| Literature DB >> 30580732 |
Thomas Gattringer1, Alexandra Posekany2, Kurt Niederkorn1, Michael Knoflach3, Birgit Poltrum1, Sebastian Mutzenbach4, Hans-Peter Haring5, Julia Ferrari6, Wilfried Lang6, Johann Willeit3, Stefan Kiechl3, Christian Enzinger1, Franz Fazekas1.
Abstract
Background and Purpose- Several risk factors are known to increase mid- and long-term mortality of ischemic stroke patients. Information on predictors of early stroke mortality is scarce but often requested in clinical practice. We therefore aimed to develop a rapidly applicable tool for predicting early mortality at the stroke unit. Methods- We used data from the nationwide Austrian Stroke Unit Registry and multivariate regularized logistic regression analysis to identify demographic and clinical variables associated with early (≤7 days poststroke) mortality of patients admitted with ischemic stroke. These variables were then used to develop the Predicting Early Mortality of Ischemic Stroke score that was validated both by bootstrapping and temporal validation. Results- In total, 77 653 ischemic stroke patients were included in the analysis (median age: 74 years, 47% women). The mortality rate at the stroke unit was 2% and median stay of deceased patients was 3 days. Age, stroke severity measured by the National Institutes of Health Stroke Scale, prestroke functional disability (modified Rankin Scale >0), preexisting heart disease, diabetes mellitus, posterior circulation stroke syndrome, and nonlacunar stroke cause were associated with mortality and served to build the Predicting Early Mortality of Ischemic Stroke score ranging from 0 to 12 points. The area under the curve of the score was 0.879 (95% CI, 0.871-0.886) in the derivation cohort and 0.884 (95% CI, 0.863-0.905) in the validation sample. Patients with a score ≥10 had a 35% (95% CI, 28%-43%) risk to die within the first days at the stroke unit. Conclusions- We developed a simple score to estimate early mortality of ischemic stroke patients treated at a stroke unit. This score could help clinicians in short-term prognostication for management decisions and counseling.Entities:
Keywords: brain ischemia; heart diseases; mortality; risk factors; stroke
Mesh:
Year: 2019 PMID: 30580732 DOI: 10.1161/STROKEAHA.118.022863
Source DB: PubMed Journal: Stroke ISSN: 0039-2499 Impact factor: 7.914