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Gattringer, T.* ; Posekany, A.* ; Niederkorn, K.* ; Knoflach, M.* ; Poltrum, B.* ; Mutzenbach, S.* ; Häring, H.-U. ; Ferrari, J.* ; Lang, W.* ; Willeit, J.* ; Kiechl, S.* ; Enzinger, C.* ; Fazekas, F.*

Predicting early mortality of acute ischemic stroke.

Stroke 50, 349-356 (2019)
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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.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Brain Ischemia ; Heart Diseases ; Mortality ; Risk Factors ; Stroke
ISSN (print) / ISBN 0039-2499
e-ISSN 1524-4628
Journal Stroke
Quellenangaben Volume: 50, Issue: 2, Pages: 349-356 Article Number: , Supplement: ,
Publisher Lippincott Williams & Wilkins
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Diabetes Research and Metabolic Diseases (IDM)