J Stroke.  2021 May;23(2):244-252. 10.5853/jos.2020.03622.

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

• Kim YD
• Nam HS
• Yoo J
• Park H
• Sohn SI
• Hong JH
• Kim BM
• Kim DJ
• Bang OY
• Seo WK
• Chung JW
• Lee KY
• Jung YH
• Lee HS
• Ahn SH
• Shin DH
• Choi HY
• Cho HJ
• Baek JH
• Kim GS
• Seo KD
• Kim SH
• Song TJ
• Kim J
• Han SW
• Park JH
• Lee SI
• Heo J
• Choi JK
• Heo JH
• on behalf of the Thrombus Imaging Study Group and the SECRET Study Group

• KMID: 2516413
• DOI: http://doi.org/10.5853/jos.2020.03622

Abstract

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.

Keyword

Ischemia; Stroke; Thrombosis; Thrombolysis; Reperfusion

Figure

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  Figure 1. Patient selection: (A) derivation cohort, (B) validation cohort. MCA, middle cerebral artery; ICA, internal carotid artery; IV t-PA, intravenous tissue plasminogen activator; SECRET, Selection Criteria in Endovascular Thrombectomy and Thrombolytic Therapy; CT, computed tomography.

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  Figure 2. Comparison of receiver operating characteristic (ROC) curves between two models (A) and decision curve analysis (B). (A) ROC curves of the derivation cohorts and area under the curve (AUC) values (model using only clot volume, 0.819; model using both clot volume and good collaterals, 0.876). (B) Decision curve analysis showing that the model using both clot volume and good collaterals was the preferred model.

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  Figure 3. Assessment of discrimination and calibration in the derivation cohort (A, B) and the validation cohort (C, D). (A) Receiver operating characteristic (ROC) curves of the derivation cohort and area under the curve (AUC) values (AUC, 0.876; 95% confidence interval [CI], 0.802 to 0.950). (B) Calibration plot per quartile of the scores in the derivation cohort. (C) ROC curves of the validation cohort and AUC values (AUC, 0.949; 95% CI, 0.886 to 1.000). (D) Calibration plot per quartile of the scores in the validation cohort.

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  Figure 4. Nomogram for predicting successful recanalization within 1 hour after intravenous tissue plasminogen activator.

Reference

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