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Prediction of Early Recanalization after Intravenous Thrombolysis in Patients with Large-Vessel Occlusion

 Young Dae Kim  ;  Hyo Suk Nam  ;  Joonsang Yoo  ;  Hyungjong Park  ;  Sung-Il Sohn  ;  Jeong-Ho Hong  ;  Byung Moon Kim  ;  Dong Joon Kim  ;  Oh Young Bang  ;  Woo-Keun Seo  ;  Jong-Won Chung  ;  Kyung-Yul Lee  ;  Yo Han Jung  ;  Hye Sun Lee  ;  Seong Hwan Ahn  ;  Dong Hoon Shin  ;  Hye-Yeon Choi  ;  Han-Jin Cho  ;  Jang-Hyun Baek  ;  Gyu Sik Kim  ;  Kwon-Duk Seo  ;  Seo Hyun Kim  ;  Tae-Jin Song  ;  Jinkwon Kim  ;  Sang Won Han  ;  Joong Hyun Park  ;  Sung Ik Lee  ;  JoonNyung Heo  ;  Jin Kyo Choi  ;  Ji Hoe Heo 
 JOURNAL OF STROKE, Vol.23(2) : 244-252, 2021-05 
Journal Title
Issue Date
Ischemia ; Reperfusion ; Stroke ; Thrombolysis ; Thrombosis
Background and purpose: We aimed to develop a model predicting early recanalization after intravenous tissue plasminogen activator (t-PA) treatment in large-vessel occlusion.

Methods: Using data from two different multicenter prospective cohorts, we determined the factors associated with early recanalization immediately after t-PA in stroke patients with large-vessel occlusion, and developed and validated a prediction model for early recanalization. Clot volume was semiautomatically measured on thin-section computed tomography using software, and the degree of collaterals was determined using the Tan score. Follow-up angiographic studies were performed immediately after t-PA treatment to assess early recanalization.

Results: Early recanalization, assessed 61.0±44.7 minutes after t-PA bolus, was achieved in 15.5% (15/97) in the derivation cohort and in 10.5% (8/76) in the validation cohort. Clot volume (odds ratio [OR], 0.979; 95% confidence interval [CI], 0.961 to 0.997; P=0.020) and good collaterals (OR, 6.129; 95% CI, 1.592 to 23.594; P=0.008) were significant factors associated with early recanalization. The area under the curve (AUC) of the model including clot volume was 0.819 (95% CI, 0.720 to 0.917) and 0.842 (95% CI, 0.746 to 0.938) in the derivation and validation cohorts, respectively. The AUC improved when good collaterals were added (derivation cohort: AUC, 0.876; 95% CI, 0.802 to 0.950; P=0.164; validation cohort: AUC, 0.949; 95% CI, 0.886 to 1.000; P=0.036). The integrated discrimination improvement also showed significantly improved prediction (0.097; 95% CI, 0.009 to 0.185; P=0.032).

Conclusions: The model using clot volume and collaterals predicted early recanalization after intravenous t-PA and had a high performance. This model may aid in determining the recanalization treatment strategy in stroke patients with large-vessel occlusion.
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Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurology (신경과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Yonsei Biomedical Research Center (연세의생명연구원) > 1. Journal Papers
Yonsei Authors
Kim, Dong Joon(김동준) ORCID logo https://orcid.org/0000-0002-7035-087X
Kim, Byung Moon(김병문) ORCID logo https://orcid.org/0000-0001-8593-6841
Kim, Young Dae(김영대) ORCID logo https://orcid.org/0000-0001-5750-2616
Kim, Jinkwon(김진권) ORCID logo https://orcid.org/0000-0003-0156-9736
Nam, Hyo Suk(남효석) ORCID logo https://orcid.org/0000-0002-4415-3995
Park, Hyungjong(박형종)
Yoo, Joon Sang(유준상) ORCID logo https://orcid.org/0000-0003-1169-6798
Lee, Kyung Yul(이경열) ORCID logo https://orcid.org/0000-0001-5585-7739
Lee, Hye Sun(이혜선) ORCID logo https://orcid.org/0000-0001-6328-6948
Jung, Yo Han(정요한) ORCID logo https://orcid.org/0000-0002-3048-4718
Heo, JoonNyung(허준녕)
Heo, Ji Hoe(허지회) ORCID logo https://orcid.org/0000-0001-9898-3321
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