were used to identify patients who underwent inpatient surgery in 2007-2012. Our predictor variable was new-onset AF, defined using validated ICD-9-CM diagnosis and present-on-admission codes. Patients with prior stroke or AF were excluded. The outcome was postoperative stroke, defined as ischemic stroke occurring within 30 days of surgery. Cox proportional hazards analysis was used to examine the association between postoperative AF and stroke while adjusting for demographics and vascular risk factors. In sensitivity analyses, we limited the outcome to stroke occurring after discharge but within 30 days of surgery. Cardiac and noncardiac surgeries were analyzed separately.

Results: Among 7,139,472 patients with inpatient surgery, 102,831 (1.44%) developed postoperative AF and 17,117 (0.24%) developed a postoperative stroke. After noncardiac surgery, the 30-day cumulative risk of stroke was significantly higher in those with postoperative AF (2.07%) than those without AF (0.18%). This difference was significant after adjustment for demographics and potential confounders (hazard ratio [HR], 4.3; 95% CI, 4.1-4.6). After cardiac surgery, postoperative AF was also associated with an increased cumulative risk of stroke (2.27%) compared to those without AF (1.17%), but the strength of association (HR, 1.8; 95% CI, 1.6-1.9) was less marked than in the setting of noncardiac surgery ( P value for interaction <0.001). Postoperative AF was associated with stroke occurring after discharge and within 30 days of noncardiac surgery (HR, 1.9; 95% CI, 1.6-2.3), but not cardiac surgery (HR, 1.1; 95% CI, 0.9-1.3).

Conclusions: Postoperative AF is associated with an increased short-term risk of stroke after noncardiac surgery.

Demographic Differences in Catheter Ablation After Hospital Presentation With Symptomatic Atrial Fibrillation

Background

Catheter ablation is increasingly used for rhythm control in symptomatic atrial fibrillation (AF), but the demographic characteristics of patients undergoing this procedure are unclear.

Methods and Results

We used data on all admissions at nonfederal acute care hospitals in California, Florida, and New York to identify patients discharged with a primary diagnosis of AF between 2006 and 2011. Our primary outcome was readmission for catheter ablation of AF, identified using validated International Classification of Diseases, Ninth Revision, Clinical Modification procedure codes. Cox regression models were used to assess relationships between demographic characteristics and catheter ablation, adjusting for Elixhauser comorbidities. We identified 397 612 eligible patients. Of these, 16 717 (4.20%, 95% CI 0.41 to 0.43) underwent ablation. These patients were significantly younger, more often male, more often white, and more often privately insured, with higher household incomes and lower rates of medical comorbidity. In Cox regression models, the likelihood of ablation was lower in women than men (hazard ratio [HR] 0.83; 95% CI 0.80 to 0.86) despite higher rates of AF-related rehospitalization (HR 1.23; 95% CI 1.21 to 1.24). Compared to whites, the likelihood of ablation was lower in Hispanics (HR 0.60; 95% CI 0.56 to 0.64) and blacks (HR 0.68; 95% CI 0.64 to 0.73), even though blacks had only a slightly lower likelihood of AF-related rehospitalization (HR 0.97; 95% CI 0.94 to 0.99) and a higher likelihood of all-cause hospitalization (HR 1.38; 95% CI 1.37 to 1.39). Essentially the same pattern existed in Hispanics.

Conclusions

We found differences in use of catheter ablation for symptomatic AF according to sex and race despite adjustment for available data on demographic characteristics and medical comorbidities.