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The Large ARtery Intracranial Occlusion Stroke Scale: A New Tool With High Accuracy in Predicting Large Vessel Occlusion
- Source :
- Frontiers in Neurology, Vol 10 (2019)
- Publication Year :
- 2019
- Publisher :
- Frontiers Media S.A., 2019.
-
Abstract
- Objectives: The combination of systemic thrombolysis and mechanical thrombectomy is indicated in patients with ischemic stroke due to a large vessel occlusion (LVO) and these treatments are time-dependent. Rapid identification of patients with suspected LVO also in a prehospital setting could influence the choice of the destination hospital. Aim of this pilot study was to evaluate the predictive role of a new stroke scale for LVO, comparing it to other scores.Patients and Methods: All consecutive patients admitted to our comprehensive stroke center with suspected ischemic stroke were studied with a CT angiography and 5 different stroke scales were applied. The Large ARtery Occlusion (LARIO) stroke scale consists of 5 items including the assessment of facial palsy, language alteration, grip and arm weakness, and the presence of neglect. A Receiving Operating Characteristic curve was evaluated for each stroke scale to explore the level of accuracy in LVO prediction.Results: A total of 145 patients were included in the analysis. LVO was detected in 37.2% of patients. The Area Under Curve of the LARIO score was 0.951 (95%CI: 0.902–0.980), similar to NIHSS and higher than other scales. The cut-off score for best performance of the LARIO stroke scale was higher than 3 (positive predictive value: 77% and negative predictive value: 100%).Conclusion: The LARIO stroke scale is a simple tool, showing high accuracy in detecting LVO, even if with some limitations due to some false positive cases. Its efficacy has to be confirmed in a pre-hospital setting and other centers.
Details
- Language :
- English
- ISSN :
- 16642295
- Volume :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Neurology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.ff8e6dc291147c69323b6d6dc946d39
- Document Type :
- article
- Full Text :
- https://doi.org/10.3389/fneur.2019.00130