Characteristics of in-hospital onset ischemic stroke

Eur Neurol. 2006;55(3):155-9. doi: 10.1159/000093574. Epub 2006 May 29.

Abstract

Background and purpose: The aim of the present study was to clarify the clinical characteristics of in-hospital onset stroke.

Material and methods: We analyzed 15,815 patients with acute brain infarction registered in the Japan Multicenter Stroke Investigators' Collaboration (J-MUSIC) registry.

Results: The in-hospital onset group included 694 (4.4%) patients and the out-of-hospital group included 15,121 (95.6%) patients. Atrial fibrillation (AF) was more common in the in-hospital onset group (34.6%) than in the out-of-hospital group (20.4%, p < 0.001). The admission NIHSS score (median, in-hospital 13 vs. out-of-hospital 5, p < 0.0001) and the mortality rate at discharge were higher in the in-hospital group than in the out-of-hospital group (in-hospital 19.2% vs. out-of-hospital 6.8%, p < 0.0001). On multivariate logistic regression analyses, female gender (OR 1.1, 95% CI 1.1-1.3), older age (OR 1.0, 95% CI 1.02-1.03), AF (OR 4.4, 95% CI 4.0-4.8), history of stroke (OR 1.3, 95% CI 1.2-1.4) and in-hospital stroke onset (OR 3.3, 95 %CI 2.7-3.9) were independent factors associated with severe stroke (NIHSS score > or =11), and older age (OR 1.03, 95% CI 1.02-1.04), the presence of AF (OR 1.21, 95% CI 1.0-1.5), in-hospital stroke onset (OR 1.01, 95% CI 1.01-1.02) and NIHSS score at initial evaluation (OR 1.15, 95% CI 1.14-1.17) were independent factors associated with death at discharge.

Conclusion: In-hospital stroke onset was not uncommon. The neurological deficits in patients with in-hospital onset stroke were severer and the outcome was worse than in those with out-of-hospital stroke. Therefore, a strategy to reduce in-hospital stroke onset should be implemented.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Atrial Fibrillation / physiopathology
  • Female
  • Hospitalization / statistics & numerical data*
  • Humans
  • Japan / epidemiology
  • Logistic Models
  • Male
  • Medical Staff, Hospital / statistics & numerical data
  • Risk Factors
  • Severity of Illness Index
  • Stroke / epidemiology*
  • Stroke / physiopathology
  • Survival Rate