Related Experiment Videos
Risk score for in-hospital ischemic stroke mortality derived and validated within the Get With the Guidelines-Stroke
Eric E Smith1, Nandavar Shobha, David Dai
1Calgary Stroke Program, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada. eesmith@ucalgary.ca
Background:
There are few validated models for prediction of in-hospital mortality after ischemic stroke. We used Get With the Guidelines-Stroke Program data to derive and validate prediction models for a patient's risk of in-hospital ischemic stroke mortality.
Methods And Results:
Between October 2001 and December 2007, there were 1036 hospitals that contributed 274,988 ischemic stroke patients to this study. The sample was randomly divided into a derivation (60%) and validation (40%) sample. Logistic regression was used to determine the independent predictors of mortality and to assign point scores for a prediction model. We also separately derived and validated a model in the 109,187 patients (39.7%) with a National Institutes of Health Stroke Scale (NIHSS) score recorded. Model discrimination was quantified by calculating the C statistic from the validation sample. In-hospital mortality was 5.5% overall and 5.2% in the subset in which NIHSS score was recorded. Characteristics associated with in-hospital mortality were age, arrival mode (eg, via ambulance versus other mode), history of atrial fibrillation, previous stroke, previous myocardial infarction, carotid stenosis, diabetes mellitus, peripheral vascular disease, hypertension, history of dyslipidemia, current smoking, and weekend or night admission. The C statistic was 0.72 in the overall validation sample and 0.85 in the model that included NIHSS score. A model with NIHSS score alone provided nearly as good discrimination (C statistic 0.83). Plots of observed versus predicted mortality showed excellent model calibration in the validation sample.
Conclusions:
The Get With the Guidelines-Stroke risk model provides clinicians with a well-validated, practical bedside tool for mortality risk stratification. The NIHSS score provides substantial incremental information on a patient's short-term mortality risk and is the strongest predictor of mortality.
Related Concept Videos
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT
Ischemic Stroke l: Introduction
Ischemic Heart Disease: Overview
Atherosclerosis, the primary malefactor, orchestrates this dangerous condition. It manifests as the accumulation of fatty deposits, akin to insidious plaques, within arterial walls. As time elapses, these plaques metamorphose, hardening and narrowing...
Pre-Procedural Guidelines for Assessing Blood Pressure
Ischemic Stroke ll: Pathophysiology
Hemorrhagic Stroke l: Introduction