SynthesisInternational journal of stroke : official journal of the International Stroke Society2019
Clinical prediction of thrombectomy eligibility: A systematic review and 4-item decision tree.
Synthesis in International journal of stroke : official journal of the International Stroke Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Article
- Sex Differences in Prehospital Identification of Large Vessel Occlusion in Patients With Suspected Stroke.Stroke · 2024Article
- Effect of region-wide use of prehospital stroke triage scale on management of patients with acute stroke.Journal of neurointerventional surgery · 2022Article
- Comparison of Prehospital Scales for Predicting Large Anterior Vessel Occlusion in the Ambulance Setting.JAMA neurology · 2021Observational
- Electroencephalography Might Improve Diagnosis of Acute Stroke and Large Vessel Occlusion.Stroke · 2020Article
- External validation of stroke mimic prediction scales in the emergency department.BMC neurology · 2020Article
- Endovascular Treatment of Acute Ischemic Stroke.Current treatment options in cardiovascular medicine · 2019Review
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA clinical large anterior vessel occlusion (LAVO)-prediction scale could reduce treatment delays by allocating intra-arterial thrombectomy (IAT)-eligible patients directly to a comprehensive stroke center.
aimTo subtract, validate and compare existing LAVO-prediction scales, and develop a straightforward decision support tool to assess IAT-eligibility.
methodsWe performed a systematic literature search to identify LAVO-prediction scales. Performance was compared in a prospective, multicenter validation cohort of the Dutch acute Stroke study (DUST) by calculating area under the receiver operating curves (AUROC). With group lasso regression analysis, we constructed a prediction model, incorporating patient characteristics next to National Institutes of Health Stroke Scale (NIHSS) items. Finally, we developed a decision tree algorithm based on dichotomized NIHSS items.
resultsWe identified seven LAVO-prediction scales. From DUST, 1316 patients (35.8% LAVO-rate) from 14 centers were available for validation. FAST-ED and RACE had the highest AUROC (both >0.81,
conclusionExternal validation of seven LAVO-prediction scales showed AUROCs between 0.75 and 0.83. Most scales, however, appear too complex for Emergency Medical Services use with prehospital validation generally lacking. GACE is the first LAVO-prediction scale using a simple decision tree as such increasing feasibility, while maintaining high accuracy. Prehospital prospective validation is planned.
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