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Predicting Endovascular Treatment Outcomes in Acute Vertebrobasilar Artery Occlusion: A Model to Aid Patient Selection from the ASIAN KR Registry

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dc.contributor.authorLee, SJ-
dc.contributor.authorHong, JM-
dc.contributor.authorChoi, JW-
dc.contributor.authorPark, JH-
dc.contributor.authorPark, B-
dc.contributor.authorKang, DH-
dc.contributor.authorKim, YW-
dc.contributor.authorKim, YS-
dc.contributor.authorHong, JH-
dc.contributor.authorYoo, J-
dc.contributor.authorKim, CH-
dc.contributor.authorSohn, SI-
dc.contributor.authorHwang, YH-
dc.contributor.authorLee, JS-
dc.date.accessioned2022-10-28T05:28:48Z-
dc.date.available2022-10-28T05:28:48Z-
dc.date.issued2020-
dc.identifier.issn0033-8419-
dc.identifier.urihttp://repository.ajou.ac.kr/handle/201003/22436-
dc.description.abstractBackground 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.isoen-
dc.subject.MESHAged-
dc.subject.MESHAged, 80 and over-
dc.subject.MESHArea Under Curve-
dc.subject.MESHArterial Occlusive Diseases-
dc.subject.MESHBasilar Artery-
dc.subject.MESHEndovascular Procedures-
dc.subject.MESHFemale-
dc.subject.MESHHumans-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHModels, Statistical-
dc.subject.MESHRegistries-
dc.subject.MESHTreatment Outcome-
dc.subject.MESHVertebral Artery-
dc.titlePredicting Endovascular Treatment Outcomes in Acute Vertebrobasilar Artery Occlusion: A Model to Aid Patient Selection from the ASIAN KR Registry-
dc.typeArticle-
dc.identifier.pmid31990269-
dc.contributor.affiliatedAuthorLee, SJ-
dc.contributor.affiliatedAuthorHong, JM-
dc.contributor.affiliatedAuthorPark, B-
dc.contributor.affiliatedAuthorLee, JS-
dc.type.localJournal Papers-
dc.identifier.doi10.1148/radiol.2020191227-
dc.citation.titleRadiology-
dc.citation.volume294-
dc.citation.number3-
dc.citation.date2020-
dc.citation.startPage628-
dc.citation.endPage637-
dc.identifier.bibliographicCitationRadiology, 294(3). : 628-637, 2020-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.identifier.eissn1527-1315-
dc.relation.journalidJ000338419-
Appears in Collections:
Journal Papers > School of Medicine / Graduate School of Medicine > Neurology
Journal Papers > School of Medicine / Graduate School of Medicine > Biomedical Informatics
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