Background: Recent clinical trials have established the efficacy of endovascular stroke therapy and intravenous thrombolysis using advanced imaging, particularly computed tomography perfusion (CTP). The availability and utilization of CTP for patients and hospitals that treat acute ischemic stroke (AIS), however, is uncertain. Methods: We performed a retrospective cross-sectional analysis using 2 complementary Medicare datasets, full sample Texas and 5% national fee-for-service data from 2014 to 2017. AIS cases were identified using International Classification of Diseases, Ninth Revision and International Classification of Diseases, Tenth Revision coding criteria. Imaging utilization performed in the initial evaluation of patients with AIS was derived using Current Procedural Terminology codes from professional claims. Primary outcomes were utilization of imaging in AIS cases and the change in utilization over time. Hospitals were defined as imaging modality–performing if they submitted at least 1 claim for that modality per calendar year. The National Medicare dataset was used to validate state-level findings, and a local hospital-level cohort was used to validate the claims-based approach. Results: Among 50 797 AIS cases in the Texas Medicare fee-for-service cohort, 64% were evaluated with noncontrast head CT, 17% with CT angiography, 3% with CTP, and 33% with magnetic resonance imaging. CTP utilization was greater in patients treated with endovascular stroke therapy (17%) and intravenous thrombolysis (9%). CT angiography (4%/y) and CTP (1%/y) utilization increased over the study period. These findings were validated in the National dataset. Among hospitals in the Texas cohort, 100% were noncontrast head CT–performing, 77% CT angiography–performing, and 14% CTP-performing in 2017. Most AIS cases (69%) were evaluated at non-CTP–performing hospitals. CTP-performing hospitals were clustered in urban areas, whereas large regions of the state lacked immediate access. Conclusions: In state-wide and national Medicare fee-for-service cohorts, CTP utilization in patients with AIS was low, and most patients were evaluated at non-CTP–performing hospitals. These findings support the need for alternative means of screening for AIS recanalization therapies.

Background and Purpose: Noncontrast head CT and CT perfusion (CTP) are both used to screen for endovascular stroke therapy (EST), but the impact of imaging strategy on likelihood of EST is undetermined. Here, we examine the influence of CTP utilization on likelihood of EST in patients with large vessel occlusion (LVO). Methods: We identified patients with acute ischemic stroke at 4 comprehensive stroke centers. All 4 hospitals had 24/7 CTP and EST capability and were covered by a single physician group (Neurology, NeuroIntervention, NeuroICU). All centers performed noncontrast head CT and CT angiography in the initial evaluation. One center also performed CTP routinely with high CTP utilization (CTP-H), and the others performed CTP optionally with lower utilization (CTP-L). Primary outcome was likelihood of EST. Multivariable logistic regression was used to determine whether facility type (CTP-H versus CTP-L) was associated with EST adjusting for age, prestroke mRS, National Institutes of Health Stroke Scale, Alberta Stroke Program Early CT Score, LVO location, time window, and intravenous tPA (tissue-type plasminogen activator). Results: Among 3107 patients with acute ischemic stroke, 715 had LVO, of which 403 (56%) presented to CTP-H and 312 (44%) presented to CTP-L. CTP utilization among LVO patients was greater at CTP-H centers (72% versus 18%, CTP-H versus CTP-L, P <0.01). In univariable analysis, EST rates for patients with LVO were similar between CTP-H versus CTP-L (46% versus 49%). In multivariable analysis, patients with LVO were less likely to undergo EST at CTP-H (odds ratio, 0.59 [0.41–0.85]). This finding was maintained in multiple patient subsets including late time window, anterior circulation LVO, and direct presentation patients. Ninety-day functional independence (odds ratio, 1.04 [0.70–1.54]) was not different, nor were rates of post-EST PH-2 hemorrhage (1% versus 1%). Conclusions: We identified an increased likelihood for undergoing EST in centers with lower CTP utilization, which was not associated with worse clinical outcomes or increased hemorrhage. These findings suggest under-treatment bias with routine CTP.

BackgroundPrior studies on rupture risk of brain arteriovenous malformations (AVMs) in women undergoing pregnancy and delivery have reported conflicting findings, but also have not accounted for AVM morphology and heterogeneity. Here, we assess the association between pregnancy and the risk of intracranial hemorrhage (ICH) in women with AVMs using a cohort-crossover design in which each woman serves as her own control.MethodsWomen who underwent pregnancy and delivery were identified using DRG codes from the Healthcare Cost and Utilization Project State Inpatient Databases for California (2005–2011), Florida (2005–2014), and New York (2005–2014). The presence of AVM and ICH was determined using ICD 9 codes. Pregnancy was defined as the 40 weeks prior to delivery, and postpartum as 12 weeks after. We defined a non-exposure control period as a 52-week period prior to pregnancy. The relative risks of ICH during pregnancy were compared against the non-exposure period using conditional Poisson regression.ResultsAmong 4 022 811 women identified with an eligible delivery hospitalization (median age, 28 years; 7.3% with gestational diabetes; 4.5% with preeclampsia/eclampsia), 568 (0.014%) had an AVM. The rates of ICH during pregnancy and puerperium were 6355.4 (95% CI 4279.4 to 8431.5) and 14.4 (95% CI 13.3 to 15.6) per 100 000 person-years for women with and without AVM, respectively. In cohort-crossover analysis, in women with AVMs the risk of ICH increased 3.27-fold (RR, 95% CI 1.67 to 6.43) during pregnancy and puerperium compared with a non-pregnant period.ConclusionsAmong women with AVM, pregnancy and puerperium were associated with a greater than 3-fold risk of ICH.

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Background and Purpose: Prehospital automated large vessel occlusion (LVO) detection in Mobile Stroke Units (MSUs) could accelerate identification and treatment of patients with LVO acute ischemic stroke. Here, we evaluate the performance of a machine learning (ML) model on CT angiograms (CTAs) obtained from 2 MSUs to detect LVO. Methods: Patients evaluated on MSUs in Houston and Los Angeles with out-of-hospital CTAs were identified. Anterior circulation LVO was defined as an occlusion of the intracranial internal carotid artery, middle cerebral artery (M1 or M2), or anterior cerebral artery vessels and determined by an expert human reader. A ML model to detect LVO was trained and tested on independent data sets consisting of in-hospital CTAs and then tested on MSU CTA images. Model performance was determined using area under the receiver-operator curve statistics. Results: Among 68 patients with out-of-hospital MSU CTAs, 40% had an LVO. The most common occlusion location was the middle cerebral artery M1 segment (59%), followed by the internal carotid artery (30%), and middle cerebral artery M2 (11%). Median time from last known well to CTA imaging was 88.0 (interquartile range, 59.5–196.0) minutes. After training on 870 in-hospital CTAs, the ML model performed well in identifying LVO in a separate in-hospital data set of 441 images with area under receiver-operator curve of 0.84 (95% CI, 0.80–0.87). ML algorithm analysis time was under 1 minute. The performance of the ML model on the MSU CTA images was comparable with area under receiver-operator curve 0.80 (95% CI, 0.71–0.89). There was no significant difference in performance between the Houston and Los Angeles MSU CTA cohorts. Conclusions: In this study of patients evaluated on MSUs in 2 cities, a ML algorithm was able to accurately and rapidly detect LVO using prehospital CTA acquisitions.