Descriptive Analysis of Patients Receiving Outpatient eConsults for Neurological Disorders in the United States.

Introduction: Interprofessional consultations ("eConsults"), which facilitate asynchronous specialist consultations, remain understudied in neurological disorders. We aimed to describe the patient population receiving eConsult services for neurological disorders nationwide and to conduct a comparative analysis between rural and urban patients within this eConsult cohort. Methods: We analyzed a dataset of U.S. outpatient claims from employer-sponsored commercial and Medicare plans. Using standardized mean differences, we compared clinical and sociodemographic patient characteristics between urban and rural patients within the eConsult group. Results: We identified 1,374 patients who had an eConsult order for a neurological disorder. Overall eConsult volume increased by 548.5% between 2019 and 2021. A majority of the cohort were aged 65 years or older (23.7%), had an eConsult order in 2021 (52.4%), and live in an urban area (90.4%). The primary diagnosis for our cohort was likely to be a sleep-wake disorder (21.9%), cerebrovascular disease (14.3%), neurological sign or symptom (14.2%), or headache (13.7%). In the secondary analysis, rural eConsult patients exhibited higher rates of primary diagnoses for traumatic brain injury, neuroophthalmic disorders, or neuropathy than their urban counterparts. Discussion: In this national sample of commercially insured patients, the utilization of eConsults for neurological conditions increased nationwide since 2019, especially for patients living in rural areas.

Utilization of Remote Patient Monitoring for Neurological Disorders: A Nationwide Analysis of Administrative Claims Data.

Introduction: The use of remote patient monitoring (RPM) services for neurological disorders remains understudied, particularly in the context of newer billing codes introduced before the COVID-19 pandemic. Methods: This retrospective cohort study utilized data from commercial and Medicare employer-sponsored administrative claims between January 1, 2019, to December 31, 2021. The study population included all patients with at least one qualifying RPM-related Current Procedural Terminology (CPT) code for a neurological disorder, separated into first-generation (CPT 99091) codes and second-generation (CPT 99453, 99454, 99457, 99458) code cohorts. We compared patient and encounter characteristics between both cohorts. Results: We identified 27,756 encounters attributable to 11,326 patients who received RPM services for neurological disorders, of whom 5,785 (51.1%) received RPM via second-generation billing codes, 3,941 (34.8%) were female, 6,712 (59.3%) were between 45 and 64 years old, and 10,488 (92.6%) had a primary diagnosis of sleep-wake disorder. The second-generation cohort was significantly more likely to be female (41.5% vs. 27.8%, p < 0.001), be of age 65 or older (15.7% vs. 7.1%, p < 0.001), and reside in urban areas (93.4% vs. 87.6%, p < 0.001) than the first-generation cohort. Patients in the second-generation cohort were more likely to receive RPM in office settings (86.3% vs. 62.5%, p < 0.001), by physicians (77.0% vs. 40.3%, p < 0.001), and less likely for sleep-wake disorders (87.9% vs. 97.5%, p < 0.001) than the first-generation cohort. Patients who received RPM from physicians were most often evaluated by pulmonologists (31.4%). Discussion: In this commercially insured patient population receiving RPM for neurological disorders, we found that sleep-wake disorders and non-neurologists were over-represented.

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.

A retrospective cohort study of clinical factors, visit patterns, and demographic factors associated with use of remote communications in patients with headache.

OBJECTIVE: To identify the characteristics associated with high utilization of remote communications (RCs) in patients with headache. BACKGROUND: Patients with headache frequently communicate with their providers using secure portal messaging and telephone calls. However, clinical and demographic factors as well as visit patterns associated with RC utilization remain poorly characterized. METHODS: We retrospectively analyzed data from patients with headache who were evaluated in the ambulatory neurology faculty practice at the Icahn School of Medicine at Mount Sinai in New York between January 1 and June 30, 2019. We extracted clinical and demographic characteristics, total office visits, secure MyChart portal messages, and telephone encounters from our institutional data warehouse. We defined high RC and MyChart utilization as the top tertile of RC and MyChart message volume, respectively, and assessed the relationship between patient characteristics and high RC (primary outcome), as well as high MyChart utilization (secondary outcome). We characterized the relationship between clinicodemographic characteristics and the ratio of MyChart messages to total RCs (secondary outcome). RESULTS: We identified 1390 patients, of whom 477 (34.3%) were high RC utilizers and 321 (23.1%) were high MyChart utilizers. High RC utilizers generated 3306/3921 (84.3%) RCs. The presence of chronic headache (aOR 2.31, 95% CI 1.75-3.03, p < 0.0001), cluster headache (aOR 18.3, 95% CI 5.0-71.7, p = 0.001), and migraine (aOR 3.82, 95% CI 1.93-9.3, p = 0.011) was associated with high RC utilization. Patients ≥65 years of age were less likely to engage in MyChart messaging as a proportion of RC (191/680, 28.1%) compared with patients 18-30 years of age (243/620, 39.2%, p = 0.049) and 30-64 years of age (1172/2721, 43.1%, p < 0.0001). CONCLUSIONS: A minority of patients with headache (477/1390; 34.3%) generated the majority (3306/3921; 84.3%) of RCs. Our findings should be validated in external patient cohorts with the objective of developing strategies to optimize RC utilization.

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.

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.

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.

Safety and Feasibility of a Rapid Outpatient Management Strategy for Transient Ischemic Attack and Minor Stroke: The Rapid Access Vascular Evaluation-Neurology (RAVEN) Approach.

STUDY OBJECTIVE: Although most transient ischemic attack and minor stroke patients in US emergency departments (EDs) are admitted, experience in other countries suggests that timely outpatient evaluation of transient ischemic attack and minor stroke can be safe. We assess the feasibility and safety of a rapid outpatient stroke clinic for transient ischemic attack and minor stroke: Rapid Access Vascular Evaluation-Neurology (RAVEN). METHODS: Transient ischemic attack and minor stroke patients presenting to the ED with a National Institutes of Health Stroke Scale score of 5 or less and nondisabling deficit were assessed for potential discharge to RAVEN with a protocol incorporating social and medical criteria. Outpatient evaluation by a vascular neurologist, including vessel imaging, was performed within 24 hours at the RAVEN clinic. Participants were evaluated for compliance with clinic attendance and 90-day recurrent transient ischemic attack and minor stroke and hospitalization rates. RESULTS: Between December 2016 and June 2018, 162 transient ischemic attack and minor stroke patients were discharged to RAVEN. One hundred fifty-four patients (95.1%) appeared as scheduled and 101 (66%) had a final diagnosis of transient ischemic attack and minor stroke. Two patients (1.3%) required hospitalization (one for worsening symptoms and another for intracranial arterial stenosis caused by zoster) at RAVEN evaluation. Among the 101 patients with confirmed transient ischemic attack and minor stroke, 18 (19.1%) had returned to an ED or been admitted at 90 days. Five were noted to have had recurrent neurologic symptoms diagnosed as transient ischemic attack (4.9%), whereas one had a recurrent stroke (0.9%). No individuals with transient ischemic attack and minor stroke died, and none received thrombolytics or thrombectomy, during the interval period. These 90-day outcomes were similar to historical published data on transient ischemic attack and minor stroke. CONCLUSION: Rapid outpatient management appears a feasible and safe strategy for transient ischemic attack and minor stroke patients evaluated in the ED, with recurrent stroke and transient ischemic attack rates comparable to historical published data.

Population-Based Assessment of the Long-Term Risk of Seizures in Survivors of Stroke.

BACKGROUND AND PURPOSE: We sought to determine the long-term risk of seizures after stroke according to age, sex, race, and stroke subtype. METHODS: We performed a retrospective cohort study using administrative claims from 2 complementary patient data sets. First, we analyzed data from all emergency department visits and hospitalizations in California, Florida, and New York from 2005 to 2013. Second, we evaluated inpatient and outpatient claims from a nationally representative 5% random sample of Medicare beneficiaries. Our cohort consisted of all adults at the time of acute stroke hospitalization without a prior history of seizures. Our outcome was seizure occurring after hospital discharge for stroke. Poisson regression and demographic data were used to calculate age-, sex-, and race-standardized incidence rate ratios (IRR). RESULTS: Among 777 276 patients in the multistate cohort, the annual incidence of seizures was 1.68% (95% confidence interval [CI], 1.67%-1.70%) after stroke versus 0.15% (95% CI, 0.15%-0.15%) among the general population (IRR, 7.3; 95% CI, 7.3-7.4). By 8 years, the cumulative rate of any emergency department visit or hospitalization for seizure was 9.27% (95% CI, 9.16%-9.38%) after stroke versus 1.21% (95% CI, 1.21%-1.22%) in the general population. Stroke was more strongly associated with a subsequent seizure among patients <65 years of age (IRR, 12.0; 95% CI, 11.9-12.2) than in patients ≥65 years of age (IRR, 5.5; 95% CI, 5.4-5.5) and in the multistate analysis, the association between stroke and seizure was stronger among nonwhite patients (IRR, 11.0; 95% CI, 10.8-11.2) than among white patients (IRR, 7.3; 95% CI, 7.2-7.4). Risks were especially elevated after intracerebral hemorrhage (IRR, 13.3; 95% CI, 13.0-13.6) and subarachnoid hemorrhage (IRR, 13.2; 95% CI, 12.8-13.7). Our study of Medicare beneficiaries confirmed these findings. CONCLUSIONS: Almost 10% of patients with stroke will develop seizures within a decade. Hemorrhagic stroke, nonwhite race, and younger age seem to confer the greatest risk of developing seizures.

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.

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.

Can I Send This Patient with Stroke Home? Strategies Managing Transient Ischemic Attack and Minor Stroke in the Emergency Department.

BACKGROUND: While transient ischemic attack and minor stroke (TIAMS) are common conditions evaluated in the emergency department (ED), there is controversy regarding the most effective and efficient strategies for managing them in the ED. Some patients are discharged after evaluation in the ED and cared for in the outpatient setting, while others remain in an observation unit without being admitted or discharged, and others experience prolonged and potentially costly inpatient admissions. OBJECTIVE OF THE REVIEW: The goal of this clinical review was to summarize and present recommendations regarding the disposition of TIAMS patients in the ED (e.g., admission vs. discharge). DISCUSSION: An estimated 250,000 to 300,000 TIA events occur each year in the United States, with an estimated near-term risk of subsequent stroke ranging from 3.5% to 10% at 2 days, rising to 17% by 90 days. While popular and easy to use, reliance solely on risk-stratification tools, such as the ABCD2, should not be used to determine whether TIAMS patients can be discharged safely. Additional vascular imaging and advanced brain imaging may improve prediction of short-term neurologic risk. We also review various disposition strategies (e.g., inpatient vs. outpatient/ED observation units) with regard to their association with neurologic outcomes, such as 30-day or 90-day stroke recurrence or new stroke, in addition to other outcomes, such as hospital length of stay and health care costs. CONCLUSIONS: Discharge from the ED for rapid outpatient follow-up may be a safe and effective strategy for some forms of minor stroke without disabling deficit and TIA patients after careful evaluation and initial ED workup. Future research on such strategies has the potential to improve neurologic and overall patient outcomes and reduce hospital costs and ED length of stay.

Angiographic Blush after Mechanical Thrombectomy is Associated with Hemorrhagic Transformation of Ischemic Stroke.

BACKGROUND AND PURPOSE: Risk factors for hemorrhagic transformation of ischemic stroke after mechanical thrombectomy (MT) are not well established. We conducted a study to determine if prominent angiographic cerebral vascularity following recanalization with thrombectomy (angiographic blush) is associated with hemorrhagic transformation. METHODS: Using the Cornell AcutE Stroke Academic Registry, we identified stroke patients who had thrombectomy and achieved recanalization of anterior circulation large-vessel occlusion between 2012 and 2015. The exposure variable was presence of angiographic blush after recanalization, defined as capillary blush with or without early venous drainage. The primary outcome was volume of hemorrhagic transformation on brain imaging after thrombectomy, as determined by semiautomated volumetric analysis on computed tomography or magnetic resonance imaging among those adjudicated to have hemorrhagic conversion by neuroradiology investigators blinded to angiography results. Using a doubly robust estimator with propensity scores and outcome regression adjusting for demographics and known risk factors for hemorrhagic transformation, we evaluated whether angiographic blush after recanalization is associated with an increased volume of hemorrhagic transformation. RESULTS: Among 48 eligible patients, 31 (64.6%) had angiographic blush and 26 (54.2%) had radiographic hemorrhagic transformation (mean volume, 7.6 ml). Patients with angiographic blush averaged lower thrombolysis in cerebral infarction scores and more often received intravenous thrombolysis. In adjusted analysis, angiographic blush was associated with an increased volume of hemorrhagic transformation: mean volume, 10.3ml (95% CI, 3.7-16.9 ml) with blush versus 1.8ml (95% Confidence Interval (CII = Confidence Interval), 0.1-3.4 ml) without (P = .01). CONCLUSIONS: Presence of angiographic blush after MT was independently associated with the volume of hemorrhagic transformation.

Left Atrial Enlargement and Anticoagulation Status in Patients with Acute Ischemic Stroke and Atrial Fibrillation.

BACKGROUND: Despite anticoagulation therapy, ischemic stroke risk in atrial fibrillation (AF) remains substantial. We hypothesize that left atrial enlargement (LAE) is more prevalent in AF patients admitted with ischemic stroke who are therapeutic, as opposed to nontherapeutic, on anticoagulation. METHODS: We included consecutive patients with AF admitted with ischemic stroke between April 1, 2015, and December 31, 2016. Patients were divided into two groups based on whether they were therapeutic (warfarin with an international normalized ratio ≥ 2.0 or non-vitamin K oral anticoagulant with uninterrupted use in the prior 2 weeks) versus nontherapeutic on anticoagulation. Univariable and multivariable models were used to estimate associations between therapeutic anticoagulation and clinical factors, including CHADS2 score and LAE (none/mild versus moderate/severe). RESULTS: We identified 225 patients during the study period; 52 (23.1%) were therapeutic on anticoagulation. Patients therapeutic on anticoagulation were more likely to have a larger left atrial diameter in millimeters (45.6 ± 9.2 versus 42.3 ± 8.6, P = .032) and a higher CHADS2 score (2.9 ± 1.1 versus 2.4 ± 1.1, P = .03). After adjusting for the CHADS2 score, patients who had a stroke despite therapeutic anticoagulation were more likely to have moderate to severe LAE (odds ratio, 2.05; 95% confidence interval, 1.01-4.16). CONCLUSION: LAE is associated with anticoagulation failure in AF patients admitted with an ischemic stroke. This provides indirect evidence that LAE may portend failure of anticoagulation therapy in patients with AF; further studies are needed to delineate the significance of this association and improve stroke prevention strategies.

Biomarkers of Atrial Cardiopathy and Atrial Fibrillation Detection on Mobile Outpatient Continuous Telemetry After Embolic Stroke of Undetermined Source.

BACKGROUND: Biomarkers of atrial dysfunction or "cardiopathy" are associated with embolic stroke risk. However, it is unclear if this risk is mediated by undiagnosed paroxysmal atrial fibrillation or flutter (AF). We aim to determine whether atrial cardiopathy biomarkers predict AF on continuous heart-rhythm monitoring after embolic stroke of undetermined source (ESUS). METHODS: This was a single-center retrospective study including all patients with ESUS undergoing 30 days of ambulatory heart-rhythm monitoring to look for AF between January 1, 2013 and December 31, 2015. We reviewed medical records for clinical, radiographic, and cardiac variables. The primary outcome was a new diagnosis of AF detected during heart-rhythm monitoring. The primary predictors were atrial biomarkers: left atrial diameter on echocardiography, P-wave terminal force in electrocardiogram (ECG) lead V1, and P wave - R wave (PR) interval on ECG. A multiple logistic regression model was used to assess the relationship between atrial biomarkers and AF detection. RESULTS: Among 196 eligible patients, 23 (11.7%) were diagnosed with AF. In unadjusted analyses, patients with AF were older (72.4 years versus 61.4 years, P < .001) and had larger left atrial diameter (39.2 mm versus 35.7 mm, P = .03). In a multivariable model, the only predictor of AF was age ≥ 60 years (odds ratio, 3.0; 95% CI, 1.06-8.5; P = .04). CONCLUSION: Atrial biomarkers were weakly associated with AF after ESUS. This suggests that previously reported associations between these markers and stroke may reflect independent cardiac pathways leading to stroke. Prospective studies are needed to investigate these mechanisms.

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.

Teleneurology and Artificial Intelligence in Clinical Practice.

ABSTRACT: As teleheath becomes integrated into the practice of medicine, it is important to understand the benefits, limitations, and variety of applications. Telestroke was an early example of teleneurology that arose from a need for urgent access to neurologists for time-sensitive treatments for stroke. It made a scarce resource widely available via video conferencing technologies. Additionally, applications such as outpatient video visits, electronic consultation (e-consult), and wearable devices developed in neurology, as well. Telehealth dramatically increased during the COVID-19 pandemic when offices were closed and hospitals were overwhelmed; a multitude of both outpatient and inpatient programs developed and matured during this time. It is helpful to explore what has been learned regarding the quality of telehealth, disparities in care, and how artificial intelligence can interact with medical practices in the teleneurology context.

Implications of Large Language Models for Quality and Efficiency of Neurologic Care: Emerging Issues in Neurology.

Large language models (LLMs) are advanced artificial intelligence (AI) systems that excel in recognizing and generating human-like language, possibly serving as valuable tools for neurology-related information tasks. Although LLMs have shown remarkable potential in various areas, their performance in the dynamic environment of daily clinical practice remains uncertain. This article outlines multiple limitations and challenges of using LLMs in clinical settings that need to be addressed, including limited clinical reasoning, variable reliability and accuracy, reproducibility bias, self-serving bias, sponsorship bias, and potential for exacerbating health care disparities. These challenges are further compounded by practical business considerations and infrastructure requirements, including associated costs. To overcome these hurdles and harness the potential of LLMs effectively, this article includes considerations for health care organizations, researchers, and neurologists contemplating the use of LLMs in clinical practice. It is essential for health care organizations to cultivate a culture that welcomes AI solutions and aligns them seamlessly with health care operations. Clear objectives and business plans should guide the selection of AI solutions, ensuring they meet organizational needs and budget considerations. Engaging both clinical and nonclinical stakeholders can help secure necessary resources, foster trust, and ensure the long-term sustainability of AI implementations. Testing, validation, training, and ongoing monitoring are pivotal for successful integration. For neurologists, safeguarding patient data privacy is paramount. Seeking guidance from institutional information technology resources for informed, compliant decisions, and remaining vigilant against biases in LLM outputs are essential practices in responsible and unbiased utilization of AI tools. In research, obtaining institutional review board approval is crucial when dealing with patient data, even if deidentified, to ensure ethical use. Compliance with established guidelines like SPIRIT-AI, MI-CLAIM, and CONSORT-AI is necessary to maintain consistency and mitigate biases in AI research. In summary, the integration of LLMs into clinical neurology offers immense promise while presenting formidable challenges. Awareness of these considerations is vital for harnessing the potential of AI in neurologic care effectively and enhancing patient care quality and safety. The article serves as a guide for health care organizations, researchers, and neurologists navigating this transformative landscape.

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.