ArticleStroke2019
Emergency Department Door-to-Puncture Time Since 2014.
Article in Stroke, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 27 citations in OpenAlex.
- Impact of Mobile Stroke Units on Patients With Large Vessel Occlusion Acute Ischemic Stroke: A Prespecified BEST-MSU Substudy.Stroke (Hoboken, N.J.) · 2024Article
- Optimizing Door-to-Groin Puncture Time: The Mayo Clinic Experience.Mayo Clinic proceedings. Innovations, quality & outcomes · 2022Article
- Mobile stroke care expedites intravenous thrombolysis and endovascular thrombectomy.Stroke and vascular neurology · 2022Review
- Association of Medicare-Medicaid Dual Eligibility and Race and Ethnicity With Ischemic Stroke Severity.JAMA network open · 2022Article
- Integrated Stroke System Model Expands Availability of Endovascular Therapy While Maintaining Quality Outcomes.Stroke · 2021Observational
- Management of Acute Ischemic Stroke.Critical care medicine · 2020Review
- Mobile Stroke Unit Computed Tomography Angiography Substantially Shortens Door-to-Puncture Time.Stroke · 2020Article
- Mobile Stroke Units: Bringing Treatment to the Patient.Current treatment options in neurology · 2020Review
Corrections and comments
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Authors and funding
20 authors at 5 institutions in 1 country.
Funding
Abstract
Background and Purpose- The impact of a mobile stroke unit (MSU) on access to intraarterial thrombectomy (IAT) is a prespecified BEST-MSU substudy (Benefits of Stroke Treatment Delivered Using a Mobile Stroke Unit Compared to Standard Management by Emergency Medical Services). On the MSU, IAT decision-making steps, such as computed tomography, neurological exam, and tPA (tissue-type plasminogen activator) treatment are completed before emergency department arrival. We hypothesized that such pre-ED assessment of potential IAT patients on an MSU improves the time from ED arrival to skin puncture time (door-to-puncture-time, DTPT). Methods- BEST-MSU is a prospective comparative effectiveness study of MSU versus standard management by emergency medical services (EMS). We compared ED DTPT among the following groups of MSU and EMS patients: all IAT patients, IAT patients post-tPA, and IAT patients post-tPA meeting thrombolytic adjudication criteria over the first 4 years of the study. Results- From August 2014 to July 2018, a total of 161 patients underwent IAT. Ninety-four patients presented to the ED via the MSU and 67 by EMS. One hundred forty patients received tPA before IAT, 85 in the MSU arm, and 55 in the EMS arm. One hundred twenty-six patients received tPA within thrombolytic adjudication criteria: 76 MSU and 50 EMS. DTPT in minutes was shorter for MSU patients (all IAT MSU versus EMS 89 versus 99, P=0.01; IAT post-tPA MSU versus EMS 93 versus 100, P=0.03; and IAT post-tPA within adjudicated criteria MSU versus EMS 93 versus 99.5, P=0.03). From 2014 to 2018, DTPT decreased at a faster rate for EMS compared with MSU-managed patients, improving by about an hour. Conclusions- Pre-ED IAT evaluation on an MSU results in faster DTPT compared with arrival by EMS. Since 2014, dramatic improvement in ED IAT metrics has attenuated this difference. However, DTPT in all groups indicates substantial room for improvement.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.