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For over two decades, telestroke has been utilized as a means for improving acute access to a stroke specialist when this expertise is otherwise unavailable. During this time, telestroke use has increased and improvements in care metrics have been widely reported. Several telestroke model variations are utilized; each has different workflow implications. A successful telestroke system should include adequate protocols and training, equipment, documentation system, and tracking of quality metrics. Upfront costs of needed technology and devices, credentialing hurdles, and limited reimbursement are all reported barriers to the utilization of telestroke. Emphasis on safety measures during the COVID-19 pandemic resulted in the dramatic upscaling of telehealth utilization, although overall stroke volumes declined in many areas in the early phases of the pandemic. Going forward, continued reduction in cost of required devices and broadband connections, increased use of automated and advanced analytical software, and a universal licensing and credentialing system are needed to continue the expansion of telestroke use.

Sex-specific differences in ischemic stroke outcomes are prevalent. We sought to investigate sex differences in the determinants of reperfusion and functional outcomes after endovascular thrombectomy (EVT) for emergent large vessel occlusion ischemic stroke (ELVO). Patients presenting to a single referral center with an anterior circulation ELVO that underwent EVT from 2011 to 2019 were included in this retrospective analysis. Sex differences in history, presentation, adequate reperfusion (TICI 2b-3), and 90-day good outcome [delta modified Rankin Scale (mRS) ≤ 2 from pre-stroke] were examined. Multivariable logistic regression analyses were performed to assess sex-specific associations with outcomes. Three hundred and eighty-one consecutive ELVO patients were identified. Women (N = 193) were older (75 vs 64 years, p

ObjectiveTo determine whether providing teleneurology (TN) consultations aiding in determination of death by neurologic criteria (DNC) to a bedside intensivist is feasible and whether timely access and expert input increase the quality of the DNC examination and identification of potential organ donors, we reviewed retrospective data related to outcomes of such consultations.MethodsBetween November 2017 and March 2019, TN consults were requested for sequential comatose patients in the intensive care unit (ICU). We recorded patients' demographic information, causes leading to coma or suspected DNC, and the results of TN consultations. We obtained data on the number of referrals to the organ bank and number of organ donors.ResultsNinety-nine consults were performed with a median time from request to start of the consult of 20.2 minutes (interquartile range 5.4–65.3 minutes). Eighty consults were requested for determination of prognosis, whereas 19 consults were requested for supervision of the DNC examination. In 1 of 80 (1.2%) prognostication consults, the patient was determined by the neurologist to require assessment of DNC and was found to meet DNC criteria; determination of DNC occurred in 11 of the 19 (57.9%) consultations for a supervised DNC examination. In a comparison of the pre-TN (94 months) and post-TN (17 months) periods, there was 2.56-fold increase in the proportion of patients meeting DNC criteria who were medically suitable for donation (pre-TN 8.9% vs post-TN 21.1%, p = 0.02) and a 2.12-fold increase in the proportion of donors (pre-TN 6.14% vs post-TN 13.1%, p = 0.14).ConclusionsIt is feasible to perform TN consultations for patients with severe neurologic damage and to allow expert supervision for DNC examination. Having a teleneurologist as part of the ICU assessment team helped differentiate severe neurologic deficits from DNC and was associated with increase in organ donation.

Since approval by the United States Food and Drug Administration in 1996, alteplase utilization rates for acute ischemic stroke have increased. Despite its efficacy for improving stroke outcomes, however, the majority of ischemic stroke patients still do not receive alteplase. To address this issue, different methods for improving access to alteplase have been tested with varying degrees of success.This article gives an overview of the recent approaches pursued to improve access to alteplase for acute ischemic stroke patients. Utilization of stroke systems of care, quality metrics, and quality-improvement initiatives to improve alteplase treatment rates are discussed. The implementation of Telestroke networks to improve access and timely evaluation by a stroke specialist are also reviewed. Lastly, this review discusses the use of neuroimaging techniques to identify alteplase candidates in stroke of unknown symptom onset or beyond the 4.5-h treatment window.Expanding access to alteplase therapy for acute ischemic stroke is a multi-faceted approach. Specific considerations based on region, population, and health-care resources should be considered for each strategy. Neuroimaging approaches to identify alteplase-eligible patients beyond the 4.5-h treatment window are a recent development in acute stroke care that holds promise for increasing alteplase treatment rates.

Background Performance of existing atrial fibrillation (AF) risk prediction models in poststroke populations is unclear. We evaluated predictive utility of an AF risk model in patients with acute stroke and assessed performance of a fully refitted model. Methods and Results Within an academic hospital, we included patients aged 46 to 94 years discharged for acute ischemic stroke between 2003 and 2018. We estimated 5‐year predicted probabilities of AF using the Cohorts for Heart and Aging Research in Genomic Epidemiology for Atrial Fibrillation (CHARGE‐AF) model, by recalibrating CHARGE‐AF to the baseline risk of the sample, and by fully refitting a Cox proportional hazards model to the stroke sample (Re‐CHARGE‐AF) model. We compared discrimination and calibration between models and used 200 bootstrap samples for optimism‐adjusted measures. Among 551 patients with acute stroke, there were 70 incident AF events over 5 years (cumulative incidence, 15.2%; 95% CI, 10.6%–19.5%). Median predicted 5‐year risk from CHARGE‐AF was 4.8% (quartile 1–quartile 3, 2.0–12.6) and from Re‐CHARGE‐AF was 16.1% (quartile 1–quartile 3, 8.0–26.2). For CHARGE‐AF, discrimination was moderate (C statistic, 0.64; 95% CI, 0.57–0.70) and calibration was poor, underestimating AF risk (Greenwood‐Nam D’Agostino chi‐square, P P P =0.001) compared with CHARGE‐AF (C statistic, 0.74 [95% CI, 0.68–0.79]; optimism‐adjusted, 0.70 [95% CI, 0.65–0.75]) and was well calibrated (Greenwood‐Nam D’Agostino chi‐square, P =0.97). Conclusions Covariates from an established AF risk model enable accurate estimation of AF risk in a poststroke population after recalibration. A fully refitted model was required to account for varying baseline AF hazard and strength of associations between covariates and incident AF.

BackgroundElectronic health records (EHRs) promise to enable broad-ranging discovery with power exceeding that of conventional research cohort studies. However, research using EHR datasets may be subject to selection bias, which can be compounded by missing data, limiting the generalizability of derived insights.MethodsMass General Brigham (MGB) is a large New England-based healthcare network comprising seven tertiary care and community hospitals with associated outpatient practices. Within an MGB-based EHR warehouse of >3.5 million individuals with at least one ambulatory care visit, we approximated a community-based cohort study by selectively sampling individuals longitudinally attending primary care practices between 2001-2018 (n=520,868), which we named the Community Care Cohort Project (C3PO). We also utilized pre-trained deep natural language processing (NLP) models to recover vital signs (i.e., height, weight, and blood pressure) from unstructured notes in the EHR. We assessed the validity of C3PO by deploying established risk models including the Pooled Cohort Equations (PCE) and the Cohorts for Aging and Genomic Epidemiology Atrial Fibrillation (CHARGE-AF) score, and compared model performance in C3PO to that observed within typical EHR Convenience Samples which included all individuals from the same parent EHR with sufficient data to calculate each score but without a requirement for longitudinal primary care. All analyses were facilitated by the JEDI Extractive Data Infrastructure pipeline which we designed to efficiently aggregate EHR data within a unified framework conducive to regular updates.ResultsC3PO includes 520,868 individuals (mean age 48 years, 61% women, median follow-up 7.2 years, median primary care visits per individual 13). Estimated using reports, C3PO contains over 2.9 million electrocardiograms, 450,000 echocardiograms, 12,000 cardiac magnetic resonance images, and 75 million narrative notes. Using tabular data alone, 286,009 individuals (54.9%) had all vital signs available at baseline, which increased to 358,411 (68.8%) after NLP recovery (31% reduction in missingness). Among individuals with both NLP and tabular data available, NLP-extracted and tabular vital signs obtained on the same day were highly correlated (e.g., Pearson r range 0.95-0.99, pConclusionsIntentional sampling of individuals receiving regular ambulatory care and use of NLP to recover missing data have the potential to reduce bias in EHR research and maximize generalizability of insights.

Electronic health record (EHR) datasets are statistically powerful but are subject to ascertainment bias and missingness. Using the Mass General Brigham multi-institutional EHR, we approximated a community-based cohort by sampling patients receiving longitudinal primary care between 2001-2018 (Community Care Cohort Project [C3PO], n = 520,868). We utilized natural language processing (NLP) to recover vital signs from unstructured notes. We assessed the validity of C3PO by deploying established risk models for myocardial infarction/stroke and atrial fibrillation. We then compared C3PO to Convenience Samples including all individuals from the same EHR with complete data, but without a longitudinal primary care requirement. NLP reduced the missingness of vital signs by 31%. NLP-recovered vital signs were highly correlated with values derived from structured fields (Pearson r range 0.95–0.99). Atrial fibrillation and myocardial infarction/stroke incidence were lower and risk models were better calibrated in C3PO as opposed to the Convenience Samples (calibration error range for myocardial infarction/stroke: 0.012–0.030 in C3PO vs. 0.028–0.046 in Convenience Samples; calibration error for atrial fibrillation 0.028 in C3PO vs. 0.036 in Convenience Samples). Sampling patients receiving regular primary care and using NLP to recover missing data may reduce bias and maximize generalizability of EHR research.

Cervico-cranial arterial dissections are a distinct etiology of both ischemic and hemorrhagic neurovascular events. These dissections can involve the extracranial carotid or vertebral arteries, classified collectively as cervical artery dissections, or can be intracranial arterial dissections, and complications and management of each differ. The most recent evidence is reviewed in this publication. Significant heterogeneity regarding treatments of dissections exists among providers and with recent advances in endovascular approaches to neurovascular care, appreciating the latest evidence on the guidance of treatment has never been so challenging. Furthermore, recognizing the complications of cervico-cranial dissections and implementing appropriate therapies can have a significant impact on patient outcomes. Overall, limited randomized controlled data exists regarding the treatment of cervico-cranial dissections. Approach to management of these dissections and potential complications is largely based on observational studies and reported cases. The available evidence and strength vary depending on the case and complication.