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1000
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Abstract/Summary
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Background!#!Telemedicine stroke networks are mandatory to provide inter-hospital transfer for mechanical thrombectomy (MT). However, studies on patient selection in daily practice are sparse.!##!Methods!#!Here, we analyzed consecutive patients from 01/2014 to 12/2018 within the supraregional stroke network 'Neurovascular Network of Southwest Bavaria' (NEVAS) in terms of diagnoses after consultation, inter-hospital transfer and predictors for performing MT. Degree of disability was rated by the modified Rankin Scale (mRS), good outcome was defined as mRS ≤ 2. Successful reperfusion was assumed when the modified thrombolysis in cerebral infarction (mTICI) was 2b-3.!##!Results!#!Of 5722 telemedicine consultations, in 14.1% inter-hospital transfer was performed, mostly because of large vessel occlusion (LVO) stroke. A total of n = 350 patients with LVO were shipped via NEVAS to our center for MT. While n = 52 recanalized spontaneously, MT-treatment was performed in n = 178 patients. MT-treated patients had more severe strokes according to the median National institute of health stroke scale (NIHSS) (16 vs. 13, p < 0.001), were more often treated with intravenous thrombolysis (64.5% vs. 51.7%, p = 0.026) and arrived significantly earlier in our center (184.5 versus 228.0 min, p < 0.001). Good outcome (27.5% vs. 30.8%, p = 0.35) and mortality (32.6% versus 23.5%, p = 0.79) were comparable in MT-treated versus no-MT-treated patients. In patients with middle cerebral artery occlusion in the M1 segment or carotid artery occlusion good outcome was twice as often in the MT-group (21.8% vs. 12.8%, p = 0.184). Independent predictors for performing MT were higher NIHSS (OR 1.096), higher ASPECTS (OR 1.28), and earlier time window (OR 0.99).!##!Conclusion!#!Within a telemedicine network stroke care can successfully be organized as only a minority of patients has to be transferred. Our data provide clinical evidence that all MT-eligible patients should be shipped with the fastest transportation modality as possible.
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1000
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Hinweis
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DeepGreen-ID: 1cda89b6e94642e4adf81bf25e6fa7c4 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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