A risk score for in-hospital death in patients admitted with ischemic or hemorrhagic stroke.

Published online

Journal Article

BACKGROUND: We aimed to derive and validate a single risk score for predicting death from ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). METHODS AND RESULTS: Data from 333 865 stroke patients (IS, 82.4%; ICH, 11.2%; SAH, 2.6%; uncertain type, 3.8%) in the Get With The Guidelines-Stroke database were used. In-hospital mortality varied greatly according to stroke type (IS, 5.5%; ICH, 27.2%; SAH, 25.1%; unknown type, 6.0%; P<0.001). The patients were randomly divided into derivation (60%) and validation (40%) samples. Logistic regression was used to determine the independent predictors of mortality and to assign point scores for a prediction model in the overall population and in the subset with the National Institutes of Health Stroke Scale (NIHSS) recorded (37.1%). The c statistic, a measure of how well the models discriminate the risk of death, was 0.78 in the overall validation sample and 0.86 in the model including NIHSS. The model with NIHSS performed nearly as well in each stroke type as in the overall model including all types (c statistics for IS alone, 0.85; for ICH alone, 0.83; for SAH alone, 0.83; uncertain type alone, 0.86). The calibration of the model was excellent, as demonstrated by plots of observed versus predicted mortality. CONCLUSIONS: A single prediction score for all stroke types can be used to predict risk of in-hospital death following stroke admission. Incorporation of NIHSS information substantially improves this predictive accuracy.

Full Text

Duke Authors

Cited Authors

  • Smith, EE; Shobha, N; Dai, D; Olson, DM; Reeves, MJ; Saver, JL; Hernandez, AF; Peterson, ED; Fonarow, GC; Schwamm, LH

Published Date

  • January 28, 2013

Published In

Volume / Issue

  • 2 / 1

Start / End Page

  • e005207 -

PubMed ID

  • 23525444

Pubmed Central ID

  • 23525444

Electronic International Standard Serial Number (EISSN)

  • 2047-9980

Digital Object Identifier (DOI)

  • 10.1161/JAHA.112.005207

Language

  • eng

Conference Location

  • England