OBJECTIVES: To assess the impact of symptomatic intracerebral hemorrhage (sICH) on outcome of thrombolysis-treated ischemic stroke patients, as additional to recognized prognosticators. METHODS: The study cohort included 985 ischemic stroke patients treated with IV thrombolysis at the Helsinki University Central Hospital (1995-2008). In a multivariable model adjusted for baseline stroke severity, age, onset-to-treatment time, baseline glucose, hyperdense cerebral artery sign, and early infarct signs on baseline imaging, and prior modified Rankin Scale (mRS), we calculated risk ratios (RRs) of patients with sICH (separately per Safe Implementation of Thrombolysis in Stroke[SITS]-Monitoring Study, European Cooperative Acute Stroke Study II [ECASS-II], and National Institute of Neurological Disorders and Stroke [NINDS] definitions) for poor 3-month outcome (mRS 3-6) and mortality. Receiver operating characteristic (ROC) curve and integrated discrimination improvement (IDI) evaluated impact of sICH on outcome. Internal cross-validation of the model was done with bootstrap statistics. RESULTS: The frequency of sICH was 2.1% (SITS), 7.0% (ECASS-II), and 9.4% (NINDS). RRs for poor and fatal outcome, respectively, were 1.7 and 4.8 (SITS), 1.6 and 3.8 (ECASS-II), and 1.6 and 3.4 (NINDS). In IDI analyses, sICH improved prediction model for 3-month mRS of 3-6 and 4-6, respectively, by 1.4% and 3.0% (SITS), 4.0% and 5.9% (ECASS-II), and 4.7% and 6.1% (NINDS). In case of 3-month mRS 5-6 and mortality, it was 6.1% and 5.3% (SITS), 11.3% and 9.3% (ECASS-II), and 10.3% and 8.0% (NINDS). ROC analysis revealed similar results. CONCLUSIONS: Patients with sICH have increased risk of poor and fatal outcome. Compared with recognized stroke prognosticators, contribution of sICH is smaller. Definition-wise, ECASS-II- and NINDS-based sICH contribute relatively more; ECASS-II has the largest contribution to worst outcomes.
OBJECTIVES: To assess the impact of symptomatic intracerebral hemorrhage (sICH) on outcome of thrombolysis-treated ischemic strokepatients, as additional to recognized prognosticators. METHODS: The study cohort included 985 ischemic strokepatients treated with IV thrombolysis at the Helsinki University Central Hospital (1995-2008). In a multivariable model adjusted for baseline stroke severity, age, onset-to-treatment time, baseline glucose, hyperdense cerebral artery sign, and early infarct signs on baseline imaging, and prior modified Rankin Scale (mRS), we calculated risk ratios (RRs) of patients with sICH (separately per Safe Implementation of Thrombolysis in Stroke[SITS]-Monitoring Study, European Cooperative Acute Stroke Study II [ECASS-II], and National Institute of Neurological Disorders and Stroke [NINDS] definitions) for poor 3-month outcome (mRS 3-6) and mortality. Receiver operating characteristic (ROC) curve and integrated discrimination improvement (IDI) evaluated impact of sICH on outcome. Internal cross-validation of the model was done with bootstrap statistics. RESULTS: The frequency of sICH was 2.1% (SITS), 7.0% (ECASS-II), and 9.4% (NINDS). RRs for poor and fatal outcome, respectively, were 1.7 and 4.8 (SITS), 1.6 and 3.8 (ECASS-II), and 1.6 and 3.4 (NINDS). In IDI analyses, sICH improved prediction model for 3-month mRS of 3-6 and 4-6, respectively, by 1.4% and 3.0% (SITS), 4.0% and 5.9% (ECASS-II), and 4.7% and 6.1% (NINDS). In case of 3-month mRS 5-6 and mortality, it was 6.1% and 5.3% (SITS), 11.3% and 9.3% (ECASS-II), and 10.3% and 8.0% (NINDS). ROC analysis revealed similar results. CONCLUSIONS:Patients with sICH have increased risk of poor and fatal outcome. Compared with recognized stroke prognosticators, contribution of sICH is smaller. Definition-wise, ECASS-II- and NINDS-based sICH contribute relatively more; ECASS-II has the largest contribution to worst outcomes.
Authors: Alexander D Horsch; Edwin Bennink; Tom van Seeters; L Jaap Kappelle; Yolanda van der Graaf; Willem P T M Mali; Hugo W A M de Jong; Birgitta K Velthuis; Jan Willem Dankbaar Journal: Cerebrovasc Dis Date: 2018-01-08 Impact factor: 2.762
Authors: Raul G Nogueira; Rishi Gupta; Tudor G Jovin; Elad I Levy; David S Liebeskind; Osama O Zaidat; Ansaar Rai; Joshua A Hirsch; Daniel P Hsu; Marilyn M Rymer; Ashis H Tayal; Ridwan Lin; Sabareesh K Natarajan; Ashish Nanda; Melissa Tian; Qing Hao; Junaid S Kalia; Michael Chen; Alex Abou-Chebl; Thanh N Nguyen; Albert J Yoo Journal: J Neurointerv Surg Date: 2014-01-08 Impact factor: 5.836