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Updated: Feb 10, 2026

Optimized Management of Endovascular Treatment for Acute Ischemic Stroke
Published on: January 18, 2018
Association between comorbid cancer and outcomes among admissions for acute ischemic stroke receiving systemic
1Medical University of South Carolina, College of Pharmacy, Charleston, SC, USA.
Background:
The impact of cancer on outcomes was not assessed in major trials of systemic thrombolysis in acute ischemic stroke.
Aims:
To evaluate the association between comorbid cancer and hospital outcomes among patients receiving systemic thrombolysis for the treatment of acute ischemic stroke.
Methods:
The 2013 and 2014 United States National Inpatient Sample was used to identify adult patients hospitalized for acute ischemic stroke who received systemic thrombolysis. Identified admissions were stratified into two cohorts based on the presence or absence of comorbid cancer. Multivariable logistic regression was performed to determine the association between comorbid cancer and the odds of in-hospital mortality and intracerebral hemorrhage after adjustment for age ≥75 years and comorbid atrial fibrillation.
Results:
A total of 13,993 acute ischemic stroke admissions were treated with systemic thrombolysis. Of these, 3.0% ( n = 416) had comorbid cancer. The overall incidence of in-hospital mortality was 7.0% and intracerebral hemorrhage occurred in 7.6% of patients. Upon multivariable adjustment, comorbid cancer was not associated with an increased odds of in-hospital mortality (odds ratio = 1.24; 95% confidence interval = 0.88-1.76). However, the adjusted odds of intracerebral hemorrhage were higher among those with comorbid cancer (odds ratio = 1.60; 95% confidence interval = 1.17-2.17).
Conclusions:
In this retrospective study of admissions for acute ischemic stroke receiving thrombolysis, comorbid cancer was not associated with a higher odds of in-hospital mortality but was associated with an increased odds of intracerebral hemorrhage. Factors driving this observed association should be explored in data sets containing clinical variables.
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