Stroke severity and residual flow determined by transcranial colour-coded ultrasound (TCCD) predict recanalization and clinical outcome during thrombolysis.

OBJECTIVE: To determine clinical, neuroradiological or ultrasonographic parameters associated with early recanalization and clinical outcome in patients treated with intravenous (IVT) or combined intravenous-intra-arterial (IVT-IAT) thrombolysis.

METHODS: From 2004 to 2007, all consecutive ischemic stroke patients admitted within a 3-hour window and who underwent thrombolytic therapy were reviewed. Degree of occlusion and recanalization during IVT was assessed by transcranial color-coded ultrasound (TCCD) using Thrombolysis In Brain Ischemia (TIBI) classification. According to our protocol, in case of recanalization (modification of TIBI grade > or = 1) after 30 min of IVT, the procedure was maintained over 1h. When TIBI grade failed to improve after 30 min, IVT was discontinued and IAT performed using the remaining tPA dose. The study endpoints were early recanalization defined as achievement of TIBI > or = 3 grade at 30 min (for this endpoint all patients presenting a TIBI grade 3 at admission were excluded from the model) and clinical outcome at 3 months assessed by the modified Rankin scale.

RESULTS: Seventy-one patients underwent either IVT (n=41) or IVT-IAT (n=30). Among all the variables, NIHSS and TIBI grades assessed at baseline were the only independent factors associated with early recanalization and clinical outcome. Furthermore, the combination of these two parameters was superior in predicting early recanalization and outcome to either one of them taken separately. An inverse correlation between NIHSS, TIBI grades and early recanalization was found: the lower the TIBI grade, the lower the probability to recanalize for any given NIHSS.

CONCLUSION: Baseline NIHSS and TIBI grades were the only independent factors associated with early recanalization and clinical outcome. The combination of these two parameters was superior to each single variable in predicting the study endpoints and could therefore be used to improve the selection of patients for IVT or more aggressive therapies.