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Predicting Endovascular Treatment Outcomes in Acute Vertebrobasilar Artery Occlusion: A Model to Aid Patient Selection from the ASIAN KR Registry
DC Field | Value | Language |
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dc.contributor.author | Lee, SJ | - |
dc.contributor.author | Hong, JM | - |
dc.contributor.author | Choi, JW | - |
dc.contributor.author | Park, JH | - |
dc.contributor.author | Park, B | - |
dc.contributor.author | Kang, DH | - |
dc.contributor.author | Kim, YW | - |
dc.contributor.author | Kim, YS | - |
dc.contributor.author | Hong, JH | - |
dc.contributor.author | Yoo, J | - |
dc.contributor.author | Kim, CH | - |
dc.contributor.author | Sohn, SI | - |
dc.contributor.author | Hwang, YH | - |
dc.contributor.author | Lee, JS | - |
dc.date.accessioned | 2022-10-28T05:28:48Z | - |
dc.date.available | 2022-10-28T05:28:48Z | - |
dc.date.issued | 2020 | - |
dc.identifier.issn | 0033-8419 | - |
dc.identifier.uri | http://repository.ajou.ac.kr/handle/201003/22436 | - |
dc.description.abstract | Background The decision to perform endovascular treatment (EVT) for stroke related to vertebrobasilar occlusion (VBO) remains controversial. Purpose To identify preprocedural predictors of good outcomes and to develop a model to aid patient selection for VBO. Materials and Methods For this retrospective study using a Korean multicenter registry, a predictive model for good outcomes (modified Rankin scale score, 0-2) was generated based on a derivation sample of patients with VBO (January 2011-February 2016). Preprocedural parameters, including onset-to-puncture time, infarct volume, occlusion type as a surrogate marker of intracranial atherosclerotic stenosis-related occlusion or embolic occlusion (truncal-type occlusion vs branching site occlusion), and collateral status, were analyzed. Continuous variables were dichotomized based on receiver operating characteristic analysis. Multiple logistic regression analysis was performed to generate a predictive model. The model was internally validated with the bootstrap method and was externally validated with a single-center sample (April 2016-December 2018). Results A predictive model was generated from 71 patients (mean age, 67 years +/- 11 [standard deviation]; 41 [58%] men) and was externally validated in 32 patients (mean age, 72 years +/- 13; 19 [59%] men). The composite of initial DW imaging volume of less than 10 mL (odds ratio [OR], 19.3; 95% confidence interval [CI]: 3.0, 126.4; P = .002), onset-to-puncture time of less than 8 hours (OR, 8.7; 95% CI: 1.8, 42.0; P = .007), and branching-site occlusion (OR, 6.1; 95% CI: 1.5, 26.0; P = .01) could be used to predict good outcomes, with a median area under the receiver operating characteristic curve of 0.86 (interquartile range [IQR], 0.77-0.95; bootstrap optimism-corrected C statistic, 0.837) in the derivation sample and 0.78 (IQR, 0.62-0.95) in the validation sample. Results failed to show an association between collateral status and outcome (P = .67). Conclusion When selecting patients with vertebrobasilar occlusion for endovascular treatment, the combination of onset-to-puncture time of less than 8 hours, initial infarct volume of less than 10 mL, and presence of branching-site occlusions is indicative of a good outcome. | - |
dc.language.iso | en | - |
dc.subject.MESH | Aged | - |
dc.subject.MESH | Aged, 80 and over | - |
dc.subject.MESH | Area Under Curve | - |
dc.subject.MESH | Arterial Occlusive Diseases | - |
dc.subject.MESH | Basilar Artery | - |
dc.subject.MESH | Endovascular Procedures | - |
dc.subject.MESH | Female | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Male | - |
dc.subject.MESH | Middle Aged | - |
dc.subject.MESH | Models, Statistical | - |
dc.subject.MESH | Registries | - |
dc.subject.MESH | Treatment Outcome | - |
dc.subject.MESH | Vertebral Artery | - |
dc.title | Predicting Endovascular Treatment Outcomes in Acute Vertebrobasilar Artery Occlusion: A Model to Aid Patient Selection from the ASIAN KR Registry | - |
dc.type | Article | - |
dc.identifier.pmid | 31990269 | - |
dc.contributor.affiliatedAuthor | Lee, SJ | - |
dc.contributor.affiliatedAuthor | Hong, JM | - |
dc.contributor.affiliatedAuthor | Park, B | - |
dc.contributor.affiliatedAuthor | Lee, JS | - |
dc.type.local | Journal Papers | - |
dc.identifier.doi | 10.1148/radiol.2020191227 | - |
dc.citation.title | Radiology | - |
dc.citation.volume | 294 | - |
dc.citation.number | 3 | - |
dc.citation.date | 2020 | - |
dc.citation.startPage | 628 | - |
dc.citation.endPage | 637 | - |
dc.identifier.bibliographicCitation | Radiology, 294(3). : 628-637, 2020 | - |
dc.embargo.liftdate | 9999-12-31 | - |
dc.embargo.terms | 9999-12-31 | - |
dc.identifier.eissn | 1527-1315 | - |
dc.relation.journalid | J000338419 | - |
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