Background: To determine a pattern of symptoms and/or risk factors that distinguishes transient ischemic attack (TIA) from nonischemic causes of transient neurologic attacks (NI-TNA). Methods: We reviewed demographic, clinical, and hospital data on 100 consecutive patients with transient focal neurologic episode(s) lasting less than 24 h and in whom the initial diagnosis was TIA. After inpatient evaluation and review, final diagnoses were made by two stroke neurologists. Using stepwise multivariable logistic regression, we estimated odds ratios (OR) for independent predictors of NI-TNA. p < 0.05 was considered significant. Results: Of the 100 patients, 40 were confirmed to have TIA and 60 NI-TNA. Compared to TIA patients, those with NI-TNA were less likely to be male and white but more likely to have a history of prior unexplained TNA, gradual symptom onset, associated nonspecific symptoms, longer symptom duration, and delayed presentation. Other variables were similar between the two groups. In a multivariable logistic regression model, gradual symptom onset (adjusted OR 6.7, p = 0.002), prior history of unexplained transient neurologic attack (adjusted OR 10.6, p = 0.031), and presence of nonspecific symptoms (adjusted OR 4.2, p = 0.008) were independent predictors of the final diagnosis of NI-TNA. Conclusions: Distinguishing TIA from nonischemic causes is difficult in the emergency room, with 60% of suspected TIA patients having nonischemic causes on inpatient evaluation. We found 3 clinical features that may be useful in the emergency room triage of transient neurologic attacks. Further study is needed to develop tools that can accurately diagnose TIA.
Background and Purpose-Noninvasive screening for intracranial in-stent stenosis is often limited by artifact because of the stent or associated coils. We aimed to determine the utility of quantitative MRA (QMRA) as a screening tool for detecting intracranial in-stent stenosis. Methods-We reviewed 14 patients who had intracranial stent placement with follow-up QMRA and conventional angiography at our institution. Socio-demographic, medical, clinical, and imaging data were abstracted from medical charts. A blinded interventional neurologist reviewed all angiograms for presence of Ͼ50% in-stent stenosis. We tested QMRA (mL/min) at varying thresholds as a predictor of angiographic results. Results-Among 14 patients (mean age, 62 years; 12 female, 2 male), 13 patients had Neuroform stents placed for wide-neck cerebral aneurysms and 1 patient had a Wingspan stent placement for atherosclerotic stenosis. Lesions were located in the intracranial internal carotid artery in 57.2% (nϭ8), the middle cerebral artery in 14.3% (nϭ2), and vertebrobasilar arteries in 28.6% (nϭ4). On follow-up angiography, 2 patients (14.3%) had Ͼ50% in-stent stenosis on angiography. Time-of-flight MRA was nondiagnostic in each case because of artifact from the stent or coils. A Ͼ20% reduction in vessel-specific blood flow by QMRA was associated with presence of Ͼ50% in-stent stenosis on angiography (Pϭ0.033). As a screening tool to predict Ͼ50% angiographic in-stent stenosis, the sensitivity, specificity, positive predictive value, and negative predictive value of QMRA were 100%, 92%, 67%, and 100%, respectively. Conclusion-We found that QMRA is a promising screening tool to detect intracranial in-stent stenosis.
Inclusion is the deliberate practice of ensuring that each individual is heard, all personal traits are respected, and all can make meaningful contributions to achieve their full potential. As Coronavirus Disease 2019 spreads globally and across the United States, we have viewed this pandemic through the lens of equity and inclusion. Here we discuss how this pandemic has magnified pre-existing health and social disparities and will summarize why inclusion is an essential tool to traverse this uncertain terrain and discuss strategies which can be implemented at organizational and individual levels to improve inclusion and address inequities moving forward.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.