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Can flat-detector CT after successful endovascular treatment predict long-term outcome in patients with large vessel occlusion? An Alberta Stroke Programme Early CT Score-based study.
- Source :
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Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology [Neurol Sci] 2023 Apr; Vol. 44 (4), pp. 1193-1200. Date of Electronic Publication: 2022 Nov 26. - Publication Year :
- 2023
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Abstract
- Purpose: Recent studies postulate a high prognostic value of the Alberta Stroke Programme Early CT Score (ASPECTS) applied on non-contrast whole-brain flat-detector CT (FDCT) after successful endovascular treatment (EVT). The aim of this study was the evaluation of long-term patient outcome after endovascular treatment using postinterventional FDCT.<br />Methods: Using a local database (Stroke Research Consortium in Northern Bavaria, STAMINA), 517 patients with successful endovascular treatment (modified Thrombolysis in Cerebral Infarction (mTICI) ≥ 2B) due to acute ischaemic stroke (AIS) and large vessel occlusion (LVO) of the anterior circulation were recruited retrospectively. In all cases, non-contrast FDCT after EVT was analysed with special focus at ASPECTS. These results were correlated with the functional outcome in long-term (modified Rankin Scale (mRS) shift from pre-stroke to 90 days after discharge).<br />Results: A significant difference in FDCT-ASPECTS compared to the subgroup of favourable vs. unfavourable outcome (Δ mRS) (median ASPECTS 10 (10-9) vs. median ASPECTS 9 (10-7); p = 0,001) could be demonstrated. Multivariable regression analysis revealed FDCT-ASPECTS (OR 0.234, 95% CI - 0.102-0.008, p = 0.022) along with the NHISS at admission (OR 0.169, 95% CI 0.003-0.018, p = 0.008) as independent factors for a favourable outcome. Cut-off point for a favourable outcome (Δ mRS) was identified at an ASPECTS ≥ 8 (sensitivity 90.6%, specificity 35%).<br />Conclusion: For patients with LVO and successful EVT, FDCT-ASPECTS was found to be highly reliable in predicting long-term outcome.<br /> (© 2022. The Author(s).)
Details
- Language :
- English
- ISSN :
- 1590-3478
- Volume :
- 44
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
- Publication Type :
- Academic Journal
- Accession number :
- 36435896
- Full Text :
- https://doi.org/10.1007/s10072-022-06511-z